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matrices.AAINDEX.txt Maven / Gradle / Ivy
H ALTS910101
D The PAM-120 matrix (Altschul, 1991)
R LIT:1713145 PMID:2051488
A Altschul, S.F.
T Amino acid substitution matrices from an information theoretic perspective
J J. Mol. Biol. 219, 555-565 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
3.
-3. 6.
0. -1. 4.
0. -3. 2. 5.
-3. -4. -5. -7. 9.
-1. 1. 0. 1. -7. 6.
0. -3. 1. 3. -7. 2. 5.
1. -4. 0. 0. -5. -3. -1. 5.
-3. 1. 2. 0. -4. 3. -1. -4. 7.
-1. -2. -2. -3. -3. -3. -3. -4. -4. 6.
-3. -4. -4. -5. -7. -2. -4. -5. -3. 1. 5.
-2. 2. 1. -1. -7. 0. -1. -3. -2. -2. -4. 5.
-2. -1. -3. -4. -6. -1. -4. -4. -4. 1. 3. 0. 8.
-4. -4. -4. -7. -6. -6. -6. -5. -2. 0. 0. -6. -1. 8.
1. -1. -2. -2. -3. 0. -1. -2. -1. -3. -3. -2. -3. -5. 6.
1. -1. 1. 0. -1. -2. -1. 1. -2. -2. -4. -1. -2. -3. 1. 3.
1. -2. 0. -1. -3. -2. -2. -1. -3. 0. -3. -1. -1. -4. -1. 2. 4.
-7. 1. -5. -8. -8. -6. -8. -8. -5. -7. -5. -5. -7. -1. -7. -2. -6. 12.
-4. -6. -2. -5. -1. -5. -4. -6. -1. -2. -3. -6. -4. 4. -6. -3. -3. -1. 8.
0. -3. -3. -3. -2. -3. -3. -2. -3. 3. 1. -4. 1. -3. -2. -2. 0. -8. -3. 5.
//
H BENS940101
D Log-odds scoring matrix collected in 6.4-8.7 PAM (Benner et al., 1994)
R LIT:2023094 PMID:7700864
A Benner, S.A., Cohen, M.A. and Gonnet, G.H.
T Amino acid substitution during functionally constrained divergent
evolution of protein sequences
J Protein Engineering 7, 1323-1332 (1994)
* extrapolated to 250 PAM
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.5
-1.7 5.1
0.0 -0.1 3.6
-0.6 -1.5 2.5 5.2
-1.7 -0.4 -1.6 -3.7 12.1
-1.7 2.5 0.1 0.6 -3.2 5.3
-0.7 -0.4 1.1 4.4 -4.7 2.1 5.2
0.8 -0.1 -0.1 0.8 -1.3 -1.6 0.5 5.8
-2.1 1.8 1.4 0.1 -1.2 3.2 -0.2 -2.1 6.1
0.1 -3.8 -2.5 -4.2 -3.6 -3.8 -4.1 -3.4 -3.7 4.4
-1.3 -3.2 -3.4 -5.3 -3.8 -2.4 -5.0 -4.6 -2.2 2.4 4.8
-1.9 4.3 1.0 -0.2 -2.8 2.5 0.9 -1.4 0.9 -3.8 -4.1 5.6
-0.2 -3.0 -2.5 -4.3 -3.7 -3.1 -4.1 -3.7 -3.4 4.0 2.9 -2.9 4.8
-3.2 -4.9 -3.5 -5.7 -0.1 -4.4 -6.7 -5.7 0.1 0.0 2.4 -6.3 -0.1 8.3
1.1 -1.3 -1.1 -2.8 -2.7 0.1 -2.6 -1.7 -0.4 -2.0 -0.2 -2.3 -1.8 -3.2 6.5
1.4 -0.9 1.2 -0.4 0.9 -1.4 -1.2 0.8 -0.9 -1.2 -1.5 -1.2 -1.3 -1.8 1.4 2.1
1.7 -1.3 0.5 -1.2 -1.5 -1.7 -1.6 -0.5 -1.7 0.7 -0.4 -1.1 0.6 -2.4 0.6 1.5 2.4
-4.3 2.0 -4.4 -6.3 1.6 -2.6 -5.6 -1.7 -2.8 -5.0 -3.0 -1.4 -4.4 -1.6 -4.8 -2.9 -2.6 14.7
-4.0 -2.6 -0.9 -2.3 2.6 -1.4 -4.1 -4.9 4.4 -3.3 -1.6 -4.0 -3.6 5.6 -3.8 -1.8 -3.4 -0.3 9.5
0.7 -3.7 -2.4 -3.3 -3.1 -3.5 -3.0 -2.3 -3.8 3.9 1.9 -3.8 3.3 -0.5 -1.6 -0.9 0.6 -4.8 -3.8 4.0
//
H BENS940102
D Log-odds scoring matrix collected in 22-29 PAM (Benner et al., 1994)
R LIT:2023094 PMID:7700864
A Benner, S.A., Cohen, M.A. and Gonnet, G.H.
T Amino acid substitution during functionally constrained divergent
evolution of protein sequences
J Protein Engineering 7, 1323-1332 (1994)
* extrapolated to 250 PAM
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.5
-1.2 5.0
0.0 0.4 3.3
-0.2 -1.0 2.4 4.8
-1.2 -1.6 -1.9 -3.7 12.6
-0.9 2.2 0.5 0.6 -3.3 4.2
-0.3 -0.1 1.2 3.9 -4.3 1.7 4.6
0.8 -0.7 0.4 0.7 -1.7 -1.4 0.5 6.2
-1.6 1.5 1.4 0.3 -1.5 2.4 -0.2 -2.0 6.1
-0.4 -3.2 -2.7 -4.0 -2.4 -2.7 -3.6 -3.8 -3.2 4.2
-1.7 -2.9 -3.5 -4.9 -2.6 -2.0 -4.4 -4.9 -2.1 2.7 4.6
-1.0 3.9 1.0 0.2 -3.3 2.2 1.0 -1.0 0.8 -3.0 -3.3 4.4
-0.8 -2.1 -2.6 -3.9 -2.5 -1.7 -3.4 -3.8 -2.4 3.1 3.2 -2.0 4.9
-3.1 -4.3 -3.5 -5.4 -0.1 -3.6 -5.7 -5.8 0.3 0.5 2.2 -5.1 0.7 7.7
0.8 -1.2 -1.1 -1.8 -3.1 -0.1 -1.7 -1.8 -0.4 -2.3 -1.3 -1.6 -2.0 -3.4 7.0
1.3 -0.5 1.1 0.1 0.3 -0.6 -0.5 0.6 -0.5 -1.4 -2.1 -0.4 -1.5 -2.2 1.1 2.0
1.4 -0.7 0.5 -0.7 -1.1 -0.7 -0.9 -0.7 -1.1 0.3 -1.0 -0.4 0.1 -2.6 0.4 1.5 2.5
-5.5 -1.1 -5.2 -6.4 0.5 -3.3 -6.3 -4.5 -2.7 -4.4 -1.8 -3.7 -2.8 0.5 -5.8 -3.9 -4.5 15.7
-3.5 -2.7 -1.2 -3.0 0.6 -1.9 -4.0 -4.8 3.7 -2.2 -0.7 -3.6 -1.8 5.9 -3.5 -1.9 -3.0 1.5 9.0
0.4 -2.9 -2.3 -3.0 -1.7 -2.4 -2.7 -2.5 -3.0 3.6 2.0 -2.7 2.5 -0.1 -1.7 -0.9 0.4 -4.5 -2.6 3.7
//
H BENS940103
D Log-odds scoring matrix collected in 74-100 PAM (Benner et al., 1994)
R LIT:2023094 PMID:7700864
A Benner, S.A., Cohen, M.A. and Gonnet, G.H.
T Amino acid substitution during functionally constrained divergent
evolution of protein sequences
J Protein Engineering 7, 1323-1332 (1994)
* extrapolated to 250 PAM
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.4
-0.8 4.8
-0.2 0.3 3.6
-0.3 -0.5 2.2 4.8
0.3 -2.2 -1.8 -3.2 11.8
-0.3 1.6 0.7 0.8 -2.6 3.0
-0.1 0.3 1.0 2.9 -3.2 1.7 3.7
0.6 -1.0 0.4 0.2 -2.0 -1.1 -0.5 6.6
-1.0 1.0 1.2 0.4 -1.3 1.4 0.2 -1.6 6.1
-0.8 -2.6 -2.8 -3.9 -1.2 -2.0 -2.9 -4.3 -2.3 4.0
-1.4 -2.4 -3.1 -4.2 -1.6 -1.7 -3.1 -4.6 -1.9 2.8 4.2
-0.4 2.9 0.9 0.4 -2.9 1.7 1.2 -1.1 0.6 -2.3 -2.4 3.4
-0.8 -1.8 -2.2 -3.2 -1.2 -1.0 -2.2 -3.5 -1.5 2.6 2.9 -1.5 4.5
-2.6 -3.5 -3.2 -4.7 -0.7 -2.8 -4.3 -5.4 0.0 0.9 2.1 -3.6 1.3 7.2
0.4 -1.0 -1.0 -1.0 -3.1 -0.2 -0.7 -1.7 -1.0 -2.6 -2.2 -0.8 -2.4 -3.8 7.5
1.1 -0.2 0.9 0.4 0.1 0.1 0.1 0.4 -0.3 -1.8 -2.2 0.0 -1.4 -2.6 0.5 2.1
0.7 -0.3 0.4 -0.2 -0.6 -0.1 -0.2 -1.0 -0.5 -0.3 -1.1 0.1 -0.4 -2.2 0.1 1.4 2.5
-4.1 -1.6 -4.0 -5.5 -0.9 -2.8 -4.7 -4.1 -1.0 -2.3 -0.9 -3.6 -1.3 3.0 -5.2 -3.4 -3.7 14.7
-2.6 -2.0 -1.4 -2.8 -0.4 -1.8 -3.0 -4.3 2.5 -1.0 -0.1 -2.4 -0.5 5.3 -3.4 -1.9 -2.1 3.6 8.1
0.1 -2.2 -2.2 -2.9 -0.2 -1.7 -2.1 -3.1 -2.1 3.2 1.9 -1.9 1.8 0.1 -1.9 -1.0 0.2 -2.9 -1.4 3.4
//
H BENS940104
D Genetic code matrix (Benner et al., 1994)
R LIT:2023094 PMID:7700864
A Benner, S.A., Cohen, M.A. and Gonnet, G.H.
T Amino acid substitution during functionally constrained divergent
evolution of protein sequences
J Protein Engineering 7, 1323-1332 (1994)
* extrapolated to 250 PAM
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
4.0
-1.6 2.9
-1.7 -1.5 4.7
1.0 -2.3 1.7 4.8
-1.9 0.7 -1.5 -1.6 5.5
-2.1 0.3 0.4 0.3 -3.1 5.5
1.3 -2.0 0.3 3.8 -3.0 2.0 5.7
1.2 0.8 -2.6 1.1 1.0 -2.1 1.4 4.2
-2.1 3.6 1.8 1.7 -1.6 3.6 0.3 -2.2 4.7
-1.8 -1.2 0.9 -2.1 -1.9 -1.9 -2.3 -2.5 -1.8 4.1
-2.3 -0.4 -2.2 -2.4 -1.3 0.1 -2.5 -2.2 -0.1 1.2 3.4
-1.9 -0.2 3.5 0.3 -3.2 2.2 2.0 -2.2 0.6 0.7 -2.0 5.6
-2.0 -0.4 0.1 -2.5 -2.7 -1.2 -1.8 -2.3 -1.8 3.3 1.5 1.6 5.4
-2.4 -1.5 -1.3 -1.7 1.8 -2.1 -2.9 -1.9 -1.1 1.3 2.2 -2.8 0.5 4.5
0.8 0.3 -1.6 -2.2 -1.9 1.0 -2.1 -1.8 0.7 -1.6 0.0 -1.5 -1.4 -1.8 3.8
0.1 0.3 -0.3 -2.1 1.5 -2.3 -2.8 -0.6 -1.6 -0.5 -1.2 -1.5 -1.3 0.0 0.4 2.6
0.9 -0.6 0.9 -2.1 -1.9 -1.7 -2.1 -2.1 -1.8 0.8 -1.9 1.0 0.7 -2.1 1.1 1.0 4.0
-2.2 1.8 -3.0 -2.9 4.1 -2.3 -3.2 1.4 -2.1 -2.2 -0.3 -3.0 -2.0 0.0 -1.6 0.8 -2.2 7.5
-2.4 -1.9 2.5 2.3 2.6 -0.8 -0.9 -1.8 2.3 -1.6 -1.6 -0.8 -2.9 2.0 -2.3 0.3 -2.1 -0.5 6.5
1.0 -2.1 -2.2 1.0 -2.2 -2.0 1.3 1.1 -2.1 1.0 1.1 -2.1 1.0 1.0 -2.1 -2.2 -2.2 -2.1 -2.2 4.1
//
H CSEM940101
D Residue replace ability matrix (Cserzo et al., 1994)
R LIT:2022066 PMID:7966267
A Cserzo, M., Bernassau, J.-M., Simon, I. and Maigret, B.
T New alignment strategy for transmembrane proteins
J J. Mol. Biol. 243, 388-396 (1994)
* Diagonal elements are missing.
* We use 1 as diagonal elements.
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.
-0.07 1.
-0.14 0.12 1.
-0.08 -0.01 0.56 1.
0.04 -0.20 -0.14 -0.24 1.
-0.01 0.57 0.20 0.19 -0.29 1.
0.08 0.34 0.13 0.37 -0.51 0.51 1.
0.11 -0.11 0.22 0.11 0.25 -0.13 -0.23 1.
-0.11 0.13 0.32 0.22 0.18 0.05 -0.19 0.18 1.
-0.10 -0.29 -0.37 -0.54 0.26 -0.43 -0.51 -0.22 -0.14 1.
0.20 -0.20 -0.39 -0.55 0.23 -0.30 -0.45 -0.14 -0.12 0.60 1.
-0.07 0.47 0.22 0.18 -0.43 0.52 0.54 -0.23 -0.09 -0.40 -0.34 1.
0.15 -0.17 -0.11 -0.25 0.10 -0.18 -0.14 -0.01 -0.19 0.36 0.38 -0.16 1.
-0.25 -0.31 -0.33 -0.40 0.30 -0.44 -0.50 -0.09 -0.06 0.60 0.44 -0.41 0.22 1.
-0.07 -0.17 0.05 0.09 0.02 -0.03 -0.11 0.25 0.05 -0.19 -0.20 -0.17 -0.17 -0.12 1.
0.14 -0.16 0.14 0.22 0.10 -0.06 -0.17 0.29 0.14 -0.27 -0.19 -0.24 -0.17 -0.01 0.27 1.
0.11 -0.32 0.13 0.23 0.14 -0.15 -0.27 -0.02 0.08 0.00 -0.04 -0.24 -0.02 0.02 0.20 0.45 1.
-0.25 -0.03 -0.39 -0.41 0.18 -0.17 -0.22 -0.08 -0.11 0.36 0.22 -0.22 0.16 0.41 -0.13 -0.17 -0.12 1.
-0.36 -0.03 -0.27 -0.34 0.21 -0.28 -0.32 -0.24 0.08 0.43 0.17 -0.20 0.07 0.54 -0.23 -0.21 -0.14 0.43 1.
0.06 -0.29 -0.46 -0.48 0.33 -0.38 -0.44 -0.12 -0.18 0.70 0.49 -0.36 0.23 0.47 -0.17 -0.18 0.07 0.29 0.31 1.
//
H DAYM780301
D Log odds matrix for 250 PAMs (Dayhoff et al., 1978)
R
A Dayhoff, M.O., Schwartz, R.M. and Orcutt, B.C.
T A model of evolutionary change in proteins
J In "Atlas of Protein Sequence and Structure", Vol.5, Suppl.3 (Dayhoff,
M.O., ed.), National Biomedical Research Foundation, Washington, D.C.,
p.352 (1978)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.
-2. 6.
0. 0. 2.
0. -1. 2. 4.
-2. -4. -4. -5. 12.
0. 1. 1. 2. -5. 4.
0. -1. 1. 3. -5. 2. 4.
1. -3. 0. 1. -3. -1. 0. 5.
-1. 2. 2. 1. -3. 3. 1. -2. 6.
-1. -2. -2. -2. -2. -2. -2. -3. -2. 5.
-2. -3. -3. -4. -6. -2. -3. -4. -2. 2. 6.
-1. 3. 1. 0. -5. 1. 0. -2. 0. -2. -3. 5.
-1. 0. -2. -3. -5. -1. -2. -3. -2. 2. 4. 0. 6.
-4. -4. -4. -6. -4. -5. -5. -5. -2. 1. 2. -5. 0. 9.
1. 0. -1. -1. -3. 0. -1. -1. 0. -2. -3. -1. -2. -5. 6.
1. 0. 1. 0. 0. -1. 0. 1. -1. -1. -3. 0. -2. -3. 1. 2.
1. -1. 0. 0. -2. -1. 0. 0. -1. 0. -2. 0. -1. -3. 0. 1. 3.
-6. 2. -4. -7. -8. -5. -7. -7. -3. -5. -2. -3. -4. 0. -6. -2. -5. 17.
-3. -4. -2. -4. 0. -4. -4. -5. 0. -1. -1. -4. -2. 7. -5. -3. -3. 0. 10.
0. -2. -2. -2. -2. -2. -2. -1. -2. 4. 2. -2. 2. -1. -1. -1. 0. -6. -2. 4.
//
H FEND850101
D Structure-Genetic matrix (Feng et al., 1985)
R LIT:1107900 PMID:6100188
A Feng, D.F., Johnson, M.S. and Doolittle, R.F.
T Aligning amino acid sequences: comparison of commonly used methods
J J. Mol. Evol. 21, 112-125 (1985)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
6.
2. 6.
3. 2. 6.
4. 2. 5. 6.
2. 2. 2. 1. 6.
3. 3. 3. 4. 1. 6.
4. 2. 3. 5. 0. 4. 6.
5. 3. 3. 4. 3. 2. 4. 6.
2. 4. 4. 3. 2. 4. 2. 1. 6.
2. 2. 2. 1. 2. 1. 1. 2. 1. 6.
2. 2. 1. 1. 2. 2. 1. 2. 3. 5. 6.
3. 5. 4. 3. 0. 4. 4. 2. 3. 2. 2. 6.
2. 2. 1. 0. 2. 2. 1. 1. 1. 4. 5. 2. 6.
2. 1. 1. 1. 3. 1. 0. 1. 2. 4. 4. 0. 2. 6.
5. 3. 2. 2. 2. 3. 3. 3. 3. 2. 3. 2. 2. 2. 6.
5. 3. 5. 3. 4. 3. 3. 5. 3. 2. 2. 3. 1. 3. 4. 6.
5. 3. 4. 2. 2. 3. 3. 2. 2. 3. 2. 4. 3. 1. 4. 5. 6.
2. 2. 0. 0. 3. 1. 1. 3. 1. 2. 4. 1. 3. 3. 2. 2. 1. 6.
2. 1. 3. 2. 3. 2. 1. 2. 3. 3. 3. 1. 2. 5. 2. 3. 2. 3. 6.
5. 2. 2. 3. 2. 2. 4. 4. 1. 5. 5. 3. 4. 4. 3. 2. 3. 3. 3. 6.
//
H FITW660101
D Mutation values for the interconversion of amino acid pairs (Fitch, 1966)
R PMID:5917736
A Fitch, W.M.
T An improved method of testing for evolutionary homology
J J. Mol. Biol. 16, 9-16 (1966)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.
2. 0.
2. 2. 0.
1. 2. 1. 0.
2. 1. 2. 2. 0.
2. 1. 2. 2. 2. 0.
1. 2. 2. 1. 3. 1. 0.
1. 1. 2. 1. 1. 2. 1. 0.
2. 1. 1. 1. 2. 1. 2. 2. 0.
2. 2. 1. 2. 2. 3. 3. 2. 2. 0.
2. 1. 2. 2. 2. 1. 2. 1. 1. 1. 0.
2. 1. 1. 2. 3. 1. 1. 2. 2. 2. 2. 0.
2. 1. 2. 3. 3. 2. 2. 2. 3. 1. 1. 1. 0.
2. 2. 2. 2. 1. 2. 3. 2. 2. 1. 1. 3. 2. 0.
1. 1. 2. 2. 2. 1. 2. 2. 1. 2. 1. 2. 2. 2. 0.
1. 1. 1. 2. 1. 1. 2. 1. 2. 1. 1. 2. 2. 1. 1. 0.
1. 1. 1. 2. 2. 2. 2. 2. 2. 1. 2. 1. 1. 2. 1. 1. 0.
2. 1. 3. 3. 1. 1. 2. 1. 3. 3. 1. 2. 2. 2. 2. 1. 2. 0.
2. 2. 1. 1. 1. 1. 2. 2. 1. 2. 2. 2. 3. 1. 2. 1. 2. 2. 0.
1. 2. 2. 1. 1. 2. 1. 1. 2. 1. 1. 2. 1. 1. 2. 2. 2. 2. 2. 0.
//
H GEOD900101
D Hydrophobicity scoring matrix (George et al., 1990)
R PMID:2314281
A George, D.G., Barker, W.C. and Hunt, L.T.
T Mutation data matrix and its uses
J Methods Enzymol. 183, 333-351 (1990)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
10.
5. 10.
9. 6. 10.
5. 9. 6. 10.
9. 4. 8. 5. 10.
9. 6. 10. 6. 8. 10.
5. 9. 6. 10. 5. 6. 10.
9. 5. 10. 6. 8. 10. 6. 10.
10. 5. 9. 5. 9. 9. 5. 9. 10.
8. 3. 7. 3. 9. 7. 3. 7. 8. 10.
8. 3. 7. 3. 9. 7. 3. 7. 8. 10. 10.
5. 10. 6. 9. 4. 6. 9. 5. 5. 3. 3. 10.
9. 3. 8. 4. 10. 8. 4. 8. 9. 9. 9. 3. 10.
7. 1. 6. 2. 8. 6. 2. 6. 7. 9. 9. 1. 8. 10.
9. 3. 8. 4. 9. 8. 4. 8. 9. 9. 9. 3. 10. 8. 10.
9. 6. 10. 7. 8. 10. 7. 10. 9. 7. 7. 6. 8. 6. 7. 10.
10. 5. 9. 5. 9. 9. 5. 9. 10. 8. 8. 5. 9. 7. 8. 9. 10.
5. 0. 4. 1. 6. 4. 1. 5. 5. 8. 8. 0. 7. 9. 7. 4. 5. 10.
7. 2. 6. 3. 8. 6. 3. 6. 7. 9. 9. 2. 8. 10. 9. 6. 7. 8. 10.
8. 3. 7. 4. 9. 7. 4. 8. 8. 10. 10. 3. 10. 8. 10. 7. 8. 7. 9. 10.
//
H GONG920101
D The mutation matrix for initially aligning (Gonnet et al., 1992)
R LIT:1813110 PMID:1604319
A Gonnet, G.H., Cohen, M.A. and Benner, S.A.
T Exhaustive matching of the entire protein sequence database
J Science 256, 1443-1445 (1992)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.4
-0.6 4.7
-0.3 0.3 3.8
-0.3 -0.3 2.2 4.7
0.5 -2.2 -1.8 -3.2 11.5
-0.2 1.5 0.7 0.9 -2.4 2.7
0.0 0.4 0.9 2.7 -3.0 1.7 3.6
0.5 -1.0 0.4 0.1 -2.0 -1.0 -0.8 6.6
-0.8 0.6 1.2 0.4 -1.3 1.2 0.4 -1.4 6.0
-0.8 -2.4 -2.8 -3.8 -1.1 -1.9 -2.7 -4.5 -2.2 4.0
-1.2 -2.2 -3.0 -4.0 -1.5 -1.6 -2.8 -4.4 -1.9 2.8 4.0
-0.4 2.7 0.8 0.5 -2.8 1.5 1.2 -1.1 0.6 -2.1 -2.1 3.2
-0.7 -1.7 -2.2 -3.0 -0.9 -1.0 -2.0 -3.5 -1.3 2.5 2.8 -1.4 4.3
-2.3 -3.2 -3.1 -4.5 -0.8 -2.6 -3.9 -5.2 -0.1 1.0 2.0 -3.3 1.6 7.0
0.3 -0.9 -0.9 -0.7 -3.1 -0.2 -0.5 -1.6 -1.1 -2.6 -2.3 -0.6 -2.4 -3.8 7.6
1.1 -0.2 0.9 0.5 0.1 0.2 0.2 0.4 -0.2 -1.8 -2.1 0.1 -1.4 -2.8 0.4 2.2
0.6 -0.2 0.5 0.0 -0.5 0.0 -0.1 -1.1 -0.3 -0.6 -1.3 0.1 -0.6 -2.2 0.1 1.5 2.5
-3.6 -1.6 -3.6 -5.2 -1.0 -2.7 -4.3 -4.0 -0.8 -1.8 -0.7 -3.5 -1.0 3.6 -5.0 -3.3 -3.5 14.2
-2.2 -1.8 -1.4 -2.8 -0.5 -1.7 -2.7 -4.0 2.2 -0.7 0.0 -2.1 -0.2 5.1 -3.1 -1.9 -1.9 4.1 7.8
0.1 -2.0 -2.2 -2.9 0.0 -1.5 -1.9 -3.3 -2.0 3.1 1.8 -1.7 1.6 0.1 -1.8 -1.0 0.0 -2.6 -1.1 3.4
//
H GRAR740104
D Chemical distance (Grantham, 1974)
R LIT:2004143 PMID:4843792
A Grantham, R.
T Amino acid difference formula to help explain protein evolution
J Science 185, 862-864 (1974)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.
112. 0.
111. 86. 0.
126. 96. 23. 0.
195. 180. 139. 154. 0.
91. 43. 46. 61. 154. 0.
107. 54. 42. 45. 170. 29. 0.
60. 125. 80. 94. 159. 87. 98. 0.
86. 29. 68. 81. 174. 24. 40. 98. 0.
94. 97. 149. 168. 198. 109. 134. 135. 94. 0.
96. 102. 153. 172. 198. 113. 138. 138. 99. 5. 0.
106. 26. 94. 101. 202. 53. 56. 127. 32. 102. 107. 0.
84. 91. 142. 160. 196. 101. 126. 127. 87. 10. 15. 95. 0.
113. 97. 158. 177. 205. 116. 140. 153. 100. 21. 22. 102. 28. 0.
27. 103. 91. 108. 169. 76. 93. 42. 77. 95. 98. 103. 87. 114. 0.
99. 110. 46. 65. 112. 68. 80. 56. 89. 142. 145. 121. 135. 155. 74. 0.
58. 71. 65. 85. 149. 42. 65. 59. 47. 89. 92. 78. 81. 103. 38. 58. 0.
148. 101. 174. 181. 215. 130. 152. 184. 115. 61. 61. 110. 67. 40. 147. 177. 128. 0.
112. 77. 143. 160. 194. 99. 122. 147. 83. 33. 36. 85. 36. 22. 110. 144. 92. 37. 0.
64. 96. 133. 152. 192. 96. 121. 109. 84. 29. 32. 97. 21. 50. 68. 124. 69. 88. 55. 0.
//
H HENS920101
D BLOSUM45 substitution matrix (Henikoff-Henikoff, 1992)
R LIT:1902106 PMID:1438297
A Henikoff, S. and Henikoff, J.G.
T Amino acid substitution matrices from protein blocks
J Proc. Natl. Acad. Sci. USA 89, 10915-10919 (1992)
* matrix in 1/3 Bit Units
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5.
-2. 7.
-1. 0. 6.
-2. -1. 2. 7.
-1. -3. -2. -3. 12.
-1. 1. 0. 0. -3. 6.
-1. 0. 0. 2. -3. 2. 6.
0. -2. 0. -1. -3. -2. -2. 7.
-2. 0. 1. 0. -3. 1. 0. -2. 10.
-1. -3. -2. -4. -3. -2. -3. -4. -3. 5.
-1. -2. -3. -3. -2. -2. -2. -3. -2. 2. 5.
-1. 3. 0. 0. -3. 1. 1. -2. -1. -3. -3. 5.
-1. -1. -2. -3. -2. 0. -2. -2. 0. 2. 2. -1. 6.
-2. -2. -2. -4. -2. -4. -3. -3. -2. 0. 1. -3. 0. 8.
-1. -2. -2. -1. -4. -1. 0. -2. -2. -2. -3. -1. -2. -3. 9.
1. -1. 1. 0. -1. 0. 0. 0. -1. -2. -3. -1. -2. -2. -1. 4.
0. -1. 0. -1. -1. -1. -1. -2. -2. -1. -1. -1. -1. -1. -1. 2. 5.
-2. -2. -4. -4. -5. -2. -3. -2. -3. -2. -2. -2. -2. 1. -3. -4. -3. 15.
-2. -1. -2. -2. -3. -1. -2. -3. 2. 0. 0. -1. 0. 3. -3. -2. -1. 3. 8.
0. -2. -3. -3. -1. -3. -3. -3. -3. 3. 1. -2. 1. 0. -3. -1. 0. -3. -1. 5.
//
H HENS920102
D BLOSUM62 substitution matrix (Henikoff-Henikoff, 1992)
R LIT:1902106 PMID:1438297
A Henikoff, S. and Henikoff, J.G.
T Amino acid substitution matrices from protein blocks
J Proc. Natl. Acad. Sci. USA 89, 10915-10919 (1992)
* matrix in 1/3 Bit Units
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
6.
-2. 8.
-2. -1. 8.
-3. -2. 2. 9.
-1. -5. -4. -5. 13.
-1. 1. 0. 0. -4. 8.
-1. 0. 0. 2. -5. 3. 7.
0. -3. -1. -2. -4. -3. -3. 8.
-2. 0. 1. -2. -4. 1. 0. -3. 11.
-2. -4. -5. -5. -2. -4. -5. -6. -5. 6.
-2. -3. -5. -5. -2. -3. -4. -5. -4. 2. 6.
-1. 3. 0. -1. -5. 2. 1. -2. -1. -4. -4. 7.
-1. -2. -3. -5. -2. -1. -3. -4. -2. 2. 3. -2. 8.
-3. -4. -4. -5. -4. -5. -5. -5. -2. 0. 1. -5. 0. 9.
-1. -3. -3. -2. -4. -2. -2. -3. -3. -4. -4. -2. -4. -5. 11.
2. -1. 1. 0. -1. 0. 0. 0. -1. -4. -4. 0. -2. -4. -1. 6.
0. -2. 0. -2. -1. -1. -1. -2. -3. -1. -2. -1. -1. -3. -2. 2. 7.
-4. -4. -6. -6. -3. -3. -4. -4. -4. -4. -2. -4. -2. 1. -5. -4. -4. 16.
-3. -3. -3. -5. -4. -2. -3. -5. 3. -2. -2. -3. -1. 4. -4. -3. -2. 3. 10.
0. -4. -4. -5. -1. -3. -4. -5. -5. 4. 1. -3. 1. -1. -4. -2. 0. -4. -2. 6.
//
H HENS920103
D BLOSUM80 substitution matrix (Henikoff-Henikoff, 1992)
R LIT:1902106 PMID:1438297
A Henikoff, S. and Henikoff, J.G.
T Amino acid substitution matrices from protein blocks
J Proc. Natl. Acad. Sci. USA 89, 10915-10919 (1992)
* matrix in 1/3 Bit Units
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
7.
-3. 9.
-3. -1. 9.
-3. -3. 2. 10.
-1. -6. -5. -7. 13.
-2. 1. 0. -1. -5. 9.
-2. -1. -1. 2. -7. 3. 8.
0. -4. -1. -3. -6. -4. -4. 9.
-3. 0. 1. -2. -7. 1. 0. -4. 12.
-3. -5. -6. -7. -2. -5. -6. -7. -6. 7.
-3. -4. -6. -7. -3. -4. -6. -7. -5. 2. 6.
-1. 3. 0. -2. -6. 2. 1. -3. -1. -5. -4. 8.
-2. -3. -4. -6. -3. -1. -4. -5. -4. 2. 3. -3. 9.
-4. -5. -6. -6. -4. -5. -6. -6. -2. -1. 0. -5. 0. 10.
-1. -3. -4. -3. -6. -3. -2. -5. -4. -5. -5. -2. -4. -6. 12.
2. -2. 1. -1. -2. -1. -1. -1. -2. -4. -4. -1. -3. -4. -2. 7.
0. -2. 0. -2. -2. -1. -2. -3. -3. -2. -3. -1. -1. -4. -3. 2. 8.
-5. -5. -7. -8. -5. -4. -6. -6. -4. -5. -4. -6. -3. 0. -7. -6. -5. 16.
-4. -4. -4. -6. -5. -3. -5. -6. 3. -3. -2. -4. -3. 4. -6. -3. -3. 3. 11.
-1. -4. -5. -6. -2. -4. -4. -6. -5. 4. 1. -4. 1. -2. -4. -3. 0. -5. -3. 7.
//
H JOHM930101
D Structure-based amino acid scoring table (Johnson-Overington, 1993)
R LIT:1923112 PMID:8411177
A Johnson, M.S. and Overington, J.P.
T A structural basis for sequence comparisons
An evaluation of scoring methodologies
J J. Mol. Biol. 233, 716-738 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
6.0
-1.6 10.0
-1.4 -1.5 8.0
-1.6 -3.4 2.6 8.5
-3.4 -5.6 -7.6 -9.7 16.1
-0.6 2.1 -0.8 -1.1 -6.9 9.0
-0.7 -0.2 -0.7 2.4 -6.9 2.4 8.6
-0.5 -2.8 -1.4 -2.1 -8.2 -2.8 -2.5 8.0
-3.1 0.1 1.7 -0.7 -8.2 1.4 -2.3 -3.2 12.7
-2.2 -5.4 -4.7 -4.8 -7.7 -7.0 -4.8 -5.5 -5.1 8.1
-3.3 -3.7 -4.8 -8.0 -8.7 -4.4 -5.6 -7.2 -4.2 2.6 7.3
-0.9 3.2 0.1 -1.5 -8.7 1.1 1.1 -3.5 0.1 -4.7 -3.4 7.6
-1.5 -4.2 -3.7 -5.9 -4.4 -0.6 -2.8 -5.2 -2.3 2.6 4.4 -1.9 11.2
-3.2 -6.0 -3.8 -7.0 -4.4 -6.4 -6.4 -8.6 -1.7 0.5 1.8 -5.6 -0.6 10.4
-1.0 -3.6 -2.4 -1.0 -8.9 -3.6 -1.5 -2.5 -4.3 -5.7 -2.8 -0.6 -9.8 -5.0 10.3
0.0 -0.6 1.0 -0.2 -7.7 -1.2 -2.2 -1.3 -2.6 -4.7 -5.2 -1.5 -4.8 -4.8 -1.0 5.8
-0.8 -1.4 0.1 -1.8 -6.0 -0.4 -0.5 -3.8 -3.0 -3.2 -4.6 -0.2 -3.2 -5.0 -2.0 2.0 6.8
-5.8 -3.8 -6.1 -6.0 -9.1 -8.2 -7.6 -6.3 -4.0 -3.3 -1.0 -5.4 -0.9 3.4 -7.4 -6.2 -9.3 15.2
-4.0 -2.1 -1.3 -3.8 -7.7 -5.1 -3.7 -5.4 -0.4 -2.5 -2.4 -3.7 -1.3 3.4 -7.0 -3.4 -2.7 2.3 10.5
-0.5 -4.9 -5.7 -5.2 -4.8 -3.6 -4.2 -5.6 -3.9 3.9 1.8 -3.7 0.7 -1.3 -5.2 -4.3 -1.9 -4.9 -1.8 7.0
//
H JOND920103
D The 250 PAM PET91 matrix (Jones et al., 1992)
R LIT:1814076 PMID:1633570
A Jones, D.T., Taylor, W.R. and Thornton, J.M.
T The rapid generation of mutation data matrices from protein sequences
J CABIOS 8, 275-282 (1992)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.
-1. 5.
0. 0. 3.
0. -1. 2. 5.
-1. -1. -1. -3. 11.
-1. 2. 0. 1. -3. 5.
-1. 0. 1. 4. -4. 2. 5.
1. 0. 0. 1. -1. -1. 0. 5.
-2. 2. 1. 0. 0. 2. 0. -2. 6.
0. -3. -2. -3. -2. -3. -3. -3. -3. 4.
-1. -3. -3. -4. -3. -2. -4. -4. -2. 2. 5.
-1. 4. 1. 0. -3. 2. 1. -1. 1. -3. -3. 5.
-1. -2. -2. -3. -2. -2. -3. -3. -2. 3. 3. -2. 6.
-3. -4. -3. -5. 0. -4. -5. -5. 0. 0. 2. -5. 0. 8.
1. -1. -1. -2. -2. 0. -2. -1. 0. -2. 0. -2. -2. -3. 6.
1. -1. 1. 0. 1. -1. -1. 1. -1. -1. -2. -1. -1. -2. 1. 2.
2. -1. 1. -1. -1. -1. -1. -1. -1. 1. -1. -1. 0. -2. 1. 1. 2.
-4. 0. -5. -5. 1. -3. -5. -2. -3. -4. -2. -3. -3. -1. -4. -3. -4. 15.
-3. -2. -1. -2. 2. -2. -4. -4. 4. -2. -1. -3. -2. 5. -3. -1. -3. 0. 9.
1. -3. -2. -2. -2. -3. -2. -2. -3. 4. 2. -3. 2. 0. -1. -1. 0. -3. -3. 4.
//
H JOND940101
D The 250 PAM transmembrane protein exchange matrix (Jones et al., 1994)
R LIT:2006072 PMID:8112466
A Jones, D.T., Taylor, W.R. and Thornton, J.M.
T A mutation data matrix for transmembrane proteins
J FEBS Lett. 339, 269-275 (1994)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.
-1. 7.
-1. 2. 11.
0. 1. 6. 12.
0. -1. -1. -3. 6.
-2. 6. 3. 2. -3. 11.
0. 2. 1. 8. -3. 7. 13.
1. 0. -2. 3. -1. -1. 3. 6.
-3. 5. 3. 3. -1. 7. 2. -3. 11.
0. -3. -3. -3. -1. -4. -4. -2. -4. 2.
-2. -3. -4. -5. -1. -2. -5. -4. -4. 1. 3.
-2. 9. 5. 3. -3. 6. 1. -1. 4. -4. -4. 12.
-1. 0. -2. -3. -1. -2. -3. -3. -3. 1. 1. -1. 3.
-2. -4. -4. -6. 1. -4. -6. -4. -3. -1. 1. -5. 0. 5.
0. -3. -2. -2. -4. 0. -3. -2. -4. -3. -1. -4. -3. -4. 11.
2. -1. 2. 0. 1. -1. 0. 1. -2. -1. -2. -1. -2. -1. -1. 3.
1. -1. 1. 0. 0. -2. -1. 0. -2. 0. -1. -2. 0. -2. -1. 2. 3.
-4. 5. -3. -4. 1. 0. -3. -2. -1. -3. -2. 3. -2. -3. -6. -3. -4. 12.
-3. -1. -1. -2. 3. 0. -5. -5. 6. -4. -3. 1. -3. 2. -5. 0. -3. -2. 10.
0. -2. -3. -3. 0. -4. -2. -1. -4. 2. 0. -4. 1. -1. -3. -1. 0. -2. -4. 2.
//
H KOLA920101
D Conformational similarity weight matrix (Kolaskar-Kulkarni-Kale, 1992)
R LIT:1806109 PMID:1538389
A Kolaskar, A.S. and Kulkarni-Kale, U.
T Sequence alignment approach to pick up conformationally similar
protein fragments
J J. Mol. Biol. 223, 1053-1061 (1992)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
10.
6.6 10.
0. 0. 10.
0. 0. 9. 10.
0. 0. 0. 0. 10.
6.6 9. 0. 0. 0. 10.
9. 6.6 0. 0. 0. 6.6 10.
0. 0. 0. 0. 0. 0. 0. 10.
0. 5. 5. 6.6 9. 5. 0. 0. 10.
0. 0. 0. 0. 0. 0. 0. 0. 0. 10.
5. 6.6 0. 0. 0. 9. 5. 0. 0. 0. 10.
6.6 9. 0. 5. 0. 9. 9. 0. 0. 0. 9. 10.
5. 9. 0. 0. 0. 5. 0. 0. 0. 0. 6.6 5. 10.
0. 9. 0. 0. 5. 6.6 0. 0. 5. 0. 5. 5. 6.6 10.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 10.
0. 5. 6.6 6.6 9. 0. 0. 0. 9. 0. 0. 5. 0. 5. 0. 10.
0. 5. 0. 0. 6.6 5. 0. 0. 5. 0. 0. 5. 0. 5. 0. 6.6 10.
0. 6.6 0. 0. 5. 5. 0. 0. 5. 0. 5. 0. 6.6 9. 0. 5. 5. 10.
0. 5. 0. 0. 5. 5. 0. 0. 6.6 0. 0. 0. 0. 9. 0. 6.6 9. 5. 10.
0. 0. 0. 0. 0. 0. 0. 0. 0. 9. 0. 0. 0. 0. 0. 0. 0. 0. 0. 10.
//
H LEVJ860101
D The secondary structure similarity matrix (Levin et al., 1986)
R LIT:1210126 PMID:3743779
A Levin, J.M., Robson, B. and Garnier, J.
T An algorithm for secondary structure determination in proteins based on
sequence similarity
J FEBS Lett. 205, 303-308 (1986)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.
0. 2.
0. 0. 3.
0. 0. 1. 2.
0. 0. 0. 0. 2.
0. 0. 1. 0. 0. 2.
1. 0. 0. 1. 0. 1. 2.
0. 0. 0. 0. 0. 0. 0. 2.
0. 0. 0. 0. 0. 0. 0. 0. 2.
0. -1. -1. -1. 0. -1. -1. -1. -1. 2.
0. -1. -1. -1. 0. -1. -1. -1. -1. 0. 2.
0. 1. 1. 0. 0. 0. 0. 0. 0. -1. -1. 2.
0. -1. -1. -1. 0. -1. -1. -1. -1. 0. 2. -1. 2.
-1. -1. -1. -1. -1. -1. -1. -1. -1. 1. 0. -1. 0. 2.
-1. 0. 0. 0. 0. 0. -1. 0. 0. -1. -1. 0. -1. -1. 3.
1. 0. 0. 0. 0. 0. 0. 0. 0. -1. -1. 0. -1. -1. 0. 2.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. -1. 0. 0. 2.
-1. 0. -1. -1. -1. -1. -1. -1. -1. 0. 0. -1. 0. 0. -1. -1. -1. 2.
-1. -1. -1. -1. -1. -1. -1. -1. 0. 0. 0. -1. 0. 1. -1. -1. -1. 0. 2.
0. -1. -1. -1. 0. -1. -1. -1. -1. 1. 1. -1. 0. 0. -1. -1. 0. 0. 0. 2.
//
H LUTR910101
D Structure-based comparison table for outside other class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
11.
0. 32.
2. 2. 11.
1. -2. 4. 29.
-5. -6. -7. -13. 109.
2. 6. 3. 2. -10. 16.
3. 2. 2. 6. -12. 5. 15.
-5. -7. -4. -7. -15. -8. -6. 39.
-4. -1. 2. -5. -23. 2. -3. -13. 54.
1. -4. -3. -7. -13. -3. -3. -16. -10. 50.
1. -4. -4. -10. -1. -2. -4. -17. -6. 19. 45.
-1. 6. -1. -2. -16. 5. 3. -15. -8. -10. -11. 39.
1. 0. -1. -7. -3. 0. -4. -11. -3. 20. 24. -8. 40.
-13. -14. -11. -15. -12. -15. -18. -24. -6. 7. 11. -26. 13. 85.
1. -9. -8. -9. -28. -6. -3. -19. -12. -11. -10. -9. -11. -24. 55.
4. 1. 3. 2. -10. 2. 2. -6. -4. -5. -5. -1. -4. -14. -3. 17.
3. -1. 2. -2. -7. 1. 1. -12. -5. 0. -4. -3. -2. -13. -6. 4. 30.
-6. 3. -6. -10. -3. -13. -14. -12. -3. 1. 1. -19. 9. 10. -11. -7. -14. 124.
-6. -3. -4. -10. 3. -9. -10. -16. 2. -3. 2. -16. 4. 22. -17. -6. -9. 29. 64.
3. -3. -3. -7. -7. -2. -2. -12. -9. 24. 13. -9. 14. 0. -8. -4. -1. -1. -2. 39.
//
H LUTR910102
D Structure-based comparison table for inside other class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
12.
5. 9.
5. 5. 6.
6. 8. 8. 17.
1. -10. -11. -14. 93.
6. 6. 6. 8. -5. 7.
7. 8. 8. 12. -16. 9. 15.
5. -2. 5. 6. -36. 3. 8. 52.
-2. 5. 6. 5. -20. 4. -3. -14. 65.
-1. -4. -3. -6. -17. -4. -5. -20. -10. 31.
-10. -10. -10. -16. -35. -12. -14. -32. -18. 9. 37.
6. 10. 10. 13. -22. 10. 13. 2. 6. -5. -15. 31.
-6. -6. -8. -13. -17. -5. -12. -32. -5. 18. 13. -11. 61.
-24. -11. -19. -25. -36. -20. -30. -52. -10. -4. 2. -30. 2. 67.
-5. -12. -11. -7. -30. -7. -7. -11. -23. -28. -36. -5. -25. -28. 83.
9. 6. 8. 8. -11. 8. 9. 7. -1. -11. -25. 8. -18. -37. -9. 36.
8. 6. 6. 8. 1. 8. 10. 0. -5. -1. -18. 6. -9. -37. -14. 10. 35.
-20. 2. -6. -16. 0. -2. -18. -23. -21. -19. -18. -21. -20. 11. -47. -29. -29. 129.
-4. 3. 0. 0. -7. 0. -3. -16. 5. 0. -2. -1. 1. 21. -20. -6. -8. 44. 26.
0. -3. -3. -4. -12. -3. -4. -20. -6. 17. 8. -4. 12. -9. -20. -10. -2. -8. -2. 26.
//
H LUTR910103
D Structure-based comparison table for outside alpha class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
24.
-2. 18.
-1. 2. 16.
-2. 0. 4. 23.
2. 2. 1. -1. 9.
-1. 2. 2. 3. 2. 13.
-2. -1. 1. 6. -3. 3. 24.
1. 2. 4. 2. 4. 2. 1. 29.
-5. 0. 3. 1. 0. 2. -1. 0. 43.
-5. -3. -6. -9. 4. -4. -10. -5. -4. 41.
-18. -7. -12. -18. -3. -13. -16. -15. -12. 13. 54.
-10. 5. -2. -4. -4. -1. -4. -4. -6. -11. -21. 32.
-3. 0. -5. -7. 4. 0. -5. -5. -5. 17. 13. -7. 44.
-20. -18. -18. -18. 4. -13. -24. -21. -9. 10. 12. -30. 13. 99.
-2. -2. -2. 1. -1. 1. -1. 0. -7. -8. -24. -8. -10. -32. 67.
1. 2. 4. 3. 5. 2. 1. 5. 0. -4. -12. -3. -3. -18. 1. 17.
1. 2. 3. 1. 4. 2. 0. 3. 1. 3. -6. -3. 2. -16. -3. 4. 16.
-20. -8. -18. -12. 16. -3. -16. -21. 7. -14. -3. -31. -14. 36. -29. -19. -2. 170.
-21. -10. -10. -14. -7. -12. -21. -14. -1. -14. -13. -25. -19. 40. -17. -16. -15. 47. 105.
-5. -3. -6. -4. 5. -5. -6. -5. -8. 18. -1. -11. 7. -11. -6. -2. 3. -9. -18. 44.
//
H LUTR910104
D Structure-based comparison table for inside alpha class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
22.
-2. 38.
4. 5. 4.
-1. 5. 11. 71.
8. -1. 4. -13. 50.
2. 9. 4. 10. 0. 6.
4. 12. 5. 20. -2. 7. 12.
5. 0. 7. 0. 3. 5. 8. 53.
-30. 4. -3. 7. -30. 13. -3. -32. 95.
-2. -1. 0. -13. 3. 0. -2. -6. -17. 17.
-14. -3. -6. -20. -11. -7. -10. -21. -10. 0. 25.
1. 22. 6. 9. -2. 9. 14. 2. -9. -1. -8. 33.
-2. 2. 0. -11. 0. -1. -3. -6. -8. 3. 2. -3. 17.
-18. -14. -15. -26. -12. -14. -21. -25. -7. -4. -4. -23. 1. 58.
5. 2. 2. 5. 2. 2. 4. 6. -14. 1. -7. 3. -1. -8. 4.
9. 4. 4. 3. 10. 4. 5. 7. -19. 1. -10. 5. 0. -14. 9. 23.
6. 3. 3. 1. 8. 3. 4. 4. -16. 2. -6. 5. 1. -13. 4. 9. 10.
-50. -35. -34. -55. -45. -15. -40. -57. -41. -27. -30. -23. -12. 4. -33. -45. -39. 130.
-15. -3. -4. -8. -8. 0. -8. -17. 23. -4. -5. -13. -2. 25. -3. -10. -9. 31. 68.
-1. -3. -1. -15. 1. -2. -3. -10. -27. 5. -6. -4. 3. -9. 0. -1. 2. -23. -14. 21.
//
H LUTR910105
D Structure-based comparison table for outside beta class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
27.
-3. 32.
-2. 0. 18.
-4. 0. 9. 38.
-22. -28. 6. -26. 156.
-3. 2. 1. 3. -29. 30.
-3. -1. 0. 10. -30. 6. 25.
9. 6. -4. 3. -33. 3. 4. 59.
-11. -7. 14. 12. -33. 4. -5. -4. 84.
-2. -2. -8. -10. -26. -7. -7. -8. -13. 29.
-7. -8. -11. -21. -34. -13. -13. -21. -9. 16. 42.
-6. 9. -1. -2. -32. 4. 2. -1. -19. -9. -14. 30.
2. 2. -3. -7. -17. -5. -5. -2. -11. 10. 12. -5. 7.
-4. -9. -8. -17. 12. -9. -12. -10. -3. 7. 6. -11. 2. 47.
6. -1. 5. -2. -22. 1. -10. -10. -9. 8. 3. -12. 6. 2. 56.
5. -4. 0. 0. 6. -6. -3. 0. -11. -10. -15. -4. -2. -9. -4. 25.
3. 2. -4. -1. -7. 2. 0. -1. -19. -3. -12. -1. 2. -8. -2. 4. 20.
-2. -31. -30. -40. -34. -34. -35. -33. -36. -25. -29. -14. -21. 32. -25. -13. -31. 150.
-10. -13. -2. -13. -25. -14. -13. -14. 18. -10. -1. -14. -4. 24. 3. -7. -16. 11. 56.
-2. -4. -9. -13. -11. -8. -8. -14. -19. 11. 8. -8. 7. -3. 1. -7. -1. -15. -13. 24.
//
H LUTR910106
D Structure-based comparison table for inside beta class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
18.
1. 60.
6. 10. 18.
4. -1. 18. 80.
0. -7. 5. 0. 66.
6. 24. 18. 18. 7. 42.
8. -1. 22. 29. -1. 15. 59.
14. -8. 6. -4. -10. 4. 13. 48.
2. 11. 13. 24. -2. 13. 16. -3. 18.
-8. -14. -14. -22. -29. -14. -18. -9. -15. 20.
-6. -12. -15. -27. -29. -9. -21. -9. -15. 11. 25.
4. 22. 16. 30. 2. 22. 10. -2. 14. -13. -11. 35.
1. 3. 3. 5. -23. 4. 5. 4. 3. 3. 2. 6. 35.
-12. -10. -6. -24. -40. -16. -7. -17. 6. -10. -4. -14. -2. 58.
4. -20. -13. -26. -8. -17. -19. -14. -15. -9. -3. -16. -16. -9. 95.
12. 3. 13. 17. -1. 10. 13. 16. 10. -12. -15. 11. -2. -16. -4. 28.
6. 10. 8. 2. -11. 4. 9. 8. 5. -7. -11. 7. 3. -17. -1. 12. 24.
-23. 16. -11. -24. -43. -14. -19. -32. 18. -8. -8. -11. -15. 3. -32. -21. -7. 115.
0. 7. 13. 7. -9. 9. 14. -9. 20. -16. -12. 11. 2. 16. -7. 3. 1. 15. 37.
-7. -11. -17. -30. -28. -15. -24. -9. -19. 11. 9. -12. -5. -13. -9. -14. -7. -15. -18. 21.
//
H LUTR910107
D Structure-based comparison table for other class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
11.
1. 28.
2. 3. 10.
2. 1. 5. 27.
-5. -9. -9. -15. 108.
3. 7. 4. 4. -11. 14.
3. 3. 3. 8. -15. 6. 15.
-4. -6. -2. -5. -21. -6. -4. 41.
-3. 0. 2. -3. -23. 2. -2. -12. 55.
-1. -6. -4. -9. -13. -4. -5. -18. -12. 49.
-3. -7. -7. -14. -10. -6. -8. -22. -10. 19. 48.
1. 7. 2. 1. -19. 6. 5. -12. -6. -11. -15. 38.
-1. -2. -3. -9. -7. -2. -7. -15. -4. 22. 24. -10. 52.
-16. -15. -14. -20. -19. -18. -22. -30. -9. 5. 10. -29. 11. 83.
0. -8. -7. -8. -30. -6. -3. -17. -12. -15. -16. -8. -15. -26. 58.
4. 2. 4. 3. -11. 3. 3. -4. -3. -8. -10. 1. -7. -19. -3. 19.
3. 0. 3. -1. -6. 2. 2. -10. -5. -1. -9. -2. -4. -19. -7. 5. 31.
-9. 2. -7. -13. -1. -13. -17. -15. -7. -5. -5. -21. 4. 10. -16. -11. -18. 129.
-5. -1. -2. -7. 0. -6. -9. -16. 3. -2. 0. -12. 3. 22. -16. -5. -9. 35. 59.
2. -4. -4. -7. -8. -3. -3. -14. -9. 24. 14. -9. 15. -2. -11. -6. -2. -3. -3. 37.
//
H LUTR910108
D Structure-based comparison table for alpha helix class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
23.
-1. 19.
1. 5. 13.
0. 3. 7. 28.
4. 1. 1. -4. 51.
1. 5. 5. 6. 1. 11.
0. 4. 5. 10. -5. 7. 23.
2. 3. 6. 4. 4. 3. 3. 37.
-6. 2. 5. 3. -5. 4. 1. -1. 52.
-6. -6. -7. -12. 5. -6. -10. -8. -9. 38.
-19. -10. -14. -21. -8. -14. -18. -19. -14. 7. 45.
-6. 9. 3. 2. -6. 4. 3. -1. -2. -12. -21. 34.
-4. -2. -5. -9. 3. -2. -7. -6. -7. 12. 8. -8. 40.
-23. -22. -22. -24. -4. -19. -28. -26. -13. 3. 4. -34. 8. 88.
1. 2. 3. 5. -2. 5. 6. 3. -4. -7. -21. -1. -8. -28. 59.
3. 4. 5. 5. 7. 4. 4. 6. 0. -5. -15. 1. -4. -21. 6. 17.
2. 2. 4. 2. 6. 3. 2. 4. 0. 1. -9. 0. 0. -19. 1. 5. 14.
-43. -29. -38. -35. -13. -19. -38. -46. -17. -25. -22. -43. -11. 19. -46. -41. -25. 162.
-19. -8. -7. -12. -8. -8. -16. -14. 4. -11. -12. -20. -12. 33. -10. -14. -13. 36. 97.
-6. -6. -8. -9. 3. -7. -8. -9. -14. 13. -4. -13. 6. -9. -7. -4. 1. -18. -19. 40.
//
H LUTR910109
D Structure-based comparison table for beta strand class (Luthy et al., 1991)
R LIT:1712085 PMID:1881879
A Luthy, R., McLachlan, A.D. and Eisenberg, D.
T Secondary structure-based profiles: Use of structure-conserving scoring
tables in searching protein sequence databases for structural similarities
J Proteins 10, 229-239 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
23.
-2. 40.
1. 4. 15.
-1. 2. 13. 49.
-5. -19. -5. -16. 97.
0. 9. 7. 9. -11. 31.
0. 2. 8. 17. -21. 11. 31.
12. 2. 0. 1. -18. 4. 6. 54.
-4. 2. 13. 17. -12. 8. 5. -5. 55.
-7. -9. -12. -17. -30. -13. -13. -11. -15. 28.
-7. -10. -13. -22. -34. -12. -14. -15. -13. 13. 34.
-3. 14. 7. 8. -23. 12. 10. 0. -1. -14. -13. 34.
1. 2. -2. -5. -28. -3. -3. 2. -3. 8. 8. -4. 25.
-9. -11. -9. -21. -31. -12. -13. -15. 3. -3. 1. -14. -1. 57.
5. -6. 2. -7. -12. -2. -13. -13. -10. -1. -1. -14. 0. -4. 78.
7. 1. 6. 8. -10. 2. 5. 8. 3. -13. -15. 4. -3. -14. -4. 26.
4. 6. 2. 2. -18. 4. 4. 3. -4. -7. -12. 4. 2. -13. -3. 8. 21.
-17. -5. -22. -32. -53. -26. -29. -33. 7. -12. -15. -15. -20. 16. -28. -19. -20. 133.
-5. -5. 4. -5. -19. -4. -3. -13. 21. -15. -7. -5. -3. 20. -1. -3. -8. 13. 47.
-5. -7. -12. -18. -27. -11. -12. -12. -18. 11. 8. -10. 2. -9. -4. -10. -4. -17. -15. 23.
//
H MCLA710101
D The similarity of pairs of amino acids (McLachlan, 1971)
R PMID:5167087
A McLachlan, A.D.
T Tests for comparing related amino-acid sequences
cytochrome c and cytochrome c551
J J. Mol. Biol. 61, 409-424 (1971)
* (RR 9.)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
8.
2. 8.
3. 3. 8.
3. 1. 5. 8.
1. 1. 1. 1. 9.
3. 5. 4. 4. 0. 8.
4. 3. 4. 5. 0. 5. 8.
3. 3. 3. 3. 1. 2. 3. 8.
3. 5. 4. 4. 3. 4. 2. 2. 8.
2. 1. 1. 0. 1. 0. 1. 1. 2. 8.
2. 2. 1. 1. 0. 3. 1. 1. 2. 5. 8.
3. 5. 4. 3. 0. 4. 4. 3. 4. 1. 2. 8.
3. 1. 2. 2. 3. 3. 1. 1. 3. 5. 6. 1. 8.
1. 1. 0. 1. 0. 0. 0. 0. 4. 3. 5. 0. 5. 9.
4. 3. 1. 3. 0. 3. 4. 3. 3. 1. 1. 3. 1. 1. 8.
4. 4. 5. 3. 2. 4. 4. 3. 3. 2. 2. 3. 2. 2. 3. 8.
3. 3. 3. 3. 2. 3. 4. 2. 4. 3. 3. 3. 3. 1. 3. 5. 8.
1. 3. 0. 0. 2. 2. 1. 1. 3. 3. 3. 1. 1. 6. 0. 3. 2. 9.
1. 2. 2. 1. 1. 1. 2. 0. 4. 3. 3. 1. 2. 6. 0. 3. 1. 6. 9.
3. 2. 1. 1. 1. 2. 2. 2. 2. 5. 5. 2. 4. 3. 2. 2. 3. 2. 3. 8.
//
H MCLA720101
D Chemical similarity scores (McLachlan, 1972)
R PMID:5023183
A McLachlan, A.D.
T Repeating sequences and gene duplication in proteins
J J. Mol. Biol. 64, 417-437 (1972)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5.
0. 6.
0. 0. 5.
0. 0. 3. 5.
0. 0. 0. 0. 6.
0. 0. 2. 1. 0. 5.
0. 0. 1. 2. 0. 3. 5.
3. 0. 0. 0. 0. 0. 0. 6.
0. 0. 1. 0. 0. 2. 0. 0. 6.
0. 0. 0. 0. 0. 0. 0. 0. 0. 5.
0. 0. 0. 0. 0. 0. 0. 0. 0. 3. 5.
0. 3. 0. 0. 0. 1. 0. 0. 0. 0. 0. 5.
0. 0. 0. 0. 0. 0. 0. 0. 0. 3. 3. 0. 6.
0. 0. 0. 0. 0. 0. 0. 0. 2. 1. 2. 0. 2. 6.
1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 5.
1. 0. 1. 0. 2. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 5.
1. 0. 1. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 3. 5.
0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 0. 1. 3. 0. 0. 0. 6.
0. 0. 0. 0. 0. 0. 0. 0. 2. 1. 1. 0. 1. 3. 0. 0. 0. 2. 6.
0. 0. 0. 0. 0. 0. 0. 0. 0. 2. 1. 0. 1. 1. 1. 0. 0. 0. 0. 5.
//
H MIYS930101
D Base-substitution-protein-stability matrix (Miyazawa-Jernigan, 1993)
R LIT:1913158 PMID:8506261
A Miyazawa, S. and Jernigan, R.L.
T A new substitution matrix for protein sequence searches based on
contact frequencies in protein structures
J Protein Engineering 6, 267-278 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.34
-0.08 0.65
-0.16 0.01 0.38
0.04 -0.06 0.20 0.36
-0.51 -0.35 -0.46 -0.41 1.02
-0.16 0.15 0.20 0.16 -0.74 0.48
0.03 -0.02 0.19 0.32 -0.64 0.25 0.36
0.19 0.20 -0.11 0.15 -0.18 -0.14 0.13 0.43
-0.21 0.11 0.21 0.18 -0.29 0.37 0.13 -0.19 0.54
-0.45 -0.82 -0.83 -0.78 -0.13 -0.95 -0.86 -0.58 -0.69 0.75
-0.45 -0.74 -0.90 -0.75 -0.02 -0.74 -0.80 -0.56 -0.50 0.48 0.61
-0.20 0.04 0.38 0.16 -0.81 0.30 0.25 -0.16 0.14 -1.01 -1.06 0.49
-0.47 -0.83 -0.97 -0.90 -0.29 -0.97 -0.87 -0.61 -0.86 0.67 0.50 -1.03 0.97
-0.47 -0.79 -0.71 -0.62 0.39 -0.85 -0.81 -0.52 -0.43 0.45 0.48 -1.03 0.35 0.61
0.17 0.14 -0.12 -0.15 -0.65 0.15 -0.13 -0.14 0.14 -0.78 -0.67 -0.14 -0.82 -0.76 0.56
0.16 0.05 -0.02 -0.14 -0.20 -0.20 -0.19 0.00 -0.15 -0.68 -0.70 -0.14 -0.75 -0.53 0.24 0.48
0.18 0.00 0.11 -0.10 -0.62 -0.07 -0.09 -0.09 -0.13 -0.59 -0.77 0.09 -0.61 -0.75 0.25 0.28 0.45
-0.51 -0.26 -0.79 -0.64 0.82 -0.83 -0.66 -0.15 -0.70 -0.23 0.13 -0.92 0.04 0.25 -0.71 -0.29 -0.70 1.42
-0.34 -0.31 0.12 0.09 0.40 -0.02 -0.11 -0.35 0.35 -0.35 -0.27 -0.12 -0.56 0.14 -0.20 -0.04 -0.27 0.00 0.84
-0.06 -0.54 -0.69 -0.39 -0.19 -0.68 -0.42 -0.15 -0.59 0.41 0.41 -0.79 0.41 0.36 -0.47 -0.44 -0.44 -0.17 -0.39 0.54
//
H MIYT790101
D Amino acid pair distance (Miyata et al., 1979)
R LIT:0601606 PMID:439147
A Miyata, T., Miyazawa, S. and Yasunaga, T.
T Two types of amino acid substitutions in protein evolution
J J. Mol. Evol. 12, 219-236 (1979)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.
2.92 0.
1.78 2.04 0.
2.37 2.34 0.65 0.
1.39 3.06 2.83 3.48 0.
1.92 1.13 0.99 1.47 2.48 0.
2.46 1.45 0.85 0.90 3.26 0.84 0.
0.91 3.58 1.96 2.37 2.22 2.48 2.78 0.
2.17 0.82 1.29 1.72 2.56 0.32 0.96 2.78 0.
2.69 2.49 3.37 3.98 1.63 2.57 3.39 3.60 2.45 0.
2.76 2.62 3.49 4.10 1.65 2.70 3.53 3.67 2.59 0.14 0.
2.96 0.40 1.84 2.05 3.27 1.06 1.14 3.54 0.79 2.84 2.98 0.
2.42 2.29 3.08 3.69 1.46 2.30 3.13 3.34 2.19 0.29 0.41 2.63 0.
3.23 2.47 3.70 4.27 2.24 2.81 3.59 4.14 2.63 0.61 0.63 2.85 0.82 0.
0.06 2.90 1.80 2.40 1.33 1.92 2.48 0.97 2.15 2.62 2.70 2.94 2.36 3.17 0.
0.51 2.74 1.31 1.87 1.84 1.65 2.06 0.85 1.94 2.95 3.04 2.71 2.67 3.45 0.56 0.
0.90 2.03 1.40 2.05 1.45 1.12 1.83 1.70 1.32 2.14 2.25 2.10 1.86 2.60 0.87 0.89 0.
4.23 2.72 4.39 4.88 3.34 3.42 4.08 5.13 3.16 1.72 1.73 3.11 1.89 1.11 4.17 4.38 3.50 0.
3.18 2.02 3.42 3.95 2.38 2.48 3.22 4.08 2.27 0.86 0.94 2.42 0.93 0.48 3.12 3.33 2.45 1.06 0.
1.85 2.43 2.76 3.40 0.86 2.13 2.97 2.76 2.11 0.85 0.91 2.70 0.62 1.43 1.79 2.15 1.42 2.51 1.52 0.
//
H MOHR870101
D EMPAR matrix (Mohana Rao, 1987)
R LIT:1304091 PMID:3570667
A Mohana Rao, J.K.
T New scoring matrix for amino acid residue exchanges based on residue
characteristic physical parameters
J Int. J. Peptide Protein Res. 29, 276-281 (1987)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
16.
8. 16.
9. 10. 16.
9. 10. 11. 16.
11. 8. 9. 8. 16.
11. 10. 11. 11. 10. 16.
10. 9. 10. 11. 9. 11. 16.
8. 7. 10. 9. 8. 8. 6. 16.
11. 10. 10. 9. 10. 11. 11. 7. 16.
9. 4. 5. 3. 8. 6. 4. 6. 8. 16.
11. 6. 7. 6. 11. 9. 7. 6. 10. 10. 16.
10. 11. 11. 11. 9. 12. 11. 7. 11. 4. 7. 16.
11. 6. 6. 5. 10. 9. 8. 4. 10. 9. 11. 8. 16.
10. 5. 6. 4. 10. 7. 6. 7. 9. 12. 11. 6. 10. 16.
6. 6. 9. 8. 7. 7. 5. 11. 5. 3. 4. 6. 2. 4. 16.
10. 9. 11. 10. 10. 10. 9. 11. 10. 8. 8. 10. 7. 8. 10. 16.
10. 9. 10. 9. 10. 10. 8. 10. 10. 10. 9. 9. 8. 10. 8. 11. 16.
11. 7. 8. 6. 11. 9. 7. 8. 10. 11. 11. 7. 10. 11. 6. 10. 11. 16.
9. 7. 8. 7. 10. 8. 6. 10. 9. 10. 9. 7. 8. 10. 8. 11. 11. 11. 16.
9. 5. 5. 3. 8. 6. 4. 6. 9. 12. 10. 5. 9. 11. 3. 8. 10. 11. 10. 16.
//
H NIEK910101
D Structure-derived correlation matrix 1 (Niefind-Schomburg, 1991)
R LIT:1713140 PMID:2051484
A Niefind, K. and Schomburg, D.
T Amino acid similarity coefficients for protein modeling and sequence
alignment derived from main-chain folding angles
J J. Mol. Biol. 219, 481-497 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.00
0.09 1.00
-0.29 -0.10 1.00
0.05 -0.08 0.30 1.00
-0.35 -0.17 0.04 -0.10 1.00
0.32 0.05 -0.14 0.11 -0.16 1.00
0.70 0.09 -0.24 0.07 -0.34 0.39 1.00
-0.40 -0.18 0.37 0.08 0.12 -0.28 -0.45 1.00
-0.18 0.15 0.04 -0.01 -0.04 0.08 -0.14 0.06 1.00
-0.25 0.05 -0.06 -0.28 -0.15 -0.13 -0.14 -0.23 0.01 1.00
0.51 0.00 -0.23 0.01 -0.27 0.29 0.57 -0.54 -0.09 0.25 1.00
0.55 0.14 -0.19 0.13 -0.25 0.16 0.50 -0.34 -0.23 -0.17 0.31 1.00
0.39 -0.10 -0.13 -0.09 -0.25 0.22 0.36 -0.29 -0.08 0.15 0.41 0.05 1.00
-0.18 0.15 -0.13 -0.31 -0.05 -0.25 -0.24 -0.05 0.17 0.27 -0.08 -0.16 -0.02 1.00
0.10 -0.18 -0.10 0.02 0.13 -0.18 -0.08 0.10 -0.32 -0.53 -0.25 0.04 -0.31 -0.28 1.00
-0.38 -0.10 0.04 0.02 0.31 -0.23 -0.41 0.28 -0.05 -0.34 -0.61 -0.18 -0.48 -0.13 0.35 1.00
-0.59 -0.12 0.01 -0.18 0.12 -0.21 -0.50 0.10 0.10 0.30 -0.31 -0.33 -0.31 0.19 -0.21 0.33 1.00
-0.11 0.00 -0.21 -0.19 0.00 -0.17 -0.12 -0.10 -0.01 0.03 -0.12 0.02 -0.19 0.15 -0.03 0.05 0.07 1.00
-0.59 -0.01 0.04 -0.19 0.25 -0.28 -0.57 0.19 0.13 0.13 -0.46 -0.43 -0.31 0.24 -0.13 0.34 0.46 0.06 1.00
-0.23 -0.03 -0.15 -0.22 -0.10 -0.03 -0.09 -0.24 -0.11 0.67 0.23 -0.13 0.08 0.13 -0.42 -0.25 0.35 -0.04 0.15 1.00
//
H NIEK910102
D Structure-derived correlation matrix 2 (Niefind-Schomburg, 1991)
R LIT:1713140 PMID:2051484
A Niefind, K. and Schomburg, D.
T Amino acid similarity coefficients for protein modeling and sequence
alignment derived from main-chain folding angles
J J. Mol. Biol. 219, 481-497 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.00
0.11 1.00
-0.31 -0.12 1.00
0.07 -0.08 0.35 1.00
-0.38 -0.20 0.04 -0.10 1.00
0.36 0.10 -0.16 0.13 -0.16 1.00
0.74 0.11 -0.27 0.09 -0.36 0.42 1.00
-0.41 -0.21 0.40 0.08 0.13 -0.32 -0.46 1.00
-0.20 0.19 0.04 0.00 -0.01 0.12 -0.14 0.09 1.00
-0.26 0.06 -0.07 -0.29 -0.16 -0.15 -0.13 -0.24 0.00 1.00
0.54 0.03 -0.24 0.01 -0.29 0.35 0.62 -0.56 -0.13 0.27 1.00
0.60 0.21 -0.22 0.14 -0.31 0.23 0.58 -0.38 -0.26 -0.18 0.36 1.00
0.43 -0.09 -0.13 -0.08 -0.29 0.22 0.38 -0.30 -0.06 0.18 0.47 0.09 1.00
-0.19 0.20 -0.12 -0.35 -0.07 -0.26 -0.27 -0.05 0.20 0.32 -0.08 -0.18 -0.01 1.00
0.11 -0.21 -0.10 0.01 0.14 -0.18 0.07 0.09 -0.34 -0.55 -0.26 0.04 -0.32 -0.31 1.00
-0.40 -0.13 0.06 0.03 0.35 -0.22 -0.43 0.28 -0.02 -0.37 -0.66 -0.21 -0.53 -0.13 0.35 1.00
-0.63 -0.12 0.01 -0.19 0.15 -0.22 -0.54 0.11 0.09 0.32 -0.36 -0.38 -0.35 0.21 -0.21 0.36 1.00
-0.11 0.03 -0.24 -0.22 -0.02 -0.18 -0.12 -0.11 -0.02 0.04 -0.15 0.02 -0.19 0.18 -0.02 0.07 0.12 1.00
-0.63 -0.01 0.05 -0.22 0.29 -0.32 -0.62 0.20 0.14 0.15 -0.48 -0.48 -0.33 0.29 -0.15 0.36 0.52 0.11 1.00
-0.25 -0.04 -0.16 -0.25 -0.10 -0.04 -0.09 -0.25 -0.13 0.72 0.25 -0.16 0.11 0.16 -0.44 -0.27 0.38 -0.02 0.17 1.00
//
H OVEJ920101
D STR matrix from structure-based alignments (Overington et al., 1992)
R LIT:1811128 PMID:1304904
A Overington, J., Donnelly, D., Johnson, M.S., Sali, A. and Blundell, T.L.
T Environment-specific amino acid substitution tables: tertiary templates
and prediction of protein folds
J Protein Science 1, 216-226 (1992)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
4.
-1. 7.
-1. -1. 5.
-1. -2. 2. 6.
-2. -2. -6. -7. 11.
0. 1. 0. 0. -3. 6.
0. 0. 0. 2. -3. 2. 5.
0. -2. -1. -1. -6. -2. -2. 5.
-2. 0. 2. 0. -6. 0. -2. -3. 8.
-2. -3. -3. -3. -4. -5. -3. -5. -5. 6.
-2. -3. -3. -6. -6. -3. -4. -5. -3. 2. 5.
-1. 2. 0. -1. -4. 1. 1. -3. 0. -3. -2. 5.
0. -4. -2. -4. -5. 1. -2. -4. -2. 1. 3. -1. 8.
-3. -4. -3. -5. -2. -4. -4. -6. -2. 1. 2. -3. 0. 7.
-1. -2. -2. -1. -8. -2. -1. -2. -3. -4. -3. -1. -6. -5. 7.
0. 0. 0. 0. -4. -1. -1. -1. -2. -3. -4. -1. -4. -3. -1. 4.
-1. -1. 0. -1. -5. 0. 0. -3. -2. -2. -3. 0. -2. -3. -1. 1. 5.
-3. -2. -5. -6. -6. -5. -6. -4. -3. -2. -1. -3. -2. 2. -4. -5. -5. 10.
-3. -1. -1. -3. -6. -3. -2. -3. 0. -1. -2. -2. -1. 3. -6. -2. -2. 2. 7.
0. -3. -4. -4. -4. -2. -2. -4. -2. 2. 1. -3. 0. -1. -4. -3. -1. -4. -1. 5.
//
H QU_C930101
D Cross-correlation coefficients of preference factors
main chain (Qu et al., 1993)
R LIT:1906100 PMID:8381879
A Qu, C., Lai, L., Xu, X. and Tang, Y.
T Phyletic relationships of protein structures based on spatial prefernce
of residues
J J. Mol. Evol. 36, 67-78 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.000
0.390 1.000
0.370 0.266 1.000
0.299 -0.109 0.037 1.000
0.270 0.273 0.105 0.035 1.000
0.261 -0.084 0.082 0.321 0.191 1.000
0.300 0.375 0.206 0.137 0.341 0.228 1.000
0.407 0.394 0.293 0.250 0.246 0.494 0.164 1.000
0.356 0.093 0.299 -0.117 0.527 0.630 0.121 0.497 1.000
0.476 0.305 0.452 0.242 -0.029 0.372 0.212 0.429 0.406 1.000
0.555 0.446 0.191 0.261 0.501 0.251 0.291 0.327 0.457 0.570 1.000
0.398 0.236 0.208 0.184 0.054 0.323 0.247 0.006 0.072 0.088 -0.080 1.000
0.207 0.374 0.438 -0.295 -0.006 0.211 0.128 0.326 0.461 0.440 0.112 0.285 1.000
0.628 0.552 0.278 0.475 0.550 0.364 0.433 0.455 0.405 0.532 0.769 0.217 0.111 1.000
0.183 -0.037 0.156 0.008 0.355 -0.168 -0.216 -0.023 0.304 0.065 0.079 0.099 0.266 0.091 1.000
0.193 -0.043 -0.051 0.012 -0.178 0.404 -0.081 0.015 0.144 0.166 -0.042 0.102 0.165 -0.012 -0.363 1.000
-0.083 0.037 0.076 0.328 0.087 0.344 0.220 0.335 0.259 0.385 0.386 -0.206 -0.141 0.306 -0.336 -0.124 1.000
0.081 -0.059 0.277 0.578 0.174 0.515 0.149 0.136 0.232 0.357 0.268 0.436 -0.075 0.451 -0.118 -0.023 0.564 1.000
0.683 0.201 0.387 0.320 0.195 0.207 0.273 0.372 0.083 0.333 0.246 0.436 -0.057 0.428 -0.054 -0.093 0.000 0.293 1.000
0.565 0.531 0.512 0.149 0.427 0.334 0.444 0.639 0.534 0.641 0.598 0.249 0.278 0.626 0.020 -0.103 0.329 0.378 0.614 1.000
//
H QU_C930102
D Cross-correlation coefficients of preference factors
side chain (Qu et al., 1993)
R LIT:1906100 PMID:8381879
A Qu, C., Lai, L., Xu, X. and Tang, Y.
T Phyletic relationships of protein structures based on spatial prefernce
of residues
J J. Mol. Evol. 36, 67-78 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.000
0.250 1.000
0.138 0.558 1.000
-0.018 -0.054 0.452 1.000
0.799 0.113 0.032 0.015 1.000
0.550 0.243 0.222 0.257 0.418 1.000
-0.116 0.037 0.408 0.851 -0.167 0.254 1.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.523 0.392 0.305 0.067 0.425 0.614 -0.102 0.000 1.000
0.888 0.108 -0.101 -0.185 0.717 0.511 -0.135 0.000 0.378 1.000
0.862 0.049 -0.172 -0.249 0.787 0.439 -0.223 0.000 0.289 0.960 1.000
0.281 0.872 0.490 -0.064 0.002 0.377 -0.051 0.000 0.488 0.099 -0.004 1.000
0.858 0.058 -0.090 -0.109 0.912 0.450 -0.180 0.000 0.441 0.842 0.881 -0.044 1.000
0.874 0.108 -0.072 -0.107 0.857 0.482 -0.187 0.000 0.511 0.893 0.927 0.061 0.903 1.000
0.656 0.133 0.265 0.276 0.558 0.598 0.097 0.000 0.651 0.572 0.504 0.206 0.523 0.661 1.000
0.281 0.804 0.661 0.245 0.104 0.357 0.204 0.000 0.568 0.083 0.003 0.745 0.054 0.152 0.200 1.000
0.574 0.427 0.519 0.382 0.326 0.610 0.287 0.000 0.399 0.382 0.346 0.540 0.313 0.410 0.435 0.601 1.000
0.825 0.169 0.003 -0.079 0.779 0.478 -0.216 0.000 0.460 0.792 0.843 0.111 0.785 0.907 0.597 0.204 0.471 1.000
0.772 0.266 0.338 0.225 0.817 0.550 0.036 0.000 0.492 0.573 0.625 0.182 0.764 0.743 0.632 0.307 0.540 0.802 1.000
0.850 0.045 -0.203 -0.196 0.755 0.458 -0.186 0.000 0.284 0.946 0.973 0.024 0.874 0.909 0.462 0.005 0.396 0.835 0.632 1.000
//
H QU_C930103
D The mutant distance based on spatial preference factor (Qu et al., 1993)
R LIT:1906100 PMID:8381879
A Qu, C., Lai, L., Xu, X. and Tang, Y.
T Phyletic relationships of protein structures based on spatial prefernce
of residues
J J. Mol. Evol. 36, 67-78 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
8.
2. 8.
1. 2. 8.
0. -1. 3. 8.
5. 0. 0. 0. 8.
2. 0. 1. 2. 3. 8.
0. 0. 3. 4. 0. 2. 8.
2. 2. 2. 0. 1. 2. -1. 8.
4. 2. 2. 0. 4. 4. 0. 0. 8.
5. 0. 0. 0. 4. 2. 0. 0. 3. 8.
5. 0. 0. 0. 5. 3. 0. 1. 2. 6. 8.
2. 6. 2. 0. 0. 1. 1. -1. 3. 1. 0. 8.
5. 0. 0. 0. 5. 2. 0. 2. 3. 5. 6. 0. 8.
5. 0. 1. 0. 6. 3. 0. 0. 4. 5. 6. 1. 5. 8.
3. 1. 3. 1. 4. 2. 0. 0. 4. 3. 2. 1. 3. 3. 8.
2. 3. 3. 2. 1. 2. 2. 1. 3. 0. 0. 3. 0. 0. 1. 8.
3. 2. 3. 4. 1. 3. 3. 1. 2. 1. 1. 3. 1. 2. 2. 4. 8.
4. 0. 0. 0. 5. 2. 0. -1. 3. 4. 4. 1. 4. 6. 3. 1. 2. 8.
4. 0. 2. 1. 4. 2. 1. 0. 3. 4. 4. 1. 4. 4. 3. 2. 3. 5. 8.
5. 0. 0. 0. 5. 3. 0. 2. 2. 6. 6. 0. 6. 5. 2. 0. 2. 5. 5. 8.
//
H RISJ880101
D Scoring matrix (Risler et al., 1988)
R LIT:1505154 PMID:3221397
A Risler, J.L., Delorme, M.O., Delacroix, H. and Henaut, A.
T Amino acid substitutions in structurally related proteins
A pattern recognition approach
Determination of a new and efficient scoring matrix
J J. Mol. Biol. 204, 1019-1029 (1988)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.2
1.5 2.2
1.3 1.2 2.2
0.2 -0.1 0.8 2.2
-1.5 -1.5 -1.6 -1.7 2.2
1.8 2.0 1.6 0.6 -1.4 2.2
1.7 1.9 1.4 1.0 -1.5 2.1 2.2
0.6 0.1 0.2 -0.4 -1.7 0.2 0.3 2.2
-0.6 -0.4 -0.3 -1.3 -1.8 -0.5 -0.6 -1.2 2.2
1.7 1.4 0.9 0.0 -1.6 1.4 1.5 0.0 -0.8 2.2
1.3 1.2 0.8 -0.2 -1.5 1.1 0.9 -0.2 -0.9 2.1 2.2
1.4 2.1 1.0 0.1 -1.6 1.7 1.4 -0.1 -1.0 1.0 0.7 2.2
1.0 1.1 0.0 -0.5 -1.6 1.2 0.6 -0.4 -1.2 0.9 1.8 0.4 2.2
0.6 0.4 0.4 -0.3 -1.6 0.7 0.6 -0.4 -1.1 1.0 1.0 0.1 -0.2 2.2
-0.2 -0.3 -1.0 -1.2 -1.8 -0.6 -0.1 -1.2 -1.6 -0.6 -0.8 -0.7 -1.2 -1.1 2.2
2.0 2.0 1.9 0.7 -1.3 1.8 1.8 0.7 -0.4 1.6 1.3 1.4 0.6 0.5 -0.3 2.2
1.9 1.9 1.1 0.0 -1.4 1.7 1.6 0.2 -0.9 1.6 1.2 1.2 0.8 0.3 -0.5 2.1 2.2
-0.9 -0.8 -1.1 -1.4 -1.8 -1.0 -1.0 -1.3 -1.7 -0.7 -0.8 -1.1 -1.3 -0.9 -1.6 -0.8 -1.0 2.2
0.2 0.8 -0.1 -0.4 -1.1 0.5 0.2 -0.2 -0.8 0.4 0.5 0.5 -0.2 2.0 -1.2 0.4 0.3 -0.6 2.2
2.0 1.5 1.1 0.0 -1.4 1.5 1.6 0.1 -0.7 2.2 2.0 1.2 0.8 0.8 -0.6 1.8 1.6 -0.7 0.3 2.2
//
H TUDE900101
D isomorphicity of replacements (Tudos et al., 1990)
R LIT:1616619 PMID:2279846
A Tudos, E., Cserzo, M. and Simon, I.
T Predicting isomorphic residue replacements for protein design
J Int. J. Peptide Protein Res. 36, 236-239 (1990)
* Diagonal elements are missing.
* We use 100 as diagonal elements.
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
100.
-2. 100.
-8. 11. 100.
3. 2. 32. 100.
4. -12. -7. -20. 100.
0. 26. 12. 8. -8. 100.
12. 11. 13. 34. -18. 37. 100.
-3. -6. 10. 8. -1. -10. -5. 100.
-10. 0. 8. 10. 3. -4. -8. -8. 100.
-17. -25. -32. -39. 12. -20. -36. -21. 3. 100.
-6. -24. -35. -40. 15. -26. -40. -16. -9. 46. 100.
2. 24. 17. 10. -14. 26. 24. -11. -4. -17. -33. 100.
-2. 0. -12. -16. 2. -12. -17. -10. -8. 18. 24. -19. 100.
-8. -11. -23. -31. 11. -22. -40. -12. -10. 32. 36. -26. 20. 100.
-2. -4. 8. 1. -3. 0. -7. 4. -2. -18. -16. -2. -10. -2. 100.
10. -10. 1. 7. -6. -7. -10. 9. -3. -17. -11. -10. -10. 0. 15. 100.
-3. -5. 12. 11. -4. -10. -12. -13. -7. -5. -11. -8. -8. 4. 2. 24. 100.
-12. -7. -6. -20. 8. -3. -10. -13. -6. 12. 8. -10. 12. 8. -9. -18. -8. 100.
-18. 0. -13. -22. 5. -23. -28. -18. 12. 29. 16. -21. 8. 24. -9. -16. -2. 6. 100.
-12. -18. -30. -32. 8. -12. -20. -14. -10. 46. 26. -14. 10. 16. -18. -16. -4. 14. 17. 100.
//
H AZAE970101
D The single residue substitution matrix from interchanges of
spatially neighbouring residues (Azarya-Sprinzak et al., 1997)
R PMID:9488136
A Azarya-Sprinzak, E., Naor, D., Wolfson, H.J. and Nussinov, R.
T Interchanges of spatially neighbouring residues in structurally conserved
environments.
J Protein Engineering 10, 1109-1122 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
14
1 16
1 10 15
0 13 16 26
5 -9 -4 -8 18
0 16 13 16 -10 21
2 13 10 15 -8 17 11
5 0 8 7 1 0 1 24
-2 4 5 8 -2 6 4 6 7
-6 -11 -11 -14 2 -12 -11 -10 -4 10
-2 -8 -9 -11 1 -9 -8 -9 -5 8 9
1 21 12 16 -11 22 17 -1 3 -13 -10 28
2 -1 -3 -7 0 -2 1 -3 -1 2 5 -4 2
-4 -8 -9 -10 2 -10 -7 -4 -1 6 5 -11 2 8
2 2 11 11 0 1 5 13 4 -14 -12 5 -10 -6 51
1 6 7 8 -1 6 6 8 3 -8 -7 6 -5 -5 6 9
-2 5 4 4 -5 6 3 1 4 -4 -6 7 -4 -4 5 5 10
-2 -3 -5 -5 -1 -3 -6 -1 3 4 2 -8 2 5 -5 -4 -2 8
-2 -1 -3 -4 -1 -3 -1 -2 0 2 0 -3 1 3 -5 -1 0 2 4
-5 -11 -11 -13 3 -12 -12 -8 -4 9 5 -14 0 5 -7 -6 -3 4 2 11
//
H AZAE970102
D The substitution matrix derived from spatially conserved motifs
(Azarya-Sprinzak et al., 1997)
R PMID:9488136
A Azarya-Sprinzak, E., Naor, D., Wolfson, H.J. and Nussinov, R.
T Interchanges of spatially neighbouring residues in structurally conserved
environments.
J Protein Engineering 10, 1109-1122 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
8
1 11
0 7 11
0 9 12 16
2 -7 -5 -8 14
1 12 10 13 -9 17
1 10 8 10 -6 13 8
1 0 7 8 0 0 0 18
-2 2 2 4 -1 2 1 5 5
-3 -10 -11 -12 4 -12 -10 -8 -3 11
0 -7 -9 -10 2 -9 -7 -8 -4 8 10
1 14 10 11 -10 16 13 0 2 -12 -9 20
1 -2 -4 -6 1 -3 0 -5 -2 3 6 -5 4
-2 -8 -9 -9 3 -10 -7 -3 -1 7 6 -10 3 8
-1 1 8 7 -2 0 0 10 3 -9 -9 1 -9 -5 33
0 4 6 6 -2 4 3 6 2 -7 -6 4 -5 -5 5 7
-2 2 2 3 -3 2 1 1 3 -2 -4 2 -3 -3 3 4 6
-1 -4 -4 -4 0 -5 -5 -1 -1 4 3 -7 2 4 -4 -3 -1 6
-1 -3 -4 -5 0 -4 -1 -1 0 3 2 -4 2 3 -4 -1 0 2 3
-4 -10 -11 -12 5 -12 -11 -7 -3 11 6 -13 1 7 -5 -5 -1 4 2 12
//
H RIER950101
D Hydrophobicity scoring matrix (Riek et al., 1995)
R PMID:7715195
A Riek, R.P., Handschumacher, M.D., Sung, S.S., Tan, M., Glynias, M.J.,
Schluchter, M.D., Novotny, J. and Graham, R.M.
T Evolutionary conservation of both the hydrophilic and hydrophobic nature of
transmembrane residues.
J J. Theor. Biol. 172, 245-258 (1995)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
100
13 100
60 53 100
33 81 73 100
98 11 58 30 100
64 49 96 68 62 100
39 74 79 94 36 74 100
96 17 64 36 94 68 43 100
71 42 89 61 69 93 68 75 100
91 4 51 23 93 55 29 87 62 100
93 6 52 25 95 57 31 89 64 98 100
35 78 75 98 33 71 96 39 64 26 27 100
89 2 49 21 91 53 27 85 60 98 96 24 100
87 0 47 19 89 51 26 83 58 96 94 22 98 100
89 24 71 44 86 76 50 93 83 79 81 46 78 76 100
94 19 66 39 91 71 45 98 78 84 86 41 83 81 95 100
98 16 63 35 95 67 41 99 74 88 90 38 86 84 91 96 100
98 11 58 31 99 63 37 94 69 93 94 33 91 89 87 92 96 100
94 19 66 38 92 70 44 98 77 85 87 41 83 81 94 99 97 93 100
94 7 54 26 96 58 33 90 65 97 99 29 95 93 83 88 91 96 88 100
//
H WEIL970101
D WAC matrix constructed from amino acid comparative profiles (Wei et al., 1997)
R PMID:9390315
A Wei, L., Altman, R.B. and Chang, J.T.
T Using the radial distributions of physical features to compare amino
acid environments and align amino acid sequences.
J Pac. Symp. Biocomput. 1997 5, 465-476 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
4
-1 4
0 0 4
-2 -1 0 4
0 -1 0 -2 4
0 0 1 -1 0 4
-3 -1 0 0 -2 0 4
-1 -1 0 -2 0 0 -2 4
0 0 0 -1 0 0 -1 -1 4
0 -2 -1 -4 0 0 -4 -2 -1 4
0 -1 -1 -3 0 0 -3 -1 -1 1 4
-1 2 0 -1 -2 0 -1 -1 0 -2 -2 4
1 0 0 -1 1 1 -1 0 0 2 2 0 4
0 -2 -1 -4 0 0 -4 -2 0 0 1 -2 2 4
0 0 0 -1 -1 0 -1 0 0 0 0 0 1 0 4
0 -1 1 -1 0 0 -2 0 -1 -1 -1 0 0 -2 0 4
0 0 1 -1 0 1 -1 0 -1 0 0 0 0 -2 0 1 4
0 0 -1 -3 0 0 -2 -2 0 0 1 -2 2 2 0 -1 -1 4
0 -1 0 -3 0 1 -4 -2 0 0 0 -2 0 1 -1 -1 -1 1 4
1 -2 -1 -3 0 -1 -4 -2 -1 2 1 -3 1 0 0 -1 0 0 0 4
//
H WEIL970102
D Difference matrix obtained by subtracting the BLOSUM62 from the WAC
matrix (Wei et al., 1997)
R PMID:9390315
A Wei, L., Altman, R.B. and Chang, J.T.
T Using the radial distributions of physical features to compare amino
acid environments and align amino acid sequences.
J Pac. Symp. Biocomput. 1997 5, 465-476 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0
0 -1
2 0 -2
0 1 -1 -2
0 2 3 1 -5
1 -1 1 -1 3 -1
-2 -1 0 -2 2 -2 -1
-1 1 0 -1 3 2 0 -2
2 0 -1 0 3 0 -1 1 -4
1 1 2 -1 1 3 -1 2 2 0
1 1 2 1 1 2 0 3 2 -1 0
0 0 0 0 1 -1 -2 1 1 1 0 -1
2 1 2 2 2 1 1 3 2 1 0 1 -1
2 1 2 -1 2 3 -1 1 1 0 1 1 2 -2
1 2 2 0 2 1 0 2 2 3 3 1 3 4 -3
-1 0 0 -1 1 0 -2 0 0 1 1 0 1 0 1 0
0 1 1 0 1 2 0 2 1 1 1 1 1 0 1 0 -1
3 3 3 1 2 2 1 0 2 3 3 1 3 -1 4 2 1 -7
2 1 2 0 2 2 -2 1 -2 1 1 0 1 0 2 1 1 -1 -3
1 1 2 0 1 1 -2 1 2 -1 0 -1 0 1 2 1 0 3 1 0
//
H MEHP950101
D (Mehta et al., 1995)
R LIT:2213135 PMID:8580842
A Mehta, P.K., Heringa, J. and Argos, P.
T A simple and fast approach to prediction of protein secondary structure from
multiply aligned sequences with accuracy above 70%
J Protein Science 4, 2517-2525 (1995)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.23
1.17 1.06
1.28 1.03 1.02
1.31 1.18 1.08 1.11
1.41 1.21 1.36 1.44 1.04
1.31 1.10 1.20 1.25 1.49 1.16
1.34 1.15 1.21 1.31 1.43 1.26 1.19
1.11 0.99 0.96 1.02 1.36 1.11 1.06 0.86
1.17 1.06 1.13 1.05 1.50 1.22 1.23 1.10 0.99
1.08 0.91 0.89 0.93 1.24 1.02 0.96 0.79 0.86 0.90
1.19 1.02 0.98 1.00 1.41 1.01 1.01 0.88 1.08 0.99 1.04
1.29 1.11 1.14 1.18 1.31 1.21 1.22 1.05 1.10 0.94 1.07 1.13
1.20 0.97 1.01 0.94 1.36 1.10 1.02 0.81 1.08 1.01 1.08 0.99 1.04
0.94 0.74 0.83 0.79 1.16 0.88 0.91 0.68 0.94 0.74 0.90 0.78 0.91 0.82
0.94 0.69 0.74 0.84 1.30 0.91 0.96 0.92 0.80 0.67 0.75 0.67 0.59 0.69 0.75
1.17 0.90 1.01 0.97 1.33 1.09 1.02 0.94 1.03 0.89 1.01 0.98 0.59 0.78 0.79 0.93
1.06 0.88 0.93 1.01 1.18 1.02 0.94 0.86 0.95 - 0.90 0.88 0.96 0.72 0.80 0.87 0.85
0.90 0.63 0.88 0.87 0.78 0.95 0.86 0.58 0.92 0.53 0.72 0.74 0.75 0.66 0.40 0.69 0.74 0.91
0.86 0.75 0.83 0.73 1.00 0.85 0.76 0.58 0.81 0.68 0.79 0.79 0.86 0.71 0.54 0.63 0.65 0.66 0.80
1.09 0.98 0.96 1.01 1.33 1.06 1.04 0.95 1.01 0.83 0.88 0.99 1.02 0.76 0.77 0.93 0.84 0.60 0.67 0.83
//
H MEHP950102
D (Mehta et al., 1995)
R LIT:2213135 PMID:8580842
A Mehta, P.K., Heringa, J. and Argos, P.
T A simple and fast approach to prediction of protein secondary structure from
multiply aligned sequences with accuracy above 70%
J Protein Science 4, 2517-2525 (1995)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.75
0.80 0.90
0.71 0.88 0.80
0.56 0.63 0.69 0.66
0.75 0.84 0.72 0.67 1.07
0.68 0.83 0.71 0.64 0.65 0.80
0.63 0.82 0.74 0.58 0.69 0.73 0.74
0.83 0.84 0.71 0.61 0.80 0.78 0.87 0.97
0.79 0.92 0.78 0.68 0.69 0.79 0.78 0.71 0.99
1.11 1.23 1.12 1.06 0.96 1.10 1.15 1.25 1.24 1.33
0.97 1.05 0.97 0.96 0.84 1.07 1.12 1.09 1.07 1.21 1.12
0.65 0.84 0.72 0.64 0.79 0.75 0.78 0.76 0.82 1.11 0.99 0.78
0.97 1.14 0.92 0.93 0.97 0.97 0.96 1.18 0.96 1.16 1.06 1.03 1.05
1.16 1.26 1.11 1.17 1.04 1.07 1.17 1.30 1.05 1.54 1.27 1.11 1.21 1.33
0.77 1.03 0.91 0.75 0.67 0.83 0.75 0.75 0.83 1.30 1.21 0.92 1.34 1.07 0.82
0.80 0.99 0.84 0.77 0.81 0.85 0.92 0.91 0.85 1.24 1.09 0.89 1.15 1.28 0.87 0.96
0.97 1.08 0.99 0.88 0.93 1.02 1.11 1.03 0.91 1.27 1.18 1.09 1.11 1.32 0.93 1.10 1.16
1.18 1.33 0.95 1.04 1.47 1.17 1.33 1.28 1.18 1.71 1.37 1.11 1.35 1.31 1.09 1.34 1.42 1.22
1.23 1.25 1.08 1.12 1.22 1.11 1.31 1.27 1.23 1.51 1.41 1.18 1.23 1.34 1.29 1.41 1.46 1.29 1.31
1.05 1.08 1.05 0.99 0.91 1.03 1.08 1.09 1.13 1.42 1.35 1.06 1.22 1.51 1.13 1.21 1.27 1.63 1.60 1.41
//
H MEHP950103
D (Mehta et al., 1995)
R LIT:2213135 PMID:8580842
A Mehta, P.K., Heringa, J. and Argos, P.
T A simple and fast approach to prediction of protein secondary structure from
multiply aligned sequences with accuracy above 70%
J Protein Science 4, 2517-2525 (1995)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.86
1.02 1.06
0.95 1.19 1.36
1.23 1.41 1.52 1.43
0.49 0.82 0.70 0.60 0.71
0.92 1.13 1.13 1.17 0.51 0.96
0.96 1.02 1.04 1.17 0.57 0.96 1.01
1.11 1.41 1.80 1.88 0.51 1.22 1.15 1.50
1.04 1.02 1.18 1.63 0.39 0.92 0.91 1.40 1.05
0.51 0.69 1.00 1.04 0.43 0.70 0.74 0.98 0.81 0.58
0.57 0.82 1.13 1.09 0.28 0.80 0.69 1.10 0.62 - 0.61
1.06 1.08 1.30 1.38 0.68 1.02 0.93 1.43 1.15 0.91 0.84 1.10
0.53 0.74 1.17 1.34 0.10 0.79 1.02 1.07 0.88 0.59 0.63 0.97 0.77
0.79 1.09 1.19 1.17 0.46 1.16 0.85 1.16 1.05 0.42 0.63 1.33 0.74 0.83
1.69 1.76 1.91 2.04 0.96 1.63 1.71 1.80 1.96 1.18 1.19 2.08 1.28 1.66 2.13
1.04 1.29 1.35 1.63 0.55 1.12 1.13 1.37 1.29 0.74 0.74 1.32 0.79 0.94 1.87 1.29
0.92 1.13 1.23 1.27 0.68 0.89 0.89 1.30 1.33 0.79 0.84 1.12 0.83 0.97 1.71 1.11 1.08
0.86 1.22 1.46 1.24 0.47 0.73 0.61 1.46 0.78 0.56 0.88 1.44 0.83 1.19 2.39 1.01 0.69 0.78
0.84 1.10 1.27 1.46 0.48 1.14 0.91 1.51 0.97 0.65 0.57 1.13 0.84 0.99 1.54 1.03 0.85 1.22 0.83
0.65 0.86 0.99 0.99 0.32 0.77 0.71 0.90 0.66 0.45 0.49 0.89 0.44 0.44 1.32 0.70 0.78 0.57 0.48 0.63
//
H KAPO950101
D (Kapp et al., 1995)
R LIT:2124159 PMID:8535255
A Kapp, O.H., Moens, L., Vanfleteren, J., Trotman, C.N., Suzuki, T. and
Vinogradov, S.N.
T Alignment of 700 globin sequences: extent of amino acid substitution and its
correlation with variation in volume
J Protein Science 4, 2179-2190 (1995)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
23.40
16.80 29.50
17.10 17.10 27.40
18.20 18.20 21.40 25.90
21.50 14.40 14.70 14.00 31.90
17.20 19.60 18.60 22.20 13.80 96.50
18.10 18.70 20.00 22.80 12.20 20.40 26.50
19.90 16.10 18.10 18.70 15.00 16.30 19.30 26.80
11.50 13.70 18.90 17.20 13.50 21.20 15.70 12.20 30.80
17.20 14.30 14.80 13.70 20.90 15.80 14.90 14.70 12.40 24.70
13.60 12.20 11.70 12.50 15.50 13.30 11.40 11.50 9.07 21.00 24.80
17.10 21.90 17.70 18.20 9.83 22.00 19.20 15.60 15.50 14.20 12.10 26.40
16.20 15.50 13.70 15.50 19.80 17.80 15.20 15.00 11.40 20.90 22.40 15.40 25.90
11.90 10.10 11.40 9.04 13.50 11.50 9.24 9.84 10.70 18.40 20.60 9.68 20.20 27.10
17.70 15.70 14.60 19.40 5.43 18.00 19.10 17.00 11.70 9.35 7.28 16.80 11.60 3.14 32.20
20.40 17.50 20.90 19.10 17.70 17.60 17.70 20.20 13.80 14.60 12.20 16.60 14.70 9.65 17.90 25.40
18.10 20.60 20.20 19.00 16.20 17.40 18.80 18.20 14.80 17.50 14.30 17.60 16.90 12.80 14.90 19.50 26.10
10.10 9.94 7.74 9.08 9.56 16.60 15.30 7.20 0.00 10.40 14.70 7.79 18.50 19.30 9.85 9.70 17.20 33.80
15.30 13.80 20.10 14.90 17.30 14.60 12.70 13.70 19.40 17.60 17.90 14.70 20.00 22.60 6.99 14.40 17.70 19.50 29.20
16.70 14.40 14.80 15.10 21.40 15.20 15.10 14.50 12.90 22.20 18.90 13.50 19.10 17.20 11.10 15.10 17.90 11.60 16.50 25.00
//
H VOGG950101
D (Vogt et al., 1995)
R LIT:2114150 PMID:7602593
A Vogt G, Etzold T, Argos P
T An assessment of amino acid exchange matrices in aligning protein sequences:
the twilight zone revisited
J J. Mol. Biol. 249, 816-831 (1995)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
7.6
4.6 9.9
4.9 5.5 9.0
4.9 4.9 7.4 9.9
5.7 3.0 3.4 2.0 16.7
5.0 6.7 5.9 6.1 2.8 7.9
5.2 5.6 6.1 7.9 2.2 6.9 8.8
5.7 4.2 5.6 5.3 3.2 4.2 4.4 11.8
4.4 5.8 6.4 5.6 3.9 6.4 5.6 3.8 11.2
4.4 2.8 2.4 1.4 4.1 3.3 2.5 0.7 3.0 9.2
4.0 3.0 2.2 1.2 3.7 3.6 2.4 0.8 3.3 8.0 9.2
4.8 7.9 6.0 5.7 2.4 6.7 6.4 4.1 5.8 3.1 3.1 8.4
4.5 3.5 3.0 2.2 4.3 4.2 3.2 1.7 3.9 7.7 8.0 3.8 9.5
2.9 2.0 2.1 0.7 4.4 2.6 1.3 0.0 5.1 6.2 7.2 1.9 6.8 12.2
5.5 4.3 4.3 4.5 2.1 5.0 4.7 3.6 4.1 2.6 2.9 4.6 2.8 1.4 12.8
6.3 5.0 6.1 5.7 5.3 5.4 5.4 5.6 5.0 3.4 3.1 5.3 3.8 2.4 5.6 7.4
5.8 5.0 5.7 5.2 4.7 5.2 5.1 4.1 4.9 4.6 3.9 5.3 4.6 3.0 5.3 6.7 7.7
1.6 3.6 1.6 0.0 4.2 2.5 0.9 1.2 4.4 3.4 4.5 1.7 4.2 8.8 0.2 1.9 1.7 19.4
3.0 3.4 3.8 2.4 4.7 3.5 2.5 1.2 7.4 4.5 5.2 3.1 5.0 10.3 2.1 3.3 3.3 9.3 13.0
5.3 3.2 3.0 2.3 5.2 3.7 3.3 1.9 3.2 8.3 7.0 3.5 6.8 5.3 3.4 4.2 5.2 2.6 4.1 8.6
//
H KOSJ950101
D Context-dependent optimal substitution matrices for exposed helix
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
55.7 3.0 3.0 3.0 3.0 0.4 0.1 3.0 3.0 2.1 3.0 3.0 3.0 0.1 1.9 2.2 2.4 3.0 0.8 1.3 3.0
25.6 47.2 1.5 1.0 0.7 0.3 1.9 2.3 4.3 0.6 0.2 2.0 0.8 0.1 0.3 3.1 2.8 3.7 0.4 0.1 2.0
14.8 0.9 62.7 1.3 0.4 0.3 4.6 0.3 0.1 1.9 0.5 2.2 5.1 0.6 0.2 0.4 1.9 1.5 0.4 0.2 0.3
15.2 0.2 0.5 48.2 3.3 0.1 3.2 4.9 0.1 1.7 1.7 1.4 3.0 0.6 1.0 0.1 9.7 2.7 0.7 1.1 1.5
15.9 3.9 1.4 7.3 52.1 0.3 0.9 11.0 2.0 0.4 0.6 0.1 0.6 0.5 0.1 0.6 2.9 0.1 0.1 0.1 0.1
9.4 1.5 0.1 1.5 1.6 73.6 0.1 2.6 0.1 0.1 2.1 4.0 0.1 0.1 0.8 0.7 0.3 2.2 0.1 0.1 0.1
0.1 8.4 5.7 2.0 4.5 0.3 47.5 8.2 0.9 1.6 0.1 3.4 7.8 0.5 0.1 0.7 5.3 2.2 0.2 0.7 0.5
5.2 5.3 1.0 1.5 8.6 0.1 4.9 56.8 1.5 1.0 0.3 0.9 5.8 0.1 0.2 1.6 2.1 2.4 0.2 0.1 1.1
20.2 2.0 1.2 2.3 3.3 0.1 0.4 0.1 6 4.8 0.8 0.1 0.1 1.4 0.3 0.6 0.1 1.2 0.6 0.1 0.5
13.3 0.3 4.7 7.5 1.8 0.1 4.4 0.7 0.1 56.9 0.6 0.1 2.3 1.2 2.2 0.1 0.1 0.1 0.1 4.4 0.1
18.4 0.1 0.1 0.1 0.1 0.1 0.4 0.1 0.1 0.1 5 2.6 10.8 1.2 3.5 1.3 0.1 0.1 3.4 0.1 0.1
15.4 0.8 0.6 0.1 0.1 0.1 1.1 0.1 0.2 0.2 3.4 67.3 0.6 3.5 3.5 0.1 0.1 0.7 0.1 0.1 2.9
5.5 4.1 8.3 3.5 1.3 0.1 3.7 5.8 1.1 1.2 0.3 1.0 55.3 0.4 0.1 0.2 2.7 3.7 0.1 0.2 1.9
0.7 5.2 4.3 3.2 0.1 0.5 2.0 5.4 1.5 0.1 7.4 9.3 3.0 44.0 1.3 0.1 2.4 4.3 0.1 0.1 6.0
14.3 1.7 0.1 0.3 0.5 1.0 0.8 0.5 0.1 0.1 0.7 1.5 0.1 0.4 67.6 0.1 2.1 1.8 0.1 7.1 0.1
13.6 1.7 1.0 0.5 3.1 0.1 0.6 0.6 0.1 1.0 0.8 1.5 2.7 0.1 0.1 65.9 5.2 1.8 0.1 0.3 0.2
6.0 18.1 1.2 1.6 2.7 0.9 0.4 2.4 5.0 1.1 0.6 0.2 3.5 0.1 0.1 0.5 46.8 7.5 0.1 0.5 1.4
18.4 7.5 0.3 2.5 0.7 0.1 0.4 0.2 1.8 0.8 2.4 4.8 1.2 1.0 0.1 0.2 6.3 48.8 0.1 0.6 2.7
21.7 0.3 0.1 0.1 0.1 0.1 1.8 0.1 0.1 0.1 0.1 2.1 2.5 0.1 4.3 0.1 0.1 0.6 64.6 2.3 0.1
8.3 0.5 0.1 0.1 0.1 0.1 0.1 1.1 0.1 3.4 2.4 6.6 0.9 0.2 8.7 0.3 0.9 1.5 1.0 60.8 3.8
14.2 6.2 1.4 0.7 0.1 0.1 0.1 0.3 0.3 0.1 17.5 1.9 0.1 0.1 1.6 0.2 0.1 0.6 0.3 1.2 53.9
//
H KOSJ950102
D Context-dependent optimal substitution matrices for exposed beta
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
72.6 0.8 3.0 0.1 2.3 0.3 1.9 1.3 0.8 0.1 0.3 2.3 3.0 0.5 0.8 1.6 3.0 1.5 0.1 0.8 3.0
7.5 60.3 2.2 0.1 1.6 1.1 0.6 1.6 0.4 0.1 0.8 2.9 1.0 0.7 0.1 2.0 6.2 4.8 0.1 1.6 5.1
14.3 1.2 60.9 0.1 1.1 0.1 5.1 2.5 1.1 0.4 0.7 0.1 9.4 0.1 0.6 0.6 0.8 0.1 0.2 0.9 0.5
3.0 2.1 3.0 53.5 11.8 0.1 2.9 0.1 1.8 2.5 0.1 1.3 4.4 0.1 0.3 1.2 9.0 1.6 0.1 1.9 0.1
14.6 1.9 0.1 6.1 58.5 0.1 2.8 5.8 4.0 0.1 0.9 0.1 1.7 0.3 0.5 0.9 1.9 0.1 0.1 0.8 0.1
20.4 1.9 0.1 0.1 1.7 49.5 1.6 0.1 1.7 0.1 4.0 0.1 0.1 0.1 8.4 0.1 2.0 1.9 0.1 3.9 3.5
11.8 1.3 2.3 0.1 1.0 0.1 55.8 7.5 1.4 2.5 1.1 2.3 3.8 0.1 0.1 0.8 2.5 3.7 0.3 0.4 1.9
5.0 1.5 0.6 1.7 8.4 0.1 2.0 66.4 0.6 1.1 0.5 0.7 4.2 0.1 0.1 0.6 3.3 1.5 0.4 0.1 2.0
6.7 2.7 0.1 0.1 0.1 0.1 0.1 1.0 82.8 0.1 0.1 0.6 0.6 0.4 0.8 0.1 1.8 2.8 0.1 0.1 0.1
0.1 1.2 10.0 5.7 0.1 0.7 0.3 4.2 0.8 45.8 0.1 1.7 1.8 1.3 0.1 0.1 8.3 10.8 0.1 4.6 2.8
0.1 0.1 2.5 0.5 0.1 0.5 0.1 0.1 0.1 0.1 54.4 5.4 1.1 2.9 4.5 0.3 0.1 3.9 0.1 1.5 22.8
14.2 1.0 0.6 0.7 0.1 0.1 2.1 0.5 0.1 1.8 5.7 60.3 0.9 2.6 2.9 1.7 1.2 0.1 0.1 0.7 3.4
7.9 1.6 8.1 2.1 0.4 0.7 3.3 2.4 0.3 0.7 0.8 1.3 61.5 0.1 0.6 0.5 2.6 4.6 0.3 0.1 0.9
12.6 6.3 3.2 0.1 0.1 0.1 2.7 2.6 0.1 0.1 4.9 2.3 7.8 46.5 1.0 0.1 3.9 2.2 0.1 0.1 4.2
8.2 0.1 0.1 0.6 0.1 0.1 0.1 0.1 1.0 1.1 2.1 1.9 0.1 2.1 66.1 0.1 2.1 0.6 0.9 10.5 2.9
16.8 6.2 0.1 0.6 0.7 0.1 0.7 0.1 0.8 0.1 0.1 1.3 0.5 0.1 0.1 67.1 2.7 2.5 0.1 0.3 0.1
30.0 2.0 0.1 1.7 0.1 0.1 0.1 1.0 4.6 0.5 0.2 0.7 0.9 0.1 0.1 2.8 49.8 4.5 0.1 0.1 1.5
4.7 3.4 1.5 2.0 2.6 0.1 0.4 3.9 0.6 0.1 1.8 1.4 4.7 0.1 0.1 0.1 8.4 59.0 0.3 0.5 5.0
5.9 0.1 0.1 0.1 0.1 0.1 0.1 2.3 2.0 0.1 0.8 2.9 0.1 0.1 4.7 0.1 1.0 0.1 75.5 2.9 2.5
5.0 2.1 0.9 1.1 0.1 0.1 0.5 0.4 0.1 2.7 3.0 2.7 0.8 0.1 5.9 0.1 1.6 0.1 0.7 72.2 0.8
18.1 1.2 0.5 0.1 0.4 0.1 2.0 2.3 1.1 0.1 6.9 4.6 0.1 2.1 0.8 0.9 0.4 1.0 0.1 0.4 57.5
//
H KOSJ950103
D Context-dependent optimal substitution matrices for exposed turn
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
69.2 3.0 1.3 3.0 0.9 0.7 1.9 3.0 3.0 1.6 0.9 1.3 0.8 0.6 1.1 1.4 1.0 3.0 0.1 1.4 0.8
31.5 46.2 1.1 0.8 0.8 0.1 0.3 0.3 2.5 0.1 2.0 2.3 0.9 0.4 0.3 0.2 4.4 2.0 0.4 0.1 4.1
5.9 1.3 64.3 2.5 1.7 0.5 2.6 0.1 2.4 2.1 0.2 0.2 8.7 0.4 0.4 0.6 3.5 1.2 0.6 0.5 1.1
9.3 1.7 1.2 55.1 6.4 0.5 1.3 1.7 4.4 0.8 0.1 0.4 3.8 0.7 0.3 0.2 8.9 1.3 0.3 1.4 1.0
2.1 2.9 0.2 9.4 61.5 0.1 1.9 9.2 3.4 0.4 0.1 0.6 3.1 0.1 0.1 1.4 2.5 1.4 0.1 0.2 0.3
17.0 7.1 0.1 0.1 0.1 66.1 0.1 0.1 2.0 0.8 0.4 0.7 0.1 0.3 3.0 0.1 2.6 0.1 0.1 0.3 0.1
9.0 4.9 3.9 3.3 2.3 0.1 48.8 4.8 1.7 2.0 1.6 4.3 4.7 0.8 0.4 2.1 1.6 3.3 0.1 0.1 0.9
7.8 3.8 1.0 1.1 7.0 0.1 3.5 57.8 1.1 1.5 1.1 1.7 4.5 0.4 0.4 1.7 3.3 1.0 0.4 0.3 1.0
6.5 2.8 0.4 2.9 2.8 0.1 0.8 1.9 74.8 0.4 0.1 0.1 1.7 0.1 0.4 0.3 2.2 1.9 0.1 0.1 0.3
14.9 1.8 0.1 4.0 0.1 0.6 2.9 1.4 0.7 56.0 0.6 0.4 2.9 0.2 2.8 2.2 2.2 0.1 0.9 5.9 0.1
10.4 0.1 0.1 0.1 0.1 0.5 0.1 0.1 0.1 0.1 65.5 7.0 0.1 2.4 0.8 0.5 0.1 2.7 0.7 0.9 8.8
9.1 0.7 3.1 0.3 0.1 0.1 0.1 0.7 0.3 0.4 3.7 68.3 0.8 4.4 1.7 0.6 0.3 1.0 1.0 1.3 2.8
2.5 4.7 8.1 2.6 1.3 0.1 5.9 4.4 1.3 1.6 0.1 1.4 58.1 0.5 0.5 0.5 2.9 2.0 0.1 0.5 1.5
15.2 1.3 0.8 0.1 0.1 0.4 0.1 0.1 0.1 0.6 4.7 6.8 0.8 61.0 2.9 0.1 0.1 1.1 0.1 2.8 1.8
14.8 0.1 0.8 0.7 0.1 0.4 0.4 0.1 0.1 0.1 0.6 3.5 0.9 0.7 70.0 0.7 0.1 0.1 2.9 2.4 1.5
4.4 7.5 1.7 1.0 1.2 0.1 0.4 2.2 0.7 0.4 0.9 0.8 2.3 0.4 0.1 70.2 3.0 2.4 0.1 0.2 0.6
2.5 10.8 1.1 2.5 5.3 0.9 1.7 1.8 5.1 1.0 0.4 1.4 3.1 0.4 0.6 1.8 49.6 8.8 0.1 0.8 0.7
15.3 2.9 1.3 2.9 1.5 0.1 1.5 1.5 0.9 0.2 2.0 1.0 1.9 0.6 0.1 0.5 9.5 54.0 0.3 0.1 2.8
10.5 0.1 0.1 0.1 0.1 0.7 0.1 0.1 0.1 0.1 0.1 0.3 0.1 0.1 0.1 1.0 0.1 0.1 77.0 10.5 0.1
13.0 0.1 0.4 0.1 0.1 0.1 0.1 0.7 0.1 0.9 1.2 2.8 0.5 0.1 8.4 0.3 0.1 0.4 0.1 71.2 0.5
8.1 2.7 0.2 0.3 0.1 1.8 0.8 0.1 1.0 0.5 10.3 4.5 1.3 1.1 2.7 0.1 0.7 2.1 0.3 1.9 60.1
//
H KOSJ950104
D Context-dependent optimal substitution matrices for exposed coil
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
50.4 3.0 3.0 2.5 3.0 1.1 3.0 3.0 3.0 1.8 3.0 3.0 3.1 1.4 1.5 3.0 3.0 3.0 0.5 1.8 3.0
29.8 49.8 0.1 0.5 0.8 0.1 2.1 0.3 4.1 0.6 0.5 1.1 0.3 0.1 0.1 2.2 3.7 1.4 0.2 0.1 3.1
15.0 1.2 60.3 1.2 0.1 0.1 1.2 0.7 0.1 2.5 0.9 0.9 6.6 0.1 0.1 2.1 2.5 3.1 0.6 0.9 0.7
8.3 1.6 2.6 50.6 5.5 0.5 2.0 3.2 2.2 2.7 0.9 1.0 4.7 0.9 0.3 0.1 6.8 3.9 0.1 1.2 1.4
9.1 1.6 0.6 7.8 62.7 0.1 2.5 6.1 1.3 0.1 0.4 0.5 1.4 0.3 0.2 1.4 1.8 1.4 0.1 1.1 0.3
23.2 12.9 0.2 0.1 1.5 58.1 0.1 1.2 0.1 0.1 2.0 0.1 0.1 0.8 0.1 0.1 0.1 0.3 0.1 0.1 0.1
28.1 0.1 2.2 2.0 0.1 0.1 44.4 9.2 0.1 1.4 0.6 0.4 3.1 1.5 0.1 0.1 1.6 3.6 0.1 0.7 1.6
22.2 5.1 0.5 0.5 4.3 0.1 3.0 57.1 1.4 0.7 0.5 0.6 1.1 0.1 0.1 0.1 1.6 0.9 0.1 0.1 1.0
18.4 1.5 0.3 1.4 1.7 0.4 0.3 0.9 70.2 0.4 0.1 0.2 0.4 0.2 0.3 0.2 2.1 0.8 0.1 0.3 0.4
27.6 1.2 0.5 0.1 4.2 0.1 2.6 1.0 0.1 50.8 0.1 0.1 1.9 0.3 0.9 3.9 4.8 0.1 0.1 0.9 0.1
30.9 1.2 0.1 0.1 0.1 0.1 0.1 0.7 1.6 0.9 41.7 3.8 2.2 0.1 0.4 1.3 0.1 0.8 0.7 0.5 13.6
18.9 0.7 1.0 0.4 0.2 0.3 2.1 0.4 0.4 0.6 6.0 57.6 0.1 3.3 3.8 1.3 0.1 0.5 0.1 0.1 2.9
9.3 3.5 6.0 2.2 3.3 0.1 3.9 4.4 1.8 0.8 0.1 2.5 52.1 0.5 0.8 2.6 3.2 2.6 0.1 0.1 1.0
22.9 0.1 0.1 0.1 0.1 0.1 0.1 0.3 0.1 1.0 7.9 9.1 1.0 45.8 2.2 1.7 0.1 6.3 0.1 0.1 2.2
16.2 0.3 0.7 0.8 0.1 0.1 0.1 0.1 0.1 0.1 1.4 2.5 0.7 0.1 69.1 0.1 0.1 0.1 0.9 7.5 0.3
15.4 6.7 0.8 0.2 0.3 0.1 1.3 2.0 1.3 0.2 0.1 0.6 0.4 0.1 0.1 64.2 3.6 0.6 0.1 0.7 1.9
13.4 5.0 0.9 3.6 3.5 1.8 1.0 1.6 3.3 0.1 0.3 0.3 0.8 0.1 0.6 3.5 48.7 8.7 0.4 0.3 2.6
16.3 4.5 0.1 2.3 0.6 0.4 1.7 0.5 0.6 0.4 2.4 1.9 1.0 0.1 0.6 2.6 8.9 51.4 0.1 0.4 4.0
15.9 0.1 0.1 1.1 0.1 0.1 0.1 0.1 0.1 0.1 3.2 0.1 0.6 1.8 2.7 0.1 0.2 0.1 73.5 1.4 0.1
15.5 0.4 0.1 0.1 0.1 0.1 0.1 0.1 0.6 0.6 0.1 2.5 0.1 0.6 8.4 0.1 0.1 0.6 1.0 68.7 1.6
25.4 1.4 0.1 0.7 0.4 0.4 0.6 0.1 0.1 0.1 8.0 4.3 1.3 1.1 1.5 0.1 0.9 2.5 0.1 0.1 51.9
//
H KOSJ950105
D Context-dependent optimal substitution matrices for buried helix
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
61.0 3.0 1.8 4.0 1.7 3.0 2.3 0.5 3.0 0.1 3.0 3.6 0.5 3.0 1.7 0.9 1.9 3.0 0.5 0.8 0.6
1.3 76.5 0.6 0.1 0.2 0.4 0.7 1.8 2.5 0.1 0.6 1.7 0.8 0.5 0.4 0.7 6.6 1.6 0.1 0.8 2.8
2.6 1.3 79.9 0.6 0.1 0.3 3.1 1.3 0.1 1.2 0.1 0.9 4.6 0.1 0.4 0.5 2.6 0.9 0.1 0.3 0.1
7.6 3.2 0.1 70.8 3.8 0.6 0.1 2.5 1.4 0.1 0.9 0.1 1.0 0.1 0.1 0.5 3.2 3.5 0.1 1.4 0.1
3.1 2.9 0.4 1.2 78.5 0.1 0.1 5.6 0.1 0.1 0.4 0.6 2.0 0.1 0.3 1.1 2.3 0.9 0.1 0.8 0.1
7.9 7.5 0.9 0.1 1.4 56.1 1.5 0.7 4.2 0.1 2.3 0.8 0.1 1.8 1.1 0.1 4.4 2.1 0.9 0.1 6.6
4.3 2.9 1.7 2.6 2.8 0.1 74.3 1.5 0.3 3.4 0.1 0.1 3.2 0.9 0.1 0.5 0.5 1.1 0.5 0.1 0.1
2.4 1.4 0.1 0.2 1.5 0.2 4.4 80.7 1.3 0.1 1.1 2.8 2.5 0.1 0.1 0.1 0.7 0.1 0.1 0.6 0.6
2.3 7.0 0.8 1.3 0.5 0.2 1.3 1.8 80.3 0.3 0.1 0.3 0.7 0.1 0.1 0.1 1.6 1.1 0.1 0.1 0.9
0.1 0.9 1.9 1.0 0.4 0.1 2.9 1.0 0.1 85.0 0.1 0.1 2.2 0.6 1.6 0.5 0.9 1.1 0.1 0.1 0.6
1.9 1.1 0.7 0.3 0.2 0.1 0.1 0.2 0.5 0.1 75.2 7.3 0.3 2.3 1.3 0.1 0.5 1.8 0.2 0.4 6.3
1.0 0.7 0.2 0.5 0.1 0.4 0.6 0.2 0.1 0.4 5.5 78.6 0.7 3.0 3.3 0.1 0.6 0.2 0.1 0.6 3.7
1.5 0.1 5.3 3.4 0.1 0.1 0.9 2.8 0.8 0.1 0.1 4.2 73.1 2.3 0.1 0.1 1.1 1.5 0.1 1.4 2.0
2.9 2.6 0.1 0.5 0.1 0.4 1.1 0.1 0.6 0.1 5.6 11.9 0.1 65.8 2.6 0.1 0.1 2.7 0.9 0.1 2.9
1.2 0.4 0.1 0.1 0.3 0.1 0.1 0.2 0.2 0.4 0.5 6.5 0.1 0.5 78.0 0.3 0.3 0.5 2.9 7.1 1.0
3.1 0.1 0.1 0.8 0.1 0.1 1.1 1.2 0.8 1.0 0.7 0.1 0.2 0.1 0.1 85.9 1.8 1.9 0.1 0.1 1.8
2.2 4.9 1.0 2.7 0.1 2.1 1.8 0.1 2.7 0.1 0.6 0.6 0.1 0.6 0.8 0.3 73.5 5.8 0.1 0.1 0.6
4.3 4.1 1.6 0.1 0.3 0.4 0.4 0.9 0.7 0.1 0.1 2.2 1.0 0.5 0.5 1.1 5.2 72.1 0.1 0.1 5.0
1.0 0.3 0.4 0.1 1.1 0.1 0.1 0.1 0.1 0.1 0.1 1.2 1.7 0.1 0.1 0.4 0.7 0.1 91.3 1.2 1.2
0.9 1.4 0.8 0.8 0.1 0.6 0.2 0.6 0.1 2.3 0.5 4.3 0.7 1.4 8.2 0.1 0.6 0.3 0.4 76.6 0.1
0.3 7.2 0.6 0.2 0.4 0.8 0.4 0.5 0.1 0.4 13.4 5.9 0.1 2.2 0.6 0.1 0.1 3.1 0.1 0.1 64.2
//
H KOSJ950106
D Context-dependent optimal substitution matrices for buried beta
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
56.4 3.0 2.1 1.7 1.6 3.0 1.7 2.1 3.0 0.9 3.0 3.0 1.1 1.1 2.0 3.0 3.0 3.0 0.7 1.7 3.0
5.8 66.6 0.5 0.9 1.5 0.3 0.6 1.7 3.7 1.0 0.4 0.3 1.0 0.1 0.1 2.6 7.3 3.7 0.1 0.2 2.4
16.1 0.1 72.6 0.1 0.1 0.1 0.8 0.1 2.5 0.1 0.7 1.0 3.0 0.8 0.1 0.9 0.1 2.0 0.1 0.1 0.1
9.5 0.1 1.5 70.8 4.2 0.1 1.3 0.1 1.2 1.6 0.5 0.1 2.8 0.1 0.1 1.1 2.6 1.9 0.7 0.1 0.8
11.0 0.1 0.2 2.9 80.8 0.1 0.2 1.0 1.2 0.1 0.6 0.9 0.1 0.1 0.1 0.1 0.6 1.3 0.1 0.1 0.1
12.4 5.9 0.4 0.4 0.8 65.6 0.1 0.8 1.2 0.7 2.5 3.0 0.1 0.4 1.2 0.5 3.0 1.9 0.1 0.1 0.1
10.9 0.1 3.1 1.9 0.1 0.1 71.6 3.3 0.1 0.1 0.1 3.0 2.6 1.4 0.4 0.6 0.1 0.6 0.1 0.7 0.5
14.3 0.9 1.2 1.0 4.4 0.1 2.3 67.9 2.3 0.1 0.1 0.7 1.7 0.1 0.4 0.1 0.2 0.1 0.1 1.0 2.3
5.8 2.8 0.1 0.1 0.7 0.1 0.1 0.1 87.6 0.6 0.1 0.1 0.1 0.1 0.1 0.3 1.4 0.3 0.1 0.1 0.4
6.3 0.1 5.0 1.3 2.2 0.6 3.0 2.5 0.1 70.9 0.1 1.6 0.5 0.9 1.0 0.5 2.3 0.1 0.9 1.1 0.1
3.2 0.4 0.4 0.3 0.1 0.4 0.1 0.1 0.1 0.1 64.4 8.9 0.2 2.0 2.3 0.4 0.7 1.6 0.4 0.3 14.4
5.8 0.6 0.1 0.1 0.1 0.2 0.1 0.3 0.3 0.1 4.4 77.6 0.1 2.8 2.2 0.2 0.1 0.3 0.3 0.8 4.4
11.0 0.6 10.7 0.1 0.1 0.1 2.2 0.2 0.1 1.5 1.5 0.7 67.7 0.1 0.1 0.4 0.7 1.7 0.1 0.4 0.9
4.9 3.1 0.1 0.6 0.4 0.6 2.8 0.1 0.5 0.1 4.4 9.4 0.1 63.4 3.1 0.7 0.1 2.5 0.1 0.5 3.6
3.4 0.2 0.1 0.1 0.1 0.3 0.1 0.1 0.3 0.4 2.4 3.0 0.2 1.1 79.7 0.1 0.6 0.7 1.2 5.2 1.7
16.2 1.8 0.5 0.1 0.1 0.1 1.3 0.7 0.5 0.1 0.1 0.3 0.7 0.1 0.1 73.3 4.4 0.8 0.1 0.1 0.1
13.9 2.5 3.0 2.8 1.1 0.3 1.1 1.4 3.7 0.5 0.1 0.1 0.8 0.5 0.8 0.9 63.3 3.4 0.1 0.1 0.5
8.9 2.9 0.4 0.7 0.1 0.4 1.0 1.8 0.6 0.3 2.0 0.6 1.6 0.7 0.1 0.4 4.6 70.2 0.1 0.7 2.5
4.6 0.1 0.6 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.6 1.2 0.1 0.5 0.1 90.5 2.2 0.1
4.0 0.1 0.6 1.5 0.1 1.0 0.3 0.1 0.1 1.3 0.5 0.7 0.4 0.1 6.3 0.6 1.1 0.6 0.8 80.9 0.1
3.9 2.4 0.3 0.1 0.4 0.8 0.2 0.1 0.1 0.1 9.6 3.0 0.1 0.2 0.6 0.3 1.1 2.1 0.1 0.3 75.0
//
H KOSJ950107
D Context-dependent optimal substitution matrices for buried turn
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
86.4 1.4 0.7 0.4 1.5 0.5 0.6 0.1 2.5 0.1 0.1 0.5 0.2 0.2 0.8 0.6 0.5 0.7 0.1 0.5 1.7
2.6 65.6 0.8 2.3 0.7 0.1 0.5 2.0 7.6 1.3 1.2 2.7 0.1 0.4 0.1 3.2 0.8 4.5 0.1 0.1 4.4
4.1 1.7 81.2 1.2 0.1 0.6 2.8 0.6 0.1 0.8 0.7 0.1 3.6 0.1 0.1 0.6 0.1 1.1 0.1 0.6 0.7
1.5 1.0 1.9 79.8 5.0 0.1 0.6 0.2 3.5 2.1 0.1 1.1 1.1 0.1 0.3 0.1 2.2 0.1 0.1 0.1 0.2
5.2 0.1 0.4 3.1 78.1 0.1 0.1 4.0 1.7 1.5 0.1 1.3 0.1 0.4 0.1 0.7 1.9 0.5 0.1 0.9 0.8
3.3 9.5 0.1 0.1 4.0 73.0 0.1 2.3 2.9 0.1 0.1 0.1 0.1 0.1 1.5 0.7 1.9 0.1 0.1 0.1 1.2
3.9 0.1 2.9 0.1 0.1 0.1 70.3 4.6 2.7 4.6 0.9 0.1 4.7 1.8 0.1 3.3 0.1 0.1 0.7 0.1 0.1
0.1 2.2 0.1 1.4 9.3 0.1 3.8 71.2 0.3 0.1 0.1 0.1 3.4 0.1 0.1 3.0 1.2 3.2 0.1 0.1 1.5
2.2 1.6 0.3 0.3 0.7 0.1 0.1 0.3 91.5 0.1 0.1 0.3 1.0 0.1 0.1 0.1 1.6 0.1 0.1 0.1 0.1
0.7 1.0 0.1 0.1 0.1 0.1 0.1 1.2 0.1 85.1 0.1 0.1 0.9 1.7 2.6 2.8 1.2 1.2 0.1 1.9 0.1
0.7 0.1 0.1 1.2 0.1 0.1 0.2 0.5 0.1 0.1 76.1 7.3 0.4 4.0 1.2 0.1 0.1 1.9 0.1 0.1 6.9
0.8 1.6 1.0 0.1 0.4 0.4 2.4 0.6 0.5 0.9 5.8 75.9 0.5 3.1 2.9 0.1 0.1 0.4 0.1 0.4 3.0
0.1 1.0 5.8 5.9 1.1 0.1 2.6 0.1 1.7 0.1 0.1 0.1 76.7 1.1 0.1 0.1 0.6 3.9 0.1 0.1 0.1
0.1 0.1 1.0 0.6 0.1 0.2 0.1 1.7 0.1 0.1 2.4 8.3 0.8 78.9 3.0 0.1 0.1 0.1 0.1 0.1 3.5
1.7 0.3 0.1 0.5 0.1 0.1 0.1 0.1 0.1 0.8 0.7 2.7 0.3 1.1 81.2 0.1 1.2 0.1 1.3 6.7 2.1
1.5 1.7 0.3 0.9 0.1 0.1 0.5 0.1 0.6 0.1 0.6 1.4 0.1 0.1 0.1 90.7 1.8 0.3 0.1 0.1 0.1
1.4 14.2 1.8 1.7 4.3 1.1 1.5 1.0 0.1 0.9 0.9 0.8 1.7 0.1 0.1 0.1 67.3 0.8 0.1 1.0 0.1
1.6 1.1 0.1 2.6 0.4 1.3 0.1 0.1 1.1 0.1 0.9 0.1 0.7 1.5 0.3 2.6 11.7 72.3 0.1 0.1 2.3
2.1 0.1 0.1 0.1 0.1 0.7 0.1 0.1 0.6 0.1 0.9 0.3 0.1 1.3 1.8 0.1 1.2 0.7 88.7 1.5 0.7
2.0 0.5 0.1 1.6 0.1 0.4 0.8 0.7 0.1 4.9 0.3 1.3 0.4 0.1 6.5 0.1 0.1 1.1 0.1 79.7 0.1
4.0 5.1 0.1 1.1 0.5 0.1 1.1 0.1 0.1 0.1 7.0 6.2 0.1 0.1 1.7 1.4 0.8 3.2 0.3 0.8 67.2
//
H KOSJ950108
D Context-dependent optimal substitution matrices for buried coil
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
74.9 3.0 0.2 0.6 2.2 1.2 1.5 1.4 1.5 0.4 0.8 2.5 0.7 0.5 1.0 1.6 1.7 0.9 0.1 0.7 2.5
7.2 68.0 0.6 0.5 0.5 1.0 0.2 0.1 5.5 0.1 0.4 0.5 0.9 0.5 0.4 1.8 5.7 4.4 0.1 0.1 2.1
4.0 0.1 77.6 0.7 0.1 0.5 1.7 0.4 0.1 3.1 0.1 3.6 1.3 0.1 1.0 0.1 4.5 2.0 0.1 0.1 0.1
2.4 0.1 0.1 83.8 3.0 0.4 1.2 0.1 2.5 1.4 0.3 0.1 1.1 0.3 0.1 0.1 2.5 0.5 0.1 0.1 0.9
7.4 1.7 0.4 4.7 75.7 0.1 0.1 3.0 0.2 0.5 1.0 0.3 0.5 0.1 0.1 0.9 1.9 0.4 0.1 1.8 0.1
5.3 9.2 0.1 1.2 0.1 64.4 0.7 1.4 1.4 0.1 1.4 1.3 0.1 3.2 2.0 0.1 3.5 0.8 1.2 2.1 1.4
11.0 2.6 2.6 0.1 3.8 0.1 61.4 2.8 1.9 0.1 0.1 1.9 2.2 0.9 0.7 1.8 3.5 2.4 0.1 0.9 0.1
13.1 1.4 2.8 0.1 0.8 0.1 3.6 70.2 2.2 1.8 0.1 0.1 2.4 0.1 0.1 1.1 0.1 0.1 0.1 0.9 0.1
2.4 0.5 0.1 0.5 1.1 0.1 0.4 0.5 91.6 0.1 0.1 0.1 0.1 0.1 0.1 0.6 1.9 0.5 0.1 0.3 0.1
2.2 0.6 0.2 2.9 1.4 1.2 0.7 0.1 0.1 84.6 0.7 1.1 0.1 0.1 1.6 0.1 0.1 0.1 0.1 3.2 0.1
1.9 0.1 0.4 0.1 0.4 0.1 0.3 0.6 0.7 0.1 71.1 7.6 0.1 1.4 1.5 0.1 0.7 0.8 0.3 0.1 12.5
4.1 0.8 0.2 0.1 0.1 0.3 1.2 0.2 0.1 0.5 4.0 78.4 0.6 2.9 2.8 0.7 0.2 0.6 0.1 0.8 2.4
6.3 0.8 7.1 1.5 0.1 0.1 0.1 0.2 5.1 2.1 1.4 0.1 71.1 0.1 0.1 0.8 1.1 0.1 0.1 0.1 3.0
4.2 0.4 0.1 0.1 0.8 0.1 0.1 0.1 0.1 0.6 6.8 9.9 0.1 69.7 0.1 0.1 1.4 0.1 0.1 0.1 6.5
2.8 0.1 0.1 0.1 0.1 0.1 0.5 0.1 0.5 0.5 1.1 4.1 0.1 0.7 78.6 1.1 1.1 0.7 0.7 5.7 2.0
2.9 3.7 0.5 1.1 0.1 0.1 1.1 0.9 0.3 0.2 1.7 0.7 0.1 0.8 0.1 83.5 1.9 0.4 0.1 0.1 0.7
4.1 4.0 0.4 2.6 1.9 1.4 0.2 1.5 1.8 0.8 0.4 0.4 0.7 0.1 0.2 2.8 70.2 5.4 0.1 1.2 0.5
2.2 1.4 0.4 2.6 0.8 0.8 1.3 0.8 1.3 0.7 0.9 0.1 0.9 0.7 0.1 0.7 5.3 76.9 0.1 0.5 2.3
0.1 0.1 0.9 0.1 0.1 0.1 0.1 0.1 0.1 0.1 2.2 1.7 0.9 0.1 6.9 0.1 0.1 0.1 82.1 4.2 1.5
2.7 0.1 0.6 0.6 0.1 0.1 0.1 0.1 0.5 1.7 0.7 1.0 0.5 0.3 8.8 0.1 0.1 0.1 0.1 82.2 0.6
4.4 4.3 0.2 1.1 0.2 1.2 0.1 0.6 0.5 0.1 6.0 3.8 0.7 0.1 1.3 0.7 2.1 3.2 0.2 0.5 69.4
//
H KOSJ950109
D Context-dependent optimal substitution matrices for alpha helix
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
70.7 1.7 2.1 2.5 2.0 2.2 1.8 0.7 2.7 1.7 1.9 1.1 0.3 0.8 1.0 2.4 0.2 2.6 1.1 0.3 0.1
9.1 63.1 0.9 0.5 1.1 0.9 1.2 2.2 3.5 0.2 0.3 1.4 1.8 0.8 0.3 1.1 6.4 2.6 0.2 0.4 2.3
11.4 1.2 68.9 1.0 0.3 0.2 3.0 0.4 0.2 1.4 0.4 1.4 5.1 0.4 0.2 0.6 1.7 1.1 0.3 0.3 0.6
13.8 1.8 0.6 60.2 3.7 0.2 1.4 3.7 0.9 1.2 0.9 0.4 2.0 0.7 0.5 0.1 4.0 1.8 0.3 1.1 0.8
11.0 2.7 1.1 4.1 61.0 0.3 0.5 9.8 1.4 0.5 0.4 0.4 1.6 0.3 0.3 1.2 2.0 1.0 0.2 0.3 0.0
12.3 3.5 0.0 0.7 1.3 66.6 0.1 1.8 1.5 0.0 1.2 1.3 0.0 0.9 0.9 0.4 2.6 1.7 0.3 0.1 2.8
10.1 3.3 4.1 2.0 1.6 0.3 61.3 3.7 0.4 2.2 0.0 1.9 3.6 0.4 0.3 0.8 2.1 0.5 0.5 0.5 0.5
3.9 4.0 1.1 1.5 6.6 0.4 6.0 61.5 1.4 0.8 0.4 1.1 4.8 0.3 0.1 1.1 2.2 1.7 0.1 0.2 0.9
15.0 3.7 1.0 1.2 1.4 0.4 0.8 1.1 69.8 0.4 0.1 0.4 0.9 0.3 0.4 0.3 1.2 0.7 0.0 0.3 0.8
9.4 0.4 4.2 4.9 1.4 0.0 3.4 1.0 0.1 65.5 0.5 0.1 2.5 0.6 1.7 0.2 0.4 1.4 0.0 2.0 0.5
10.7 0.6 0.3 0.4 0.1 0.3 0.1 0.4 0.3 0.1 65.9 6.9 0.5 2.1 1.5 0.2 0.3 1.6 0.0 0.3 7.3
6.3 0.7 0.6 0.5 0.1 0.3 0.7 0.3 0.1 0.3 4.9 72.6 1.0 2.9 2.9 0.2 0.3 0.7 0.2 1.1 3.2
1.6 3.1 8.0 3.2 1.7 0.1 4.3 6.0 1.1 1.1 0.5 1.4 58.5 1.0 0.0 0.5 2.3 3.1 0.5 0.4 1.7
4.2 3.3 0.3 0.6 0.1 0.4 1.6 1.3 1.1 0.1 5.8 11.8 0.2 58.3 1.8 0.0 1.0 3.1 0.7 0.2 4.1
5.5 1.1 0.0 0.3 0.3 0.3 0.4 0.3 0.1 0.4 0.5 5.5 0.0 0.6 72.9 0.3 0.8 0.9 2.2 6.7 1.0
13.6 1.5 0.8 0.6 1.8 0.1 0.7 0.8 0.5 1.0 0.9 0.9 2.0 0.0 0.1 69.1 3.1 1.4 0.3 0.1 0.8
0.8 9.5 2.0 3.8 2.3 1.4 2.5 2.1 3.7 1.5 0.8 0.9 1.7 0.4 0.4 0.8 56.3 7.9 0.2 0.4 0.7
14.6 3.8 0.9 1.4 0.4 0.4 0.4 0.6 1.0 0.5 1.4 2.7 1.4 0.8 0.3 1.2 4.7 59.9 0.0 0.4 3.5
6.1 0.7 0.2 0.1 0.9 0.1 0.1 0.0 0.0 0.0 0.0 1.0 2.2 0.2 0.5 0.1 0.6 0.0 84.5 1.7 1.1
1.9 1.1 0.4 0.6 0.1 0.6 0.1 1.0 0.1 3.0 1.1 4.6 0.9 1.0 9.0 0.0 0.9 0.6 0.5 71.7 0.9
0.8 8.5 0.7 0.4 0.1 0.8 0.3 0.9 0.2 0.3 15.1 5.9 0.4 1.7 0.8 0.2 0.2 2.8 0.3 0.8 58.9
//
H KOSJ950110
D Context-dependent optimal substitution matrices for beta sheet
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
68.7 1.0 2.7 1.2 2.0 3.0 2.1 1.7 1.1 1.0 0.7 1.4 1.4 1.3 0.7 2.9 2.9 1.3 1.0 0.8 1.1
5.8 64.6 1.1 1.0 1.3 1.1 0.5 1.8 3.0 0.8 0.2 0.7 0.8 1.1 0.1 2.2 6.7 3.8 0.0 0.6 3.0
15.4 0.3 66.4 0.4 0.9 0.0 3.8 1.2 1.8 1.2 0.5 0.3 4.5 0.5 0.3 0.8 1.0 0.4 0.1 0.2 0.2
6.7 0.2 1.8 63.9 7.6 0.1 1.9 0.3 1.3 2.1 0.3 0.9 3.4 0.2 0.1 1.4 4.8 1.4 0.0 0.9 0.7
11.6 1.1 0.2 3.8 70.5 0.3 0.9 4.5 2.0 0.2 0.5 0.3 1.1 0.0 0.4 0.3 0.9 0.6 0.0 0.5 0.4
17.0 4.6 0.0 0.4 1.1 62.5 0.0 0.3 1.3 0.5 2.6 2.2 0.1 0.2 2.3 0.0 2.7 1.5 0.0 0.2 0.6
12.2 1.0 1.6 1.3 0.7 0.0 63.2 5.4 0.6 0.9 0.3 2.8 3.1 1.2 0.2 0.5 0.9 1.9 0.5 0.6 1.2
9.6 1.3 0.8 1.4 5.6 0.1 2.2 66.1 1.3 0.8 0.4 0.7 3.1 0.2 0.1 0.5 2.6 1.0 0.3 0.2 1.8
6.4 2.5 0.4 0.3 0.6 0.3 0.3 0.3 84.6 0.5 0.0 0.1 0.2 0.2 0.1 0.3 1.4 0.8 0.1 0.0 0.5
5.9 0.2 4.9 3.0 1.0 0.8 2.7 2.3 2.1 60.3 0.0 2.3 0.3 1.0 0.9 1.7 4.4 3.6 0.6 1.6 0.7
4.2 0.4 0.5 0.4 0.1 0.6 0.1 0.1 0.0 0.1 62.0 8.3 0.3 2.2 2.6 0.3 0.4 1.5 0.3 0.5 15.1
8.1 0.8 0.2 0.2 0.1 0.5 0.7 0.3 0.3 0.6 4.4 72.2 0.3 2.8 2.3 0.5 0.3 0.3 0.2 0.8 4.2
8.3 1.6 9.8 1.5 0.4 0.4 3.2 2.2 0.3 1.2 1.0 1.1 60.9 0.3 0.4 0.5 1.7 3.4 0.4 0.6 0.9
7.3 4.4 1.9 0.4 0.2 0.8 2.7 1.0 1.0 0.2 4.4 7.5 1.4 56.2 2.4 0.5 1.9 2.5 0.1 0.1 3.2
4.2 0.1 0.1 0.2 0.1 0.6 0.0 0.0 0.6 0.4 2.4 2.9 0.2 1.4 75.8 0.0 0.9 0.7 1.2 6.3 2.0
16.8 3.6 0.2 0.3 0.3 0.0 1.1 0.3 1.1 0.4 0.1 0.8 0.4 0.1 0.0 69.9 3.1 1.2 0.0 0.1 0.1
16.3 2.3 1.7 2.4 0.8 0.7 0.7 0.9 4.0 1.1 0.3 0.1 1.0 0.5 0.6 1.8 59.3 4.6 0.1 0.3 0.7
7.7 2.9 1.3 1.4 1.4 0.4 0.7 2.6 0.6 0.9 2.1 1.0 3.4 0.6 0.2 0.3 5.2 64.0 0.2 0.7 2.7
5.5 0.0 0.5 0.0 0.0 0.0 0.1 0.1 0.0 0.1 0.1 0.8 0.1 0.5 1.8 0.0 0.5 0.0 87.5 2.3 0.0
4.4 0.5 0.8 1.2 0.1 0.9 0.5 0.2 0.0 1.9 1.3 1.2 0.6 0.0 6.1 0.4 1.2 0.6 0.7 77.2 0.3
6.3 2.2 0.7 0.2 0.3 0.6 0.6 0.7 0.1 0.2 8.7 3.1 0.3 0.8 0.7 0.4 1.2 2.5 0.2 0.3 70.1
//
H KOSJ950111
D Context-dependent optimal substitution matrices for turn
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
74.2 3.1 1.1 1.3 0.6 1.7 2.1 1.0 1.0 1.2 1.5 1.0 0.4 1.5 1.5 0.7 1.1 1.3 1.0 1.7 1.2
15.8 54.3 1.1 1.3 1.6 2.1 0.8 0.9 3.4 0.6 1.6 2.4 1.2 0.4 0.2 1.8 4.2 2.3 0.3 0.1 3.6
5.5 1.1 68.1 2.3 1.3 0.3 2.8 0.2 1.7 1.9 0.4 0.5 6.9 0.4 0.3 0.7 2.5 1.1 0.5 0.5 1.1
6.7 1.5 1.4 60.1 6.7 0.4 1.4 1.6 4.2 1.3 0.0 0.8 3.6 0.5 0.2 0.3 6.4 1.0 0.2 1.1 0.7
3.2 1.9 0.3 7.5 64.1 0.6 1.5 8.3 3.3 0.6 0.1 0.2 2.4 0.0 0.0 1.3 2.9 1.2 0.0 0.3 0.4
9.1 8.6 0.1 0.1 2.6 67.0 0.0 1.3 2.3 1.1 0.4 0.0 0.0 0.2 2.3 0.3 2.6 0.0 0.2 1.2 0.6
10.9 3.2 3.5 2.1 1.8 0.0 52.5 4.0 1.6 2.5 1.4 3.9 4.7 0.9 0.2 2.3 0.7 2.2 0.4 0.0 1.4
5.1 3.8 1.0 1.3 7.4 0.3 4.1 60.0 0.9 1.2 0.8 1.2 4.7 0.3 0.3 2.0 2.9 1.5 0.2 0.2 1.0
5.1 2.7 0.4 2.2 2.1 0.6 0.6 1.5 78.5 0.3 0.0 0.2 1.5 0.1 0.3 0.2 1.9 1.5 0.1 0.1 0.2
6.2 2.5 0.5 3.1 0.1 0.7 1.8 2.4 0.7 64.6 0.6 0.7 2.6 1.0 2.2 2.6 2.0 0.8 0.0 5.1 0.0
7.6 0.4 0.1 0.2 0.0 0.4 0.3 0.4 0.0 0.1 68.5 6.5 0.3 3.1 1.1 0.4 0.1 2.2 0.1 0.5 7.7
5.3 1.3 2.2 0.2 0.7 0.2 1.0 0.8 0.4 0.4 4.9 70.1 0.4 3.9 2.3 0.3 0.3 0.8 0.6 1.0 3.1
2.3 3.8 8.2 2.7 1.2 0.0 5.4 3.6 1.4 1.3 0.1 1.5 60.8 0.6 0.5 0.4 2.8 2.1 0.0 0.4 1.1
7.7 0.4 1.2 0.1 0.0 0.9 0.2 1.3 0.0 0.2 3.3 7.8 0.9 67.3 3.3 0.0 0.1 0.7 0.4 1.3 2.9
7.8 0.0 0.6 0.9 0.0 0.6 0.7 0.1 0.1 0.8 0.6 3.1 0.6 0.9 73.1 0.4 0.5 0.0 1.8 5.7 1.8
3.5 4.6 1.4 1.1 0.8 0.1 0.6 1.5 0.7 0.6 0.7 1.0 1.6 0.2 0.4 76.2 2.7 1.8 0.1 0.2 0.4
6.0 8.2 1.5 2.7 4.2 1.1 1.8 1.6 4.5 0.8 0.3 1.2 2.6 0.3 0.6 1.2 52.9 6.9 0.3 0.8 0.7
7.0 2.9 0.9 3.1 1.5 0.2 1.3 1.5 1.0 0.2 2.0 0.6 1.9 1.0 0.1 1.2 10.0 60.7 0.2 0.2 2.6
5.2 0.1 0.1 0.0 0.0 0.9 0.1 0.0 0.4 0.0 0.5 0.1 0.0 1.5 1.3 0.3 1.1 0.7 82.1 4.9 0.7
8.8 0.5 0.3 0.3 0.1 0.3 0.2 0.8 0.0 2.1 0.9 2.0 0.7 0.3 6.8 0.0 0.2 0.8 1.2 73.4 0.4
6.4 3.9 0.3 0.7 0.2 0.8 0.8 0.2 0.8 0.1 8.4 4.8 0.7 0.7 2.2 0.8 0.7 2.8 0.5 1.5 62.8
//
H KOSJ950112
D Context-dependent optimal substitution matrices for coil
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
60.6 3.0 2.1 1.0 1.3 2.0 2.9 3.2 1.8 2.0 2.7 1.5 1.5 2.4 1.6 1.8 1.5 1.8 1.3 1.7 2.4
19.0 55.6 0.4 0.5 0.8 2.7 1.2 0.8 4.3 0.3 0.6 0.8 0.8 0.2 0.3 2.3 4.7 2.6 0.0 0.1 2.0
13.6 0.5 64.3 1.3 0.1 0.1 1.3 0.6 0.2 2.0 0.2 1.3 5.8 0.0 0.1 1.6 2.7 2.9 0.4 0.7 0.5
6.4 1.0 1.9 59.8 4.8 0.7 1.6 2.8 2.3 2.2 0.7 0.9 3.6 0.8 0.2 0.1 5.4 2.6 0.1 1.0 1.3
8.6 1.5 0.5 6.2 66.7 0.3 1.8 5.0 1.2 0.6 0.6 0.5 1.3 0.1 0.1 1.2 1.6 1.1 0.0 1.1 0.2
13.0 11.3 0.4 0.2 1.1 59.3 0.0 1.6 0.9 0.1 2.3 0.1 0.0 1.5 1.0 0.0 2.9 1.0 0.9 0.6 2.0
19.2 1.5 2.5 1.7 1.3 0.0 51.2 7.4 0.9 0.9 0.3 0.7 3.1 1.3 0.7 0.3 2.3 3.2 0.0 0.5 1.1
20.4 3.3 1.0 0.7 3.4 0.4 2.9 60.6 1.2 0.8 0.2 0.5 1.2 0.1 0.0 0.4 1.3 0.7 0.0 0.3 0.6
11.7 1.2 0.2 1.0 1.3 0.3 0.4 0.8 77.9 0.3 0.1 0.1 0.5 0.1 0.1 0.5 2.0 0.8 0.1 0.3 0.4
12.9 1.4 1.2 1.9 2.3 0.6 1.4 0.5 0.3 68.2 0.9 0.8 0.3 0.2 1.3 0.7 2.1 0.1 0.4 2.6 0.0
17.1 0.6 0.4 0.2 0.1 0.6 0.3 1.0 0.4 0.2 55.0 5.2 1.1 1.6 1.6 0.9 0.4 1.0 0.7 0.3 11.5
10.2 0.8 0.6 0.2 0.1 0.3 1.5 0.2 0.3 0.6 4.9 68.2 0.7 3.0 3.0 0.9 0.1 0.7 0.2 0.8 2.7
9.7 3.4 6.0 1.7 2.7 0.0 3.2 3.9 2.0 1.3 0.4 1.3 55.4 0.4 0.6 1.9 2.8 1.9 0.2 0.2 1.3
15.4 0.0 0.0 0.2 0.4 0.4 0.3 0.6 0.0 0.8 6.5 9.4 0.1 56.8 0.6 0.1 0.5 3.0 0.2 0.1 4.5
10.2 0.2 0.4 0.2 0.0 0.2 0.5 0.0 0.3 0.4 1.2 3.6 0.1 0.6 70.9 1.1 0.8 0.7 1.1 5.9 1.7
11.9 5.1 0.8 0.5 0.3 0.0 1.4 1.7 0.8 0.4 0.3 0.8 0.5 0.4 0.3 69.9 2.7 0.5 0.0 0.5 1.4
9.9 4.4 0.7 3.4 3.2 1.3 0.9 1.3 2.5 0.5 0.4 0.4 1.2 0.1 0.3 3.6 57.1 6.9 0.3 0.5 1.2
11.7 3.2 0.7 2.7 0.8 0.5 1.6 0.5 1.0 0.6 1.7 0.9 1.2 0.8 0.2 2.0 7.5 58.8 0.0 0.6 3.3
8.4 0.0 0.4 0.5 0.0 0.2 0.0 0.0 0.0 0.1 2.9 0.9 0.9 0.7 4.3 0.0 1.4 0.0 76.5 2.1 0.7
10.9 0.3 0.3 0.3 0.3 0.1 0.1 0.1 0.6 0.9 0.1 0.7 0.7 0.5 8.4 0.1 0.1 0.4 0.9 73.3 0.9
15.5 3.3 0.1 0.9 0.3 0.7 0.3 0.8 0.3 0.1 6.3 3.9 0.8 1.1 1.0 0.5 1.6 3.0 0.3 0.5 58.8
//
H KOSJ950113
D Context-dependent optimal substitution matrices for exposed residues
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
60.2 3.3 1.7 1.1 1.1 2.8 2.1 1.2 1.8 2.2 2.6 2.3 0.7 2.2 2.2 2.1 1.7 2.1 2.1 1.8 2.7
21.5 51.3 0.7 0.6 1.1 1.0 1.2 1.2 3.0 0.4 1.2 2.1 1.2 0.7 0.2 2.1 4.2 2.8 0.3 0.2 3.2
11.4 1.2 62.9 1.6 0.7 0.1 2.9 0.9 0.7 1.6 0.6 1.1 7.3 0.5 0.4 0.6 2.2 1.6 0.6 0.4 0.8
7.5 1.8 1.5 52.6 6.4 0.4 2.3 2.7 2.8 1.7 0.4 1.0 4.8 0.8 0.4 0.1 7.9 2.7 0.3 1.2 0.9
7.4 2.8 0.7 8.0 59.2 0.3 1.7 8.3 2.3 0.3 0.4 0.4 2.3 0.2 0.1 1.4 2.6 1.2 0.0 0.4 0.2
18.1 4.2 0.0 0.3 1.3 64.7 0.0 0.9 1.1 0.5 1.1 1.0 0.0 1.5 2.2 0.0 1.7 0.9 0.0 0.1 0.3
13.9 3.1 3.7 1.8 1.7 0.1 51.0 5.9 1.0 1.7 0.5 3.0 3.9 0.8 0.1 1.0 2.3 2.6 0.1 0.6 1.4
7.8 4.3 0.9 1.3 6.7 0.2 4.5 58.3 1.1 1.1 0.6 1.0 4.2 0.5 0.3 1.4 2.5 1.8 0.2 0.1 1.3
11.8 2.6 0.4 2.2 2.3 0.3 0.6 1.6 71.0 0.3 0.0 0.1 1.2 0.3 0.5 0.3 2.2 1.7 0.2 0.2 0.4
14.1 0.9 3.3 5.0 1.0 0.1 2.2 1.7 0.8 54.8 0.6 1.1 1.3 0.5 1.9 1.4 2.6 0.1 0.0 4.4 2.4
17.2 0.3 0.3 0.2 0.1 0.3 0.2 0.3 0.0 0.1 54.4 7.6 0.7 2.0 1.5 0.6 0.0 2.1 0.3 0.6 11.3
15.0 0.7 1.2 0.4 0.1 0.2 0.8 0.4 0.3 0.6 3.8 64.4 0.8 3.5 2.8 0.5 0.3 0.6 0.5 0.7 2.6
4.8 3.8 7.9 2.3 1.6 0.2 4.6 4.9 1.2 1.3 0.4 1.4 56.0 0.4 0.4 0.9 3.0 3.2 0.1 0.3 1.4
14.4 2.8 0.7 0.2 0.0 0.4 1.1 1.9 1.1 0.1 6.6 7.7 1.8 49.9 2.1 0.1 1.4 2.7 0.8 0.8 3.5
14.2 0.6 0.5 0.5 0.2 0.5 0.4 0.2 0.1 0.5 1.7 2.8 0.7 0.6 66.6 0.4 0.8 0.5 1.1 5.9 1.2
13.8 4.9 1.3 0.6 0.8 0.0 0.8 1.3 0.9 0.4 0.4 1.0 1.3 0.3 0.1 66.0 3.5 1.3 0.1 0.4 0.9
11.3 7.4 1.3 2.7 3.0 0.9 1.1 1.9 4.3 0.8 0.1 0.5 1.8 0.3 0.3 2.3 50.1 8.1 0.0 0.5 1.3
13.7 4.0 0.9 2.5 1.2 0.2 1.3 1.2 0.6 0.6 2.8 2.3 2.0 0.7 0.2 1.3 7.4 53.0 0.3 0.4 3.6
13.7 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.6 2.0 0.5 0.2 2.5 0.4 0.0 0.1 75.4 4.2 0.1
11.6 0.6 0.4 0.4 0.2 0.5 0.1 0.6 0.2 1.5 1.6 3.0 0.6 0.4 7.8 0.1 0.7 0.7 1.0 66.8 1.2
17.5 2.5 0.4 0.5 0.4 0.6 0.8 0.6 0.6 0.6 10.4 3.7 0.7 0.9 1.6 0.3 0.7 1.6 0.3 0.7 54.8
//
H KOSJ950114
D Context-dependent optimal substitution matrices for buried residues
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
79.2 0.2 1.6 1.2 1.9 1.2 1.2 2.0 0.7 0.2 0.4 0.2 4.0 0.4 0.4 1.6 1.8 0.7 0.4 0.4 0.3
1.0 76.3 0.6 0.5 0.6 1.7 0.6 1.0 2.8 0.2 0.9 1.5 0.4 0.5 0.3 1.1 4.4 1.7 0.0 0.4 3.7
8.2 0.7 72.9 0.9 0.1 0.4 2.4 0.4 0.9 1.7 1.1 1.4 3.7 0.2 0.3 0.6 1.7 1.9 0.1 0.4 0.1
6.2 2.0 1.1 65.7 3.1 0.6 1.3 0.9 2.5 1.6 1.2 1.5 1.6 0.4 0.1 0.5 4.8 2.6 0.1 1.0 1.3
9.7 2.5 0.6 3.0 66.9 0.4 0.6 4.2 2.0 0.7 0.8 0.8 0.9 0.0 0.2 1.0 2.7 1.5 0.2 1.0 0.5
5.7 6.9 0.1 0.1 1.5 71.6 0.1 0.6 1.4 0.3 1.8 2.0 0.0 0.5 1.3 0.0 2.0 0.7 0.1 0.1 3.2
6.1 2.4 1.7 1.3 0.9 0.4 67.3 2.0 0.8 1.9 0.6 3.6 2.9 2.3 1.0 0.9 1.3 1.1 0.8 0.4 0.5
9.9 4.0 1.8 0.6 2.5 0.4 3.8 62.5 1.8 0.5 0.1 2.5 1.6 0.3 0.0 0.5 2.5 1.0 0.0 1.3 2.5
3.6 3.6 0.3 0.6 0.5 0.3 0.4 0.4 85.7 0.2 0.1 0.3 0.5 0.1 0.1 0.2 1.7 0.7 0.2 0.1 0.4
1.0 0.6 0.8 0.9 0.6 0.4 1.4 0.5 0.0 84.1 0.6 1.0 0.6 0.8 2.0 0.3 0.5 0.5 0.6 2.6 0.2
1.8 0.4 0.3 0.3 0.2 0.4 0.1 0.2 0.0 0.1 73.9 7.7 0.4 2.2 1.5 0.2 0.3 0.8 0.2 0.2 8.8
1.1 0.6 0.3 0.4 0.2 0.5 0.9 0.6 0.2 0.2 5.0 78.6 1.1 3.0 2.4 0.3 0.1 0.4 0.2 0.5 3.4
20.3 1.8 5.4 1.6 0.5 0.0 1.3 1.8 1.7 1.5 1.6 4.8 46.8 1.1 0.6 0.4 1.1 2.8 0.2 1.1 3.7
2.2 1.2 0.2 0.3 0.2 0.7 0.6 0.3 0.4 0.2 5.1 12.2 0.3 68.7 2.2 0.1 0.1 0.4 0.4 0.1 4.2
1.9 0.2 0.1 0.1 0.1 0.3 0.2 0.0 0.4 0.5 1.5 4.7 0.1 1.0 80.2 0.1 0.5 0.4 1.6 4.6 1.4
7.8 4.6 0.4 1.0 0.2 0.1 1.2 0.8 0.9 0.8 1.0 1.3 0.3 0.5 0.4 73.3 2.9 1.5 0.0 0.0 1.0
8.8 7.1 1.1 1.5 0.8 1.6 0.9 0.6 2.2 0.8 0.5 0.4 0.7 0.4 1.1 1.2 62.2 5.9 0.1 0.9 1.2
3.5 3.8 0.5 0.8 0.4 0.9 0.8 0.9 0.6 0.3 3.1 1.7 0.9 1.7 0.2 0.6 4.5 68.2 0.0 0.4 6.4
1.9 0.0 0.6 0.0 0.0 0.4 0.2 0.0 0.2 0.1 0.7 0.8 0.7 0.7 1.4 0.0 0.5 0.2 89.0 1.7 0.8
2.0 0.4 0.4 0.6 0.2 0.6 0.2 0.3 0.0 1.5 0.9 2.0 0.5 0.5 9.7 0.2 0.2 0.5 0.7 78.0 0.6
1.4 2.5 0.2 0.3 0.2 0.8 0.1 0.6 0.1 0.1 11.1 3.8 0.9 1.0 1.2 0.3 0.5 1.6 0.2 0.1 73.0
//
H KOSJ950115
D Context-dependent optimal substitution matrices for all residues
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
69.2 1.6 2.0 1.1 1.3 2.4 2.0 1.4 1.5 1.7 1.2 1.3 0.9 1.7 1.1 2.1 2.1 1.5 1.0 1.3 1.7
8.9 61.9 0.8 0.6 1.3 1.6 1.0 1.6 3.7 0.3 0.6 1.6 1.3 0.5 0.2 1.9 5.9 3.2 0.2 0.4 2.6
11.3 1.3 67.2 1.4 0.7 0.2 2.4 0.7 0.6 1.3 0.6 1.0 5.7 0.3 0.2 0.7 1.9 1.4 0.3 0.5 0.4
6.4 1.8 1.5 60.9 5.4 0.3 1.8 2.0 2.5 1.6 0.5 0.8 3.5 0.7 0.1 0.4 5.6 2.0 0.4 1.0 1.0
7.3 2.0 0.5 6.1 65.0 0.4 1.2 6.9 1.9 0.3 0.4 0.4 1.9 0.3 0.2 1.1 2.4 1.0 0.0 0.5 0.2
13.8 6.6 0.0 0.3 1.6 64.4 0.0 1.2 1.3 0.5 1.8 1.2 0.0 0.5 1.6 0.0 2.6 1.0 0.2 0.2 1.2
11.4 2.4 3.3 1.6 1.7 0.2 58.4 4.9 1.0 1.8 0.5 2.0 3.5 0.8 0.3 1.0 1.9 1.9 0.5 0.5 0.6
7.9 3.2 1.0 1.4 5.8 0.3 4.3 62.1 1.2 0.9 0.4 1.1 4.0 0.2 0.1 1.2 2.2 1.3 0.2 0.1 1.2
8.4 2.5 0.4 1.4 1.6 0.4 0.5 1.1 77.8 0.3 0.0 0.2 1.0 0.1 0.2 0.3 1.9 1.1 0.1 0.2 0.4
9.5 0.9 2.7 2.8 1.1 0.3 2.4 1.4 0.8 65.4 0.5 1.5 1.5 0.8 1.5 1.0 1.9 0.5 0.4 2.9 0.3
6.9 0.8 0.3 0.4 0.1 0.4 0.1 0.4 0.2 0.1 64.8 7.7 0.4 2.0 1.7 0.3 0.3 1.6 0.3 0.3 10.9
7.1 0.9 0.7 0.2 0.1 0.3 1.0 0.3 0.1 0.4 4.7 71.7 0.8 3.2 2.8 0.3 0.2 0.6 0.2 0.8 3.7
5.0 2.9 8.1 2.3 1.4 0.1 4.1 4.3 1.1 1.2 0.4 1.4 58.7 0.5 0.5 1.2 2.5 2.6 0.1 0.3 1.4
9.4 2.0 0.8 0.2 1.3 0.4 1.0 0.9 0.6 0.2 5.5 9.2 0.8 59.4 2.2 0.1 0.6 1.7 0.2 0.2 3.4
6.4 0.3 0.2 0.4 0.2 0.4 0.4 0.2 0.3 0.4 1.4 3.7 0.1 0.9 73.8 0.3 0.9 0.6 1.4 6.4 1.5
12.0 3.5 0.9 0.6 0.6 0.0 0.8 1.0 0.7 0.4 0.5 0.9 0.9 0.6 0.1 71.2 2.8 1.4 0.0 0.5 0.7
11.7 5.1 1.4 3.0 2.2 0.9 1.1 1.5 3.3 0.6 0.4 0.5 1.4 0.3 0.5 1.8 56.8 6.1 0.3 0.5 0.8
8.8 3.1 0.9 2.2 1.1 0.4 1.1 1.2 0.9 0.6 2.0 1.4 2.0 0.8 0.1 1.1 6.9 61.8 0.1 0.4 3.2
6.0 0.1 0.4 0.1 0.0 0.7 0.1 0.0 0.5 0.1 0.4 1.0 0.6 0.8 2.3 0.0 1.3 0.2 82.3 2.5 0.7
7.4 0.6 0.5 0.6 0.4 0.7 0.2 0.5 0.3 1.7 0.9 2.0 0.6 0.4 7.1 0.1 0.6 0.9 0.7 73.2 0.7
9.8 3.7 0.5 0.4 0.2 0.8 0.5 0.4 0.3 0.1 8.8 3.6 0.4 0.8 1.2 0.4 0.9 2.5 0.2 0.5 64.0
//
H OVEJ920102
D Environment-specific amino acid substitution matrix for alpha residues
(Overington et al., 1992)
R LIT:1811128 PMID:1304904
A Overington, J., Donnelly, D., Johnson, M.S., Sali, A. and Blundell, T.L.
T Environment-specific amino acid substitution tables: tertiary templates
and prediction of protein folds
J Protein Science 1, 216-226 (1992)
M rows = ACDEFGHIKLMNPQRSTVWYJ-, cols = ACDEFGHIKLMNPQRSTVWYJ
0.355 0.007 0.090 0.100 0.050 0.177 0.037 0.077 0.096 0.056 0.081 0.103 0.106 0.090 0.088 0.163 0.120 0.098 0.065 0.036 0.252
0.001 0.901 0.000 0.000 0.000 0.000 0.000 0.004 0.001 0.000 0.000 0.003 0.000 0.006 0.006 0.004 0.002 0.000 0.007 0.000 0.000
0.038 0.000 0.315 0.109 0.006 0.041 0.027 0.009 0.033 0.004 0.009 0.088 0.051 0.089 0.023 0.065 0.048 0.013 0.012 0.011 0.009
0.044 0.011 0.111 0.305 0.011 0.048 0.026 0.011 0.059 0.013 0.009 0.068 0.069 0.086 0.053 0.033 0.045 0.017 0.012 0.018 0.000
0.017 0.000 0.005 0.007 0.415 0.004 0.009 0.039 0.025 0.097 0.042 0.013 0.006 0.011 0.009 0.009 0.014 0.041 0.053 0.085 0.009
0.065 0.000 0.070 0.042 0.006 0.370 0.017 0.022 0.029 0.013 0.015 0.036 0.043 0.031 0.013 0.068 0.049 0.014 0.009 0.021 0.045
0.010 0.000 0.012 0.011 0.010 0.007 0.571 0.003 0.022 0.005 0.015 0.043 0.006 0.035 0.021 0.016 0.008 0.017 0.009 0.037 0.009
0.029 0.014 0.009 0.008 0.048 0.021 0.004 0.325 0.017 0.076 0.107 0.018 0.007 0.007 0.015 0.014 0.033 0.112 0.016 0.030 0.018
0.053 0.007 0.044 0.081 0.020 0.041 0.044 0.026 0.336 0.029 0.059 0.073 0.045 0.094 0.163 0.041 0.054 0.026 0.041 0.028 0.036
0.038 0.000 0.006 0.018 0.210 0.019 0.004 0.139 0.033 0.415 0.225 0.033 0.016 0.041 0.028 0.029 0.026 0.133 0.037 0.057 0.036
0.013 0.000 0.004 0.003 0.016 0.007 0.000 0.043 0.014 0.053 0.197 0.010 0.000 0.018 0.004 0.003 0.010 0.018 0.021 0.021 0.018
0.031 0.007 0.057 0.035 0.010 0.026 0.054 0.012 0.034 0.012 0.013 0.195 0.015 0.066 0.026 0.037 0.046 0.012 0.002 0.048 0.000
0.022 0.000 0.036 0.035 0.005 0.026 0.011 0.009 0.020 0.006 0.000 0.013 0.424 0.013 0.016 0.039 0.011 0.009 0.002 0.000 0.000
0.025 0.011 0.045 0.039 0.011 0.021 0.031 0.004 0.045 0.015 0.035 0.059 0.015 0.183 0.029 0.030 0.030 0.008 0.007 0.025 0.009
0.019 0.011 0.012 0.023 0.005 0.008 0.019 0.010 0.069 0.009 0.004 0.018 0.013 0.028 0.348 0.030 0.019 0.005 0.007 0.018 0.018
0.086 0.021 0.075 0.047 0.012 0.079 0.033 0.020 0.041 0.020 0.009 0.089 0.082 0.069 0.063 0.264 0.096 0.028 0.005 0.020 0.054
0.043 0.007 0.039 0.033 0.020 0.038 0.014 0.026 0.032 0.015 0.026 0.057 0.028 0.046 0.035 0.065 0.266 0.037 0.016 0.034 0.000
0.055 0.000 0.018 0.021 0.069 0.022 0.044 0.178 0.025 0.111 0.016 0.018 0.025 0.017 0.015 0.129 0.060 0.350 0.012 0.043 0.162
0.009 0.000 0.003 0.004 0.022 0.004 0.007 0.006 0.012 0.006 0.020 0.001 0.001 0.006 0.004 0.002 0.007 0.003 0.588 0.064 0.000
0.009 0.000 0.006 0.006 0.046 0.006 0.029 0.014 0.007 0.013 0.031 0.033 0.003 0.020 0.010 0.007 0.017 0.016 0.078 0.377 0.027
0.009 0.000 0.001 0.000 0.001 0.004 0.001 0.002 0.002 0.002 0.004 0.000 0.000 0.004 0.003 0.006 0.004 0.010 0.000 0.005 0.297
0.028 0.004 0.041 0.074 0.010 0.029 0.017 0.022 0.050 0.031 0.033 0.031 0.045 0.039 0.028 0.047 0.034 0.032 0.002 0.021 0.000
//
H OVEJ920103
D Environment-specific amino acid substitution matrix for beta residues
(Overington et al., 1992)
R LIT:1811128 PMID:1304904
A Overington, J., Donnelly, D., Johnson, M.S., Sali, A. and Blundell, T.L.
T Environment-specific amino acid substitution tables: tertiary templates
and prediction of protein folds
J Protein Science 1, 216-226 (1992)
M rows = ACDEFGHIKLMNPQRSTVWYJ-, cols = ACDEFGHIKLMNPQRSTVWYJ
0.275 0.000 0.025 0.047 0.023 0.086 0.007 0.029 0.036 0.031 0.074 0.041 0.035 0.050 0.050 0.057 0.055 0.065 0.014 0.031 0.080
0.000 0.910 0.000 0.016 0.014 0.000 0.000 0.003 0.008 0.000 0.000 0.000 0.000 0.008 0.015 0.002 0.001 0.000 0.000 0.000 0.020
0.008 0.000 0.350 0.059 0.008 0.011 0.014 0.017 0.018 0.006 0.000 0.095 0.040 0.020 0.010 0.026 0.020 0.013 0.006 0.012 0.000
0.018 0.016 0.054 0.192 0.004 0.015 0.021 0.012 0.071 0.009 0.037 0.039 0.028 0.056 0.053 0.018 0.036 0.018 0.002 0.015 0.000
0.020 0.022 0.013 0.005 0.398 0.008 0.021 0.049 0.017 0.046 0.023 0.006 0.012 0.006 0.015 0.020 0.012 0.021 0.071 0.096 0.020
0.092 0.000 0.021 0.033 0.015 0.623 0.007 0.016 0.018 0.016 0.042 0.019 0.017 0.033 0.017 0.036 0.028 0.013 0.049 0.021 0.020
0.003 0.000 0.006 0.010 0.008 0.002 0.332 0.006 0.022 0.004 0.000 0.035 0.014 0.021 0.023 0.009 0.010 0.009 0.000 0.008 0.020
0.040 0.010 0.044 0.021 0.089 0.020 0.017 0.358 0.022 0.105 0.077 0.025 0.012 0.010 0.015 0.021 0.026 0.119 0.041 0.034 0.020
0.024 0.011 0.021 0.099 0.015 0.007 0.070 0.013 0.299 0.017 0.012 0.060 0.052 0.060 0.139 0.026 0.051 0.010 0.004 0.017 0.040
0.057 0.000 0.027 0.031 0.111 0.023 0.031 0.143 0.051 0.459 0.169 0.031 0.038 0.026 0.031 0.025 0.028 0.119 0.096 0.044 0.060
0.026 0.000 0.006 0.021 0.011 0.013 0.021 0.021 0.007 0.031 0.244 0.010 0.002 0.031 0.002 0.007 0.013 0.019 0.006 0.006 0.000
0.016 0.000 0.092 0.044 0.003 0.018 0.073 0.008 0.038 0.008 0.019 0.261 0.026 0.016 0.011 0.036 0.032 0.004 0.012 0.017 0.000
0.014 0.000 0.027 0.020 0.001 0.005 0.021 0.007 0.029 0.019 0.002 0.017 0.504 0.011 0.023 0.010 0.021 0.009 0.018 0.003 0.000
0.038 0.014 0.033 0.068 0.006 0.020 0.073 0.008 0.071 0.014 0.077 0.037 0.019 0.414 0.118 0.025 0.045 0.015 0.002 0.013 0.000
0.022 0.011 0.006 0.042 0.007 0.010 0.038 0.008 0.079 0.008 0.002 0.012 0.031 0.055 0.214 0.015 0.027 0.010 0.014 0.017 0.000
0.078 0.003 0.085 0.041 0.029 0.056 0.052 0.024 0.048 0.022 0.030 0.112 0.040 0.042 0.065 0.403 0.140 0.028 0.014 0.040 0.040
0.081 0.002 0.075 0.111 0.021 0.037 0.052 0.027 0.095 0.022 0.049 0.110 0.073 0.078 0.092 0.153 0.363 0.044 0.008 0.037 0.020
0.141 0.000 0.058 0.065 0.074 0.027 0.070 0.202 0.034 0.145 0.123 0.019 0.033 0.039 0.046 0.043 0.062 0.446 0.027 0.059 0.040
0.005 0.000 0.008 0.002 0.048 0.000 0.000 0.013 0.001 0.019 0.005 0.015 0.012 0.001 0.013 0.003 0.002 0.005 0.559 0.017 0.000
0.026 0.000 0.027 0.037 0.112 0.011 0.049 0.024 0.020 0.018 0.014 0.033 0.005 0.013 0.032 0.026 0.022 0.023 0.051 0.505 0.000
0.003 0.002 0.000 0.000 0.001 0.001 0.007 0.001 0.003 0.001 0.000 0.000 0.000 0.000 0.000 0.002 0.001 0.001 0.000 0.000 0.620
0.012 0.000 0.021 0.007 0.002 0.006 0.021 0.012 0.013 0.004 0.002 0.021 0.007 0.008 0.015 0.038 0.007 0.009 0.004 0.009 0.000
//
H OVEJ920104
D Environment-specific amino acid substitution matrix for accessible
residues (Overington et al., 1992)
R LIT:1811128 PMID:1304904
A Overington, J., Donnelly, D., Johnson, M.S., Sali, A. and Blundell, T.L.
T Environment-specific amino acid substitution tables: tertiary templates
and prediction of protein folds
J Protein Science 1, 216-226 (1992)
M rows = ACDEFGHIKLMNPQRSTVWYJ-, cols = ACDEFGHIKLMNPQRSTVWYJ
0.224 0.013 0.055 0.068 0.031 0.067 0.048 0.053 0.068 0.050 0.087 0.059 0.067 0.073 0.062 0.074 0.059 0.079 0.033 0.035 0.121
0.002 0.739 0.001 0.006 0.012 0.000 0.001 0.004 0.003 0.000 0.000 0.001 0.001 0.005 0.008 0.001 0.001 0.000 0.001 0.000 0.008
0.044 0.007 0.284 0.091 0.016 0.041 0.056 0.033 0.034 0.012 0.022 0.094 0.047 0.052 0.025 0.054 0.044 0.025 0.014 0.023 0.030
0.052 0.029 0.079 0.251 0.016 0.028 0.026 0.026 0.053 0.019 0.031 0.038 0.037 0.071 0.049 0.031 0.044 0.034 0.010 0.027 0.008
0.010 0.029 0.006 0.008 0.291 0.004 0.023 0.046 0.011 0.047 0.032 0.012 0.006 0.010 0.009 0.011 0.013 0.018 0.093 0.073 0.000
0.079 0.000 0.066 0.047 0.020 0.455 0.042 0.024 0.033 0.028 0.039 0.073 0.054 0.054 0.040 0.064 0.037 0.039 0.041 0.036 0.038
0.013 0.003 0.021 0.011 0.024 0.010 0.284 0.008 0.021 0.011 0.020 0.035 0.008 0.020 0.023 0.013 0.012 0.020 0.014 0.025 0.023
0.014 0.016 0.017 0.014 0.058 0.006 0.010 0.235 0.015 0.050 0.048 0.018 0.009 0.009 0.015 0.014 0.023 0.075 0.015 0.030 0.008
0.062 0.007 0.039 0.072 0.032 0.027 0.068 0.039 0.294 0.050 0.077 0.055 0.045 0.077 0.122 0.043 0.059 0.044 0.037 0.035 0.053
0.028 0.000 0.010 0.017 0.097 0.013 0.024 0.094 0.035 0.311 0.141 0.030 0.030 0.028 0.027 0.019 0.029 0.073 0.064 0.033 0.015
0.010 0.000 0.003 0.005 0.015 0.005 0.005 0.020 0.011 0.030 0.167 0.004 0.003 0.017 0.005 0.003 0.007 0.013 0.004 0.008 0.015
0.041 0.007 0.080 0.041 0.022 0.044 0.087 0.031 0.042 0.035 0.024 0.239 0.019 0.040 0.031 0.050 0.051 0.021 0.008 0.036 0.030
0.053 0.000 0.039 0.036 0.036 0.006 0.027 0.018 0.017 0.034 0.014 0.018 0.412 0.021 0.026 0.037 0.031 0.019 0.018 0.008 0.015
0.040 0.013 0.038 0.060 0.018 0.025 0.042 0.017 0.046 0.026 0.075 0.032 0.019 0.231 0.056 0.032 0.042 0.036 0.007 0.015 0.023
0.025 0.023 0.015 0.031 0.010 0.017 0.033 0.017 0.062 0.019 0.015 0.022 0.018 0.047 0.248 0.026 0.028 0.022 0.022 0.023 0.000
0.100 0.013 0.088 0.059 0.044 0.073 0.057 0.051 0.062 0.043 0.026 0.096 0.070 0.072 0.079 0.290 0.138 0.057 0.025 0.059 0.053
0.054 0.010 0.049 0.058 0.042 0.029 0.037 0.059 0.058 0.039 0.049 0.068 0.042 0.066 0.053 0.099 0.266 0.061 0.021 0.041 0.015
0.041 0.000 0.021 0.033 0.040 0.020 0.038 0.148 0.031 0.077 0.051 0.018 0.020 0.043 0.033 0.028 0.044 0.269 0.023 0.049 0.091
0.005 0.000 0.002 0.002 0.049 0.006 0.006 0.009 0.006 0.017 0.005 0.003 0.004 0.003 0.008 0.003 0.004 0.003 0.421 0.038 0.000
0.014 0.000 0.013 0.018 0.111 0.012 0.034 0.028 0.017 0.023 0.026 0.023 0.005 0.012 0.024 0.018 0.019 0.028 0.109 0.355 0.023
0.002 0.000 0.001 0.000 0.001 0.002 0.002 0.001 0.002 0.001 0.003 0.001 0.001 0.001 0.001 0.002 0.001 0.007 0.000 0.001 0.341
0.086 0.092 0.072 0.072 0.045 0.089 0.060 0.043 0.061 0.075 0.048 0.061 0.083 0.050 0.056 0.087 0.050 0.057 0.021 0.048 0.091
//
H OVEJ920105
D Environment-specific amino acid substitution matrix for inaccessible residues
(Overington et al., 1992)
R LIT:1811128 PMID:1304904
A Overington, J., Donnelly, D., Johnson, M.S., Sali, A. and Blundell, T.L.
T Environment-specific amino acid substitution tables: tertiary templates
and prediction of protein folds
J Protein Science 1, 216-226 (1992)
M rows = ACDEFGHIKLMNPQRSTVWYJ-, cols = ACDEFGHIKLMNPQRSTVWYJ
0.426 0.022 0.025 0.095 0.036 0.075 0.009 0.039 0.000 0.029 0.061 0.036 0.041 0.053 0.015 0.149 0.103 0.071 0.020 0.032 0.112
0.007 0.879 0.000 0.000 0.005 0.000 0.000 0.003 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.008 0.004 0.000 0.003 0.001 0.004
0.012 0.000 0.775 0.042 0.002 0.008 0.004 0.007 0.000 0.002 0.001 0.112 0.004 0.011 0.000 0.016 0.005 0.005 0.000 0.006 0.000
0.007 0.009 0.011 0.460 0.004 0.008 0.000 0.005 0.000 0.003 0.009 0.036 0.000 0.064 0.015 0.009 0.001 0.006 0.000 0.001 0.000
0.022 0.014 0.004 0.011 0.493 0.006 0.015 0.045 0.000 0.075 0.036 0.006 0.016 0.005 0.000 0.012 0.013 0.033 0.058 0.143 0.017
0.070 0.000 0.016 0.037 0.006 0.732 0.000 0.013 0.000 0.007 0.015 0.009 0.004 0.013 0.023 0.064 0.032 0.008 0.005 0.004 0.043
0.005 0.000 0.002 0.000 0.003 0.003 0.705 0.003 0.029 0.003 0.006 0.058 0.000 0.061 0.008 0.008 0.001 0.006 0.005 0.014 0.000
0.043 0.007 0.009 0.032 0.061 0.017 0.009 0.402 0.029 0.110 0.096 0.015 0.018 0.008 0.008 0.013 0.036 0.135 0.043 0.038 0.017
0.014 0.010 0.000 0.005 0.002 0.004 0.002 0.003 0.412 0.003 0.004 0.021 0.014 0.008 0.145 0.013 0.007 0.004 0.000 0.006 0.004
0.048 0.005 0.005 0.037 0.162 0.015 0.022 0.163 0.015 0.524 0.250 0.033 0.031 0.032 0.038 0.027 0.022 0.130 0.048 0.052 0.030
0.019 0.000 0.004 0.037 0.014 0.004 0.019 0.027 0.000 0.048 0.262 0.027 0.000 0.072 0.000 0.009 0.018 0.020 0.014 0.017 0.009
0.011 0.000 0.071 0.011 0.005 0.007 0.028 0.006 0.000 0.002 0.013 0.398 0.007 0.005 0.008 0.035 0.012 0.003 0.006 0.009 0.009
0.014 0.002 0.005 0.000 0.011 0.013 0.004 0.005 0.000 0.002 0.000 0.015 0.764 0.008 0.008 0.005 0.012 0.007 0.000 0.001 0.000
0.017 0.009 0.002 0.101 0.002 0.009 0.039 0.001 0.088 0.003 0.039 0.018 0.000 0.560 0.122 0.008 0.001 0.007 0.006 0.005 0.004
0.013 0.009 0.000 0.058 0.003 0.004 0.015 0.004 0.294 0.003 0.001 0.000 0.002 0.040 0.588 0.013 0.002 0.004 0.003 0.007 0.009
0.074 0.010 0.023 0.016 0.011 0.039 0.017 0.009 0.015 0.007 0.016 0.103 0.020 0.013 0.000 0.450 0.111 0.017 0.005 0.004 0.052
0.044 0.006 0.012 0.000 0.006 0.018 0.006 0.015 0.015 0.009 0.025 0.024 0.025 0.005 0.008 0.081 0.504 0.025 0.002 0.005 0.034
0.116 0.001 0.012 0.053 0.073 0.015 0.054 0.205 0.000 0.134 0.118 0.033 0.031 0.027 0.015 0.043 0.079 0.476 0.014 0.047 0.082
0.006 0.003 0.007 0.000 0.024 0.001 0.011 0.011 0.000 0.009 0.013 0.003 0.000 0.005 0.000 0.003 0.001 0.005 0.731 0.031 0.000
0.015 0.001 0.005 0.000 0.071 0.006 0.034 0.021 0.029 0.013 0.023 0.024 0.007 0.008 0.000 0.014 0.012 0.017 0.037 0.561 0.009
0.013 0.002 0.000 0.000 0.002 0.002 0.000 0.002 0.000 0.002 0.003 0.006 0.000 0.003 0.000 0.008 0.007 0.003 0.000 0.004 0.547
0.006 0.010 0.012 0.005 0.007 0.013 0.006 0.011 0.074 0.010 0.009 0.018 0.016 0.000 0.000 0.011 0.018 0.016 0.002 0.012 0.017
//
H LINK010101
D Substitution matrices from an neural network model (Lin et al., 2001)
R PMID:11694178
A Lin, K., May, A.C. and Taylor, W.R.
T Amino acid substitution matrices from an artificial neural network
model
J J Comput Biol. 8, 471-481 (2001)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.441 0.030 0.020 0.033 0.000 0.029 0.045 0.064 0.011 0.021 0.043 0.032 0.010 0.015 0.029 0.069 0.041 0.003 0.009 0.055
0.034 0.519 0.026 0.012 0.001 0.047 0.033 0.022 0.014 0.020 0.029 0.134 0.007 0.005 0.019 0.041 0.013 0.004 0.015 0.004
0.029 0.036 0.396 0.097 0.001 0.034 0.046 0.051 0.015 0.014 0.021 0.053 0.006 0.008 0.009 0.088 0.054 0.002 0.017 0.025
0.039 0.012 0.070 0.522 0.000 0.031 0.102 0.042 0.008 0.003 0.006 0.036 0.002 0.007 0.014 0.047 0.031 0.002 0.011 0.016
0.035 0.012 0.007 0.006 0.757 0.007 0.003 0.012 0.007 0.021 0.031 0.008 0.003 0.009 0.004 0.023 0.023 0.001 0.015 0.019
0.055 0.061 0.031 0.043 0.001 0.395 0.121 0.022 0.022 0.014 0.011 0.092 0.013 0.005 0.013 0.036 0.044 0.004 0.006 0.014
0.056 0.029 0.026 0.091 0.000 0.072 0.474 0.021 0.010 0.009 0.015 0.065 0.008 0.004 0.018 0.029 0.036 0.000 0.016 0.021
0.060 0.023 0.027 0.036 0.001 0.016 0.007 0.691 0.008 0.007 0.017 0.022 0.000 0.001 0.017 0.038 0.015 0.000 0.002 0.012
0.019 0.038 0.041 0.039 0.000 0.044 0.040 0.012 0.572 0.005 0.036 0.044 0.006 0.014 0.011 0.006 0.011 0.001 0.047 0.015
0.024 0.011 0.006 0.003 0.000 0.009 0.010 0.011 0.003 0.464 0.157 0.015 0.028 0.016 0.011 0.008 0.039 0.001 0.009 0.175
0.027 0.011 0.011 0.003 0.007 0.002 0.008 0.006 0.004 0.096 0.603 0.011 0.042 0.039 0.013 0.010 0.017 0.002 0.011 0.077
0.050 0.107 0.034 0.039 0.001 0.057 0.070 0.019 0.013 0.018 0.019 0.411 0.004 0.008 0.022 0.044 0.057 0.002 0.010 0.019
0.020 0.019 0.013 0.005 0.000 0.005 0.023 0.020 0.012 0.092 0.243 0.031 0.337 0.037 0.016 0.017 0.023 0.001 0.014 0.073
0.027 0.005 0.004 0.010 0.003 0.003 0.001 0.010 0.011 0.009 0.088 0.011 0.015 0.605 0.009 0.014 0.023 0.017 0.111 0.024
0.056 0.016 0.004 0.025 0.000 0.013 0.038 0.020 0.010 0.009 0.009 0.024 0.004 0.009 0.688 0.043 0.003 0.000 0.004 0.024
0.104 0.030 0.052 0.033 0.001 0.027 0.043 0.039 0.004 0.020 0.015 0.032 0.004 0.012 0.027 0.408 0.111 0.002 0.017 0.022
0.065 0.016 0.036 0.028 0.000 0.024 0.035 0.012 0.004 0.039 0.032 0.053 0.009 0.018 0.008 0.126 0.424 0.002 0.015 0.056
0.018 0.010 0.014 0.014 0.000 0.014 0.016 0.008 0.005 0.015 0.031 0.018 0.011 0.037 0.000 0.019 0.011 0.688 0.049 0.022
0.027 0.012 0.010 0.018 0.000 0.007 0.011 0.020 0.028 0.004 0.028 0.004 0.010 0.128 0.003 0.021 0.024 0.000 0.635 0.011
0.056 0.004 0.015 0.011 0.007 0.006 0.017 0.007 0.005 0.146 0.112 0.018 0.017 0.022 0.015 0.023 0.048 0.003 0.007 0.463
//
H BLAJ010101
D Matrix built from structural superposition data for identifying potential
remote homologues (Blake-Cohen, 2001)
R PMID:11254392
A Blake, J.D. and Cohen, F.E.
T Pairwise sequence alignment below the twilight zone
J J Mol Biol. 307, 721-735 (2001)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
9
0 14
0 1 11
0 -2 5 17
-5 -16 -13 -13 39
1 7 1 1 -14 13
0 3 1 5 -20 5 12
1 -2 1 2 -15 -3 0 16
-2 2 5 1 -18 2 0 -2 23
0 -7 -8 -9 -3 -7 -8 -3 -4 10
-2 -4 -7 -10 -11 -10 -8 -6 -4 7 10
0 7 2 0 -23 4 6 0 1 -7 -4 9
-2 -8 -6 -7 -9 -8 -6 -7 -5 10 11 -4 13
-1 -6 -3 -6 -12 -4 -10 -8 -1 3 3 -8 0 16
-1 -3 -1 2 -18 -4 -1 0 -4 -3 1 1 -4 -4 19
0 2 3 0 -18 0 0 0 0 -6 -4 1 -7 -4 1 9
-3 0 2 0 -19 2 3 -4 0 -3 -5 1 -3 -2 -1 5 7
-11 -6 -9 -7 -24 -12 -3 -10 -9 -6 2 -7 -4 9 -5 -7 0 32
-3 -1 1 -6 -1 -5 -5 -10 1 -2 -4 -5 -3 8 -8 -1 3 0 19
0 -4 -4 -10 0 -2 -6 -5 -6 8 6 -6 6 1 -4 -5 -1 -5 -1 9
//
H PRLA000101
D Structure derived matrix (SDM) for alignment of distantly related sequences
(Prlic et al., 2000)
R PMID:10964983
A Prlic, A., Domingues, F.S. and Sippl, M.J.
T Structure-derived substitution matrices for alignment of distantly
related sequences
J Protein Eng. 13, 545-550 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.09
-0.50 2.87
-0.57 0.60 3.60
-0.73 0.13 1.78 4.02
0.33 -1.30 -2.08 -2.51 6.99
-0.75 0.13 0.33 0.34 -0.83 2.60
-0.12 0.99 -0.16 1.20 -1.97 1.23 2.97
0.27 -0.96 0.79 -1.20 -2.11 -0.12 -0.41 4.36
-1.42 0.54 0.76 -0.01 -1.50 -0.46 -0.62 -0.40 5.89
-0.97 -1.40 -2.43 -2.77 0.13 -1.47 -1.81 -2.93 -1.76 2.76
-0.39 -1.19 -2.10 -2.65 -0.31 -1.49 -2.11 -1.98 -0.93 1.56 2.43
-0.38 1.42 0.83 0.66 -2.19 0.92 1.11 -0.71 0.31 -1.81 -1.96 2.91
-0.04 -0.63 -2.01 -2.58 1.04 -0.13 -1.86 -1.86 -1.04 0.99 1.61 -1.62 3.75
-0.76 -1.40 -2.25 -2.19 1.13 -2.31 -1.61 -2.67 -0.22 0.76 1.23 -2.41 0.80 3.28
-0.53 0.21 -1.10 0.72 -2.19 0.24 -0.26 -0.04 -1.44 -2.00 -1.56 -0.19 -1.09 -0.91 5.45
0.34 -0.06 0.40 0.71 0.31 1.04 0.31 0.29 -0.74 -1.75 -2.30 -0.06 -1.34 -1.11 -0.29 2.36
0.13 -0.15 0.30 -0.75 -0.59 0.60 -0.21 -0.81 -0.52 -0.96 -0.86 -0.10 -1.58 -0.69 0.93 1.20 2.04
-0.66 -0.04 -2.89 -1.91 -0.76 -0.81 -2.70 -1.21 -1.48 0.25 -0.14 -1.94 0.87 2.29 -5.34 -1.18 -0.57 6.96
-1.25 -0.75 -0.36 -1.21 0.13 -0.61 -1.64 -1.62 -0.12 0.08 0.70 -1.72 -0.41 1.96 -1.98 -1.56 -0.41 2.15 3.95
0.02 -1.52 -2.17 -2.02 0.34 -1.38 -1.84 -1.96 -0.35 1.94 0.81 -1.27 0.61 0.51 -1.11 -1.11 0.05 -1.09 0.21 2.05
//
H PRLA000102
D Homologous structure dereived matrix (HSDM) for alignment of distantly
related sequences (Prlic et al., 2000)
R PMID:10964983
A Prlic, A., Domingues, F.S. and Sippl, M.J.
T Structure-derived substitution matrices for alignment of distantly
related sequences
J Protein Eng. 13, 545-550 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5.50
-2.24 8.59
-1.77 0.24 10.00
-2.38 -0.33 4.07 11.01
0.45 -6.29 -6.53 -6.98 19.05
-2.16 -0.74 1.42 1.10 -2.47 7.85
-0.47 2.83 -0.39 2.41 -4.70 3.16 8.43
0.63 -3.39 1.16 -3.91 -5.70 -0.24 -1.80 11.64
-3.01 0.70 1.77 0.32 -5.95 -2.24 -1.29 -1.24 15.72
-1.72 -3.93 -5.78 -6.18 -0.13 -3.26 -5.89 -8.58 -4.44 6.74
-1.09 -2.83 -5.64 -7.41 -0.82 -4.56 -5.62 -6.55 -2.49 3.86 6.38
-1.22 3.89 1.64 1.53 -6.65 3.24 3.08 -1.82 -0.17 -4.82 -5.91 8.23
0.16 -1.43 -4.67 -7.88 3.50 -1.76 -3.94 -5.29 -3.66 2.94 4.32 -5.47 10.21
-2.42 -4.36 -6.22 -5.06 1.72 -5.54 -4.44 -7.46 0.25 2.30 3.90 -6.19 2.66 9.14
-1.11 1.31 -3.23 0.81 -6.70 1.30 -0.43 -1.79 -3.55 -4.04 -2.88 -1.21 -2.02 -2.96 13.32
1.27 -0.50 1.54 2.34 1.08 2.59 0.42 0.63 -2.38 -4.67 -6.22 -0.27 -3.92 -5.03 -1.28 6.35
0.60 0.34 1.14 -1.36 -1.89 1.08 -0.61 -2.24 -1.14 -3.03 -2.40 -0.37 -5.18 -4.00 2.44 3.09 6.33
-2.61 1.02 -6.29 -5.63 -3.01 -4.30 -6.28 -4.77 -5.71 -0.26 -0.58 -5.45 4.28 6.49 -11.46 -4.44 -3.55 18.08
-4.22 -1.01 -0.93 -3.85 -0.44 -1.73 -4.50 -4.34 1.17 -0.08 1.81 -4.03 -4.95 5.38 -7.41 -4.17 -2.92 6.79 10.92
0.16 -3.80 -5.65 -6.10 1.32 -4.97 -4.23 -5.32 -1.63 5.23 2.28 -3.57 1.18 0.52 -2.31 -2.69 -0.23 -2.13 0.66 5.28
//
H DOSZ010101
D Amino acid similarity matrix based on the sausage force
field (Dosztanyi-Torda, 2001)
R PMID:11524370
A Dosztanyi, Z. and Torda, A.E.
T Amino acid similarity matrices based on force fields
J Bioinformatics. 17, 686-699 (2001)
* #SM_SAUSAGE
* #Amino acid similarity matrix based on the sausage force field
* #Supplementary material
* #http://www.rsc.anu.edu.au/~zsuzsa/suppl/matrices/SM_SAUSAGE
* #Zsuzsanna Doszt?yi and Andrew E. Torda
* #Amino acid similarity matrices based on force fields
* #The amino acids are ordered according to the first principal component of the SM_SAUSAGE matrix.
* #The native cysteine residues were devided into two subsets depending on their covalent state.
* #Three rows correspond to cysteines: disulfide bonded (O), free cysteines (J) and all cysteines (C).
M rows = ARNDCQEGHILKMFPSTWYVJO, cols = ARNDCQEGHILKMFPSTWYV
15.4 -4.9 -8.1 -10.7 38.6 -7.4 -10.7 -6.0 0.2 23.0 20.9 -10.9 17.8 18.9 -9.3 -1.6 -5.2 17.6 18.9 23.7
6.4 -3.1 -5.3 -9.0 23.8 -6.5 -10.0 -8.3 -1.1 12.3 10.4 -7.9 9.6 9.8 -8.8 -2.1 -5.5 8.6 10.8 14.6
4.0 -6.1 -3.4 -4.8 23.5 -7.2 -9.2 -7.6 -1.9 8.6 7.1 -10.1 6.2 7.8 -8.7 -1.3 -5.2 6.4 9.5 11.5
4.1 -7.2 -2.7 0.2 22.2 -6.5 -6.0 -7.1 -2.7 5.3 4.8 -10.6 4.4 5.7 -8.2 -0.1 -4.9 4.6 8.0 8.1
19.2 -6.6 -7.0 -7.4 111.4 -6.3 -12.2 -3.0 11.4 31.0 27.4 -12.3 26.1 35.3 0.2 2.6 1.5 25.9 30.3 31.5
6.3 -4.8 -5.3 -6.8 24.0 -6.0 -8.3 -8.4 -1.4 11.2 10.0 -8.9 8.9 9.2 -9.0 -2.8 -6.1 8.3 10.4 13.1
5.3 -5.3 -4.5 -3.7 21.3 -5.8 -6.0 -7.7 -1.8 8.7 7.4 -9.1 6.7 7.4 -7.9 -2.3 -5.8 6.8 8.7 10.8
7.3 -8.2 -6.9 -8.4 30.7 -9.0 -10.8 1.2 -2.9 7.8 6.0 -11.6 7.1 8.8 -7.1 -1.5 -7.3 8.4 9.8 11.1
6.8 -6.0 -6.1 -8.0 30.5 -7.8 -10.7 -7.5 -0.7 14.1 11.8 -10.5 10.5 12.3 -8.2 -2.4 -5.7 9.8 13.2 16.1
12.7 -5.6 -11.3 -15.0 39.5 -9.0 -13.5 -12.7 0.6 35.7 29.5 -12.6 22.8 25.3 -8.9 -6.2 -4.7 21.3 24.1 35.5
13.0 -5.7 -10.1 -13.3 39.5 -8.2 -12.4 -11.5 0.9 31.9 27.8 -12.3 21.8 23.6 -9.2 -5.1 -5.3 20.1 22.3 31.1
5.3 -3.0 -4.4 -7.3 20.3 -5.7 -8.7 -7.3 -1.5 8.5 7.0 -6.7 7.2 7.0 -8.2 -1.7 -5.6 5.8 8.1 10.9
11.2 -5.6 -8.8 -11.6 36.3 -7.7 -11.4 -10.3 0.5 25.5 22.4 -11.2 18.8 19.4 -8.7 -4.2 -5.7 17.3 19.0 25.7
11.4 -6.5 -9.3 -11.9 39.2 -8.7 -12.5 -9.4 0.4 27.2 23.2 -12.2 18.9 21.5 -8.0 -4.1 -5.3 18.4 21.0 27.5
4.9 -7.8 -7.3 -7.5 26.7 -8.5 -10.0 -6.2 -1.2 12.5 9.1 -10.4 8.2 10.1 2.0 -2.1 -5.3 8.9 10.0 14.3
7.3 -5.9 -4.3 -4.9 28.2 -7.1 -9.3 -5.3 -1.6 8.8 7.9 -10.0 7.8 8.9 -7.1 3.0 -3.0 7.6 10.5 11.7
6.7 -5.4 -5.2 -7.0 27.1 -7.3 -10.1 -8.0 -1.5 13.6 10.9 -10.1 9.3 11.0 -7.3 0.8 -2.6 9.0 12.3 16.2
9.9 -6.9 -8.8 -10.7 37.4 -8.6 -11.7 -9.0 -0.3 23.2 19.7 -12.1 16.2 18.4 -7.4 -3.8 -5.5 17.0 19.1 23.8
10.2 -6.5 -8.6 -10.7 37.4 -8.4 -11.6 -8.8 -0.0 23.7 19.9 -11.7 16.6 19.1 -7.7 -3.9 -5.3 16.9 19.8 24.6
13.4 -5.4 -10.7 -14.8 41.3 -8.6 -13.4 -11.4 1.0 35.9 29.2 -12.6 23.0 26.0 -8.4 -5.5 -3.9 22.1 25.1 36.7
14.8 -7.1 -10.4 -13.9 48.4 -9.3 -13.4 -8.9 1.0 30.8 27.0 -13.5 23.1 25.1 -10.1 -3.1 -4.6 21.6 24.9 31.8
24.8 -4.6 -3.2 -1.4 166.7 -1.7 -10.1 4.6 20.6 31.6 28.3 -9.3 29.4 44.3 10.4 8.8 7.5 30.9 36.2 32.3
//
H DOSZ010102
D Normalised version of SM_SAUSAGE (Dosztanyi-Torda, 2001)
R PMID:11524370
A Dosztanyi, Z. and Torda, A.E.
T Amino acid similarity matrices based on force fields
J Bioinformatics. 17, 686-699 (2001)
* #SM_SAUS_NORM
* #Normalised version of SM_SAUSAGE
* #For each matrix element of SM_SAUSAGE, the average over its column and row were subtracted.
* #Supplementary material
* #http://www.rsc.anu.edu.au/~zsuzsa/suppl/matrices/SM_SAUS_NORM
* #Zsuzsanna Doszt?yi and Andrew E. Torda
* #Amino acid similarity matrices based on force fields
* #The amino acids are ordered according to the first principal component of the SM_SAUSAGE matrix.
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.56 -5.10 -7.00 -7.73 0.83 -5.75 -6.26 -4.00 -5.12 -1.42 -0.71 -6.17 -1.44 -1.90 -7.45 -5.11 -6.13 -1.22 -2.38 -2.26
-4.35 0.78 -0.16 -1.92 -9.95 -0.76 -1.47 -2.26 -2.33 -8.02 -7.13 0.93 -5.59 -6.89 -2.89 -1.52 -2.29 -6.20 -6.44 -7.30
-5.77 -1.19 2.69 3.20 -9.21 -0.47 0.31 -0.51 -2.20 -10.75 -9.48 -0.26 -8.00 -7.97 -1.81 0.24 -1.08 -7.43 -6.70 -9.36
-5.30 -1.93 3.82 8.58 -10.18 0.63 3.96 0.39 -2.59 -13.72 -11.35 -0.39 -9.45 -9.67 -0.94 1.79 -0.32 -8.82 -7.82 -12.42
-1.72 -8.93 -11.04 -12.59 8.91 -9.31 -10.67 -8.60 -5.98 4.64 3.68 -10.42 2.17 2.61 -10.05 -8.27 -7.21 1.05 1.86 4.11
-4.22 -0.66 0.14 0.51 -9.50 -0.05 0.50 -2.03 -2.34 -8.94 -7.32 0.13 -6.00 -7.28 -2.89 -1.96 -2.68 -6.16 -6.52 -8.49
-4.66 -0.60 1.40 4.09 -11.62 0.74 3.35 -0.89 -2.27 -10.89 -9.31 0.49 -7.69 -8.51 -1.29 -1.00 -1.81 -7.23 -7.74 -10.31
-2.72 -3.58 -1.07 -0.67 -2.34 -2.60 -1.59 7.98 -3.42 -11.80 -10.82 -2.10 -7.33 -7.17 -0.52 -0.24 -3.37 -5.61 -6.74 -10.01
-4.62 -2.70 -1.65 -1.56 -3.85 -2.73 -2.77 -2.09 -2.55 -6.88 -6.34 -2.36 -5.32 -5.02 -2.94 -2.48 -3.13 -5.59 -4.71 -6.44
-3.54 -7.10 -11.57 -13.36 0.31 -8.69 -10.38 -12.05 -6.06 9.92 6.53 -9.26 2.19 3.12 -8.48 -11.11 -6.99 1.12 1.50 8.16
-2.74 -6.81 -9.98 -11.26 0.73 -7.44 -8.85 -10.47 -5.34 6.58 5.26 -8.48 1.62 1.91 -8.38 -9.58 -7.08 0.30 0.07 4.19
-4.52 1.87 1.66 0.73 -12.46 0.93 0.77 -0.31 -1.81 -10.93 -9.60 3.01 -7.07 -8.79 -1.43 -0.17 -1.43 -8.02 -8.13 -10.05
-3.19 -5.33 -7.25 -8.13 -1.06 -5.56 -6.49 -7.84 -4.34 1.59 1.24 -5.99 -0.02 -0.91 -6.45 -7.27 -6.08 -1.10 -1.77 0.20
-3.42 -6.69 -8.26 -8.93 1.34 -7.06 -8.01 -7.42 -4.96 2.74 1.57 -7.53 -0.35 0.74 -6.23 -7.68 -6.23 -0.50 -0.36 1.52
-5.95 -3.94 -2.26 -0.52 -7.12 -2.87 -1.51 -0.20 -2.55 -7.90 -8.52 -1.66 -7.10 -6.65 7.75 -1.58 -2.20 -5.96 -7.30 -7.69
-3.67 -2.18 0.63 1.90 -5.80 -1.63 -0.97 0.58 -3.10 -11.75 -9.84 -1.38 -7.62 -8.02 -1.44 3.35 -0.07 -7.36 -6.95 -10.43
-4.77 -2.16 -0.75 -0.62 -7.27 -2.26 -2.25 -2.58 -3.43 -7.48 -7.34 -1.98 -6.61 -6.42 -2.08 0.71 -0.11 -6.41 -5.58 -6.35
-3.91 -6.07 -6.74 -6.70 0.60 -5.95 -6.26 -5.99 -4.57 -0.27 -0.92 -6.32 -2.01 -1.37 -4.55 -6.28 -5.42 -0.78 -1.14 -1.09
-3.88 -5.94 -6.73 -6.96 0.33 -5.99 -6.32 -6.07 -4.56 0.05 -0.99 -6.20 -1.90 -0.88 -5.16 -6.67 -5.43 -1.14 -0.77 -0.54
-3.35 -7.47 -11.62 -13.79 1.58 -8.92 -10.84 -11.38 -6.24 9.49 5.63 -9.80 1.76 3.32 -8.51 -10.91 -6.70 1.31 1.87 8.82
//
H DOSZ010103
D An amino acid similarity matrix based on the THREADER force field
(Dosztanyi-Torda, 2001)
R PMID:11524370
A Dosztanyi, Z. and Torda, A.E.
T Amino acid similarity matrices based on force fields
J Bioinformatics. 17, 686-699 (2001)
* #SM_THREADER
* #An amino acid similarity matrix based on the THREADER force field (Jones, DT et al.Nature, 358,86-89).
* #Supplementary material
* #http://www.rsc.anu.edu.au/~zsuzsa/suppl/matrices/SM_THREADER
* #Zsuzsanna Doszt?yi and Andrew E. Torda
* #Amino acid similarity matrices based on force fields
* #The amino acids are ordered according to the first principal component of the SM_SAUSAGE matrix.
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
10.0 -0.2 -1.2 -2.8 3.8 0.6 -1.0 0.9 0.2 5.1 4.5 -1.4 3.9 1.9 -0.9 1.8 1.6 0.5 1.8 5.5
2.3 8.1 -0.4 -1.6 -0.6 2.9 1.0 -1.9 1.8 0.5 1.8 3.6 1.7 0.4 -2.1 0.2 0.7 -0.5 1.7 1.0
1.5 0.3 6.4 1.9 -0.3 1.2 0.6 0.5 2.0 -0.4 -1.1 0.5 0.2 -1.9 -1.3 1.6 1.0 -2.4 -0.4 -0.6
0.7 -0.4 2.2 7.3 -2.3 1.5 2.7 -0.4 0.2 -1.6 -1.3 -0.1 -1.7 -3.0 -0.4 0.9 0.2 -3.4 -1.4 -1.8
2.7 -3.0 -2.4 -4.9 16.3 -2.4 -4.1 -1.6 -0.9 4.0 3.7 -4.2 2.2 2.7 -3.6 -0.4 0.5 -1.2 1.0 4.6
3.5 3.2 0.8 0.6 0.0 8.4 3.3 -1.0 2.7 1.2 2.6 3.1 3.4 -0.6 -0.2 1.3 0.8 1.2 1.6 0.7
3.0 2.2 0.8 2.4 -0.6 4.1 7.0 -1.9 1.6 -0.3 1.0 2.3 1.1 -0.4 -0.2 0.4 0.7 -1.0 0.2 0.2
2.0 -2.2 -0.1 -1.3 -1.0 -1.3 -3.0 7.8 -0.9 -1.2 -1.4 -2.2 -0.9 -1.9 -1.5 0.6 -0.9 -1.7 -1.3 -1.3
1.4 1.1 0.8 -1.4 0.4 1.8 -0.2 -1.0 9.9 0.5 1.4 -0.2 2.1 2.0 -1.6 -0.2 -0.4 -0.6 4.1 0.3
4.1 -2.9 -3.8 -5.9 4.8 -2.4 -5.7 -2.5 -1.2 13.2 9.8 -4.7 7.4 6.3 -3.1 -2.2 1.1 1.6 4.0 11.8
3.6 -1.4 -4.3 -5.4 4.2 -0.8 -3.9 -2.7 -0.4 9.7 12.5 -3.9 8.3 6.8 -3.8 -2.1 0.9 2.3 3.8 8.2
2.7 4.6 0.8 -0.3 -0.7 3.9 2.4 -1.0 1.6 0.4 0.8 6.5 1.0 -1.3 -0.2 1.2 0.6 -1.1 0.2 0.0
4.3 -0.4 -2.2 -4.9 3.6 1.2 -2.5 -1.7 1.3 8.7 9.7 -2.5 11.4 5.2 -2.8 -1.0 0.9 2.7 4.1 7.2
1.8 -2.0 -4.4 -6.3 3.8 -3.1 -4.3 -2.6 1.1 7.0 7.6 -5.1 4.8 12.4 -3.8 -2.2 -0.1 4.4 7.6 5.8
0.3 -2.1 -1.5 -0.8 -2.9 -0.4 -0.7 -1.2 -1.1 -1.5 -2.4 -0.9 -1.7 -2.7 8.7 -0.4 -0.2 -3.1 -1.9 -1.5
3.5 0.0 0.9 -0.3 1.3 0.9 -0.8 0.6 0.3 0.4 0.4 -0.1 0.6 -0.4 -0.6 4.9 2.8 -2.0 0.1 1.1
2.9 0.1 -0.1 -1.4 2.1 -0.0 -1.1 -1.0 -0.3 3.2 2.9 -1.1 2.0 1.1 -0.6 2.4 5.8 -0.7 0.7 3.9
1.5 -1.8 -4.2 -5.9 0.6 -0.3 -3.8 -2.0 -0.7 3.5 4.3 -3.9 3.5 5.5 -3.7 -3.0 -1.2 16.0 5.4 3.1
2.2 -0.1 -2.5 -4.2 2.4 -0.4 -3.1 -1.9 3.6 5.4 5.1 -3.0 4.3 8.2 -2.9 -1.3 -0.2 4.9 10.8 5.1
4.6 -2.2 -3.8 -5.9 5.4 -2.6 -4.9 -2.5 -1.4 11.9 8.4 -4.8 6.1 5.1 -3.0 -1.4 2.0 1.3 3.8 12.7
//
H DOSZ010104
D Normalised version of SM_THREADER (Dosztanyi-Torda, 2001)
R PMID:11524370
A Dosztanyi, Z. and Torda, A.E.
T Amino acid similarity matrices based on force fields
J Bioinformatics. 17, 686-699 (2001)
* #SM_THREAD_NORM
* #Normalised version of SM_THREADER
* #based on the THREADER force field (Jones, DT et al.Nature, 358,86-89)
* #For each matrix element of SM_THREADER, the average over its column and row were subtracted.
* #Supplementary material
* #http://www.rsc.anu.edu.au/~zsuzsa/suppl/matrices/SM_THREAD_NORM
* #Zsuzsanna Doszt?yi and Andrew E. Torda
* #Amino acid similarity matrices based on force fields
* #The amino acids are ordered according to the first principal component of the SM_SAUSAGE matrix.
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5.34 -2.01 -2.01 -2.43 0.01 -1.75 -1.66 -0.02 -2.48 -0.08 -0.70 -1.99 -0.84 -2.14 -1.29 0.01 -0.96 -2.08 -2.19 0.48
-1.67 7.03 -0.49 -0.60 -3.62 1.22 1.10 -2.07 -0.20 -3.98 -2.76 3.65 -2.34 -2.93 -1.78 -0.86 -1.15 -2.34 -1.64 -3.36
-1.90 -0.19 6.86 3.48 -2.83 0.13 1.27 0.93 0.53 -4.39 -5.08 1.17 -3.28 -4.64 -0.37 1.09 -0.27 -3.75 -3.14 -4.39
-2.11 -0.33 3.25 9.44 -4.24 0.92 3.93 0.59 -0.65 -4.98 -4.75 1.13 -4.55 -5.14 1.12 0.90 -0.56 -4.19 -3.58 -4.97
-0.65 -3.48 -1.98 -3.34 13.84 -3.45 -3.46 -1.20 -2.28 0.06 -0.27 -3.54 -1.22 -0.03 -2.65 -0.95 -0.79 -2.50 -1.78 0.87
-1.30 1.31 -0.14 0.78 -3.78 5.96 2.62 -1.93 -0.10 -4.13 -2.74 2.36 -1.42 -4.69 -0.67 -0.59 -1.87 -1.51 -2.55 -4.38
-1.02 0.98 0.60 3.37 -3.78 2.32 6.97 -2.17 -0.47 -4.95 -3.65 2.26 -2.97 -3.79 0.06 -0.76 -1.28 -3.04 -3.19 -4.26
-0.26 -1.56 1.55 1.48 -2.34 -1.25 -1.17 9.29 -1.15 -4.03 -4.21 -0.44 -3.19 -3.47 0.51 1.17 -1.03 -1.86 -2.90 -3.91
-2.56 0.01 0.68 -0.35 -2.57 0.11 -0.10 -1.19 7.89 -3.96 -3.16 -0.08 -1.90 -1.24 -1.20 -1.23 -2.21 -2.46 0.77 -4.03
-0.31 -4.43 -4.41 -5.36 1.30 -4.51 -6.08 -3.12 -3.69 8.26 4.84 -5.08 2.88 2.56 -3.16 -3.78 -1.20 -0.79 0.26 7.02
-0.88 -3.07 -4.99 -4.92 0.62 -3.02 -4.35 -3.46 -2.92 4.66 7.42 -4.37 3.75 2.96 -4.05 -3.72 -1.49 -0.14 -0.11 3.28
-1.38 3.49 0.60 0.70 -3.80 2.13 2.39 -1.25 -0.51 -4.23 -3.83 6.56 -3.10 -4.67 0.10 -0.01 -1.31 -3.05 -3.23 -4.37
-0.78 -2.55 -3.44 -4.93 -0.53 -1.56 -3.50 -2.97 -1.76 3.06 4.06 -3.56 6.28 0.83 -3.50 -3.15 -2.07 -0.25 -0.27 1.80
-2.29 -3.14 -4.59 -5.31 0.64 -4.86 -4.31 -2.90 -0.99 2.42 2.96 -5.13 0.69 8.98 -3.57 -3.35 -2.07 2.45 4.24 1.36
-1.73 -1.24 0.29 2.15 -3.99 -0.11 1.26 0.50 -1.21 -4.07 -4.99 1.11 -3.74 -4.08 11.00 0.46 -0.15 -3.03 -3.33 -3.88
-0.12 -0.69 1.10 1.03 -1.37 -0.44 -0.42 0.78 -1.31 -3.73 -3.79 0.30 -3.04 -3.34 0.06 4.20 1.29 -3.55 -2.88 -2.85
-1.04 -0.99 -0.21 -0.43 -0.96 -1.67 -1.06 -1.15 -2.26 -1.36 -1.66 -1.06 -2.03 -2.16 -0.27 1.33 3.91 -2.63 -2.66 -0.44
-2.06 -2.46 -3.91 -4.46 -2.06 -1.62 -3.37 -1.76 -2.37 -0.62 0.12 -3.41 -0.13 2.53 -2.97 -3.71 -2.67 14.53 2.44 -0.84
-2.32 -1.76 -3.17 -3.78 -1.25 -2.67 -3.59 -2.64 0.97 0.27 -0.02 -3.54 -0.32 4.28 -3.11 -2.98 -2.64 2.44 6.90 0.15
0.27 -3.71 -4.37 -5.30 1.94 -4.67 -5.26 -3.06 -3.82 7.00 3.43 -5.11 1.69 1.39 -3.05 -2.86 -0.24 -1.03 0.05 7.93
//
H GIAG010101
D Residue substitutions matrix from thermo/mesophilic to psychrophilic
enzymes (Gianese et al., 2001)
R PMID:11342709
A Gianese, G., Argos, P. and Pascarella, S.
T Structural adaptation of enzymes to low temperatures
J Protein Eng. 14, 141-148 (2001)
* (rows = WARM, cols = COLD)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.0 -2.4 0.5 -1.0 -0.4 -0.1 -5.7 1.8 -0.2 -0.8 0.5 -1.8 0.2 -0.2 -2.0 -0.4 0.9 -0.4 -0.4 -3.9
2.4 0.0 2.1 0.9 0.2 2.0 0.9 0.8 0.1 0.2 0.5 3.4 0.1 -0.5 0.5 2.2 1.3 0.2 0.2 0.7
-0.5 -2.1 0.0 -1.3 0.2 -0.8 -1.9 -0.4 -0.3 -0.2 -0.5 -2.4 -0.2 -0.4 -0.8 -1.3 -1.5 0.0 0.4 -0.9
1.0 -0.9 1.3 0.0 -0.2 -1.2 -2.7 -1.0 -0.2 0.0 -0.8 -0.7 0.1 -0.1 -0.6 -0.3 1.2 -0.2 -0.1 0.1
0.4 -0.2 -0.2 0.2 0.0 0.1 -0.3 -0.3 0.1 -0.1 0.2 0.0 0.0 0.0 0.0 0.0 -0.9 -0.1 0.1 -0.6
0.1 -2.0 0.8 1.2 -0.1 0.0 -1.5 -0.5 0.4 -0.5 -1.4 -1.9 0.5 -0.3 -0.3 0.1 0.7 -0.2 0.0 -0.8
5.7 -0.9 1.9 2.7 0.3 1.5 0.0 0.0 -0.4 0.5 -0.4 -1.7 0.4 -0.1 -0.7 2.7 2.2 -0.2 -0.1 -0.1
-1.8 -0.8 0.4 1.0 0.3 0.5 0.0 0.0 0.2 0.0 -0.1 -0.5 0.4 -0.5 -0.2 0.1 -0.1 -0.1 0.3 0.4
0.2 -0.1 0.3 0.2 -0.1 -0.4 0.4 -0.2 0.0 0.1 0.3 -0.4 0.0 -0.5 0.2 0.3 0.0 -0.3 -0.3 0.1
0.8 -0.2 0.2 0.0 0.1 0.5 -0.5 0.0 -0.1 0.0 -0.3 -0.6 1.3 -0.2 0.2 0.3 0.8 -0.5 0.0 -2.1
-0.5 -0.5 0.5 0.8 -0.2 1.4 0.4 0.1 -0.3 0.3 0.0 -0.7 0.2 -1.0 0.6 -0.1 -0.1 0.1 -0.7 0.1
1.8 -3.4 2.4 0.7 0.0 1.9 1.7 0.5 0.4 0.6 0.7 0.0 0.8 -0.7 0.1 2.6 1.4 0.0 0.1 1.1
-0.2 -0.1 0.2 -0.1 0.0 -0.5 -0.4 -0.4 0.0 -1.3 -0.2 -0.8 0.0 0.3 -0.2 -0.2 0.1 0.2 -0.1 -1.0
0.2 0.5 0.4 0.1 0.0 0.3 0.1 0.5 0.5 0.2 1.0 0.7 -0.3 0.0 0.0 0.5 -0.8 -0.7 0.5 0.3
2.0 -0.5 0.8 0.6 0.0 0.3 0.7 0.2 -0.2 -0.2 -0.6 -0.1 0.2 0.0 0.0 1.8 0.5 -0.1 0.1 0.2
0.4 -2.2 1.3 0.3 0.0 -0.1 -2.7 -0.1 -0.3 -0.3 0.1 -2.6 0.2 -0.5 -1.8 0.0 -1.6 -0.1 -0.1 0.0
-0.9 -1.3 1.5 -1.2 0.9 -0.7 -2.2 0.1 0.0 -0.8 0.1 -1.4 -0.1 0.8 -0.5 1.6 0.0 -0.4 0.4 -1.5
0.4 -0.2 0.0 0.2 0.1 0.2 0.2 0.1 0.3 0.5 -0.1 0.0 -0.2 0.7 0.1 0.1 0.4 0.0 -0.2 0.1
0.4 -0.2 -0.4 0.1 -0.1 0.0 0.1 -0.3 0.3 0.0 0.7 -0.1 0.1 -0.5 -0.1 0.1 -0.4 0.2 0.0 -0.1
3.9 -0.7 0.9 -0.1 0.6 0.8 0.1 -0.4 -0.1 2.1 -0.1 -1.1 1.0 -0.3 -0.2 0.0 1.5 -0.1 0.1 0.0
//
H DAYM780302
D Log odds matrix for 40 PAMs (Dayhoff et al., 1978)
R
A Dayhoff, M.O., Schwartz, R.M. and Orcutt, B.C.
T A model of evolutionary change in proteins
J In "Atlas of Protein Sequence and Structure", Vol.5, Suppl.3 (Dayhoff,
M.O., ed.), National Biomedical Research Foundation, Washington, D.C.,
p.352 (1978)
* #
* # This matrix was produced by "pam" Version 1.0.6 [28-Jul-93]
* #
* # PAM 40 substitution matrix, scale = ln(2)/2 = 0.346574
* #
* # Expected score = -4.27, Entropy = 2.26 bits
* #
* # Lowest score = -15, Highest score = 13
* #
M rows = ARNDCQEGHILKMFPSTWYV-, cols = ARNDCQEGHILKMFPSTWYV
6 -6 -3 -3 -6 -3 -2 -1 -6 -4 -5 -6 -4 -7 -1 0 0 -12 -7 -2
-6 8 -5 -9 -7 -1 -8 -8 -1 -5 -8 1 -3 -8 -3 -2 -5 -1 -9 -7
-3 -5 7 2 -9 -3 -1 -2 1 -4 -6 0 -7 -8 -5 0 -1 -7 -4 -7
-3 -9 2 7 -12 -2 3 -3 -3 -6 -11 -4 -9 -13 -7 -3 -4 -13 -10 -7
-6 -7 -9 -12 9 -12 -12 -8 -7 -5 -13 -12 -12 -11 -7 -2 -7 -14 -3 -5
-3 -1 -3 -2 -12 8 2 -6 1 -7 -4 -2 -3 -11 -2 -4 -5 -11 -10 -6
-2 -8 -1 3 -12 2 7 -3 -4 -5 -8 -4 -6 -12 -5 -4 -5 -15 -8 -6
-1 -8 -2 -3 -8 -6 -3 6 -8 -9 -9 -6 -7 -8 -5 -1 -5 -13 -12 -5
-6 -1 1 -3 -7 1 -4 -8 9 -8 -5 -5 -9 -5 -3 -5 -6 -6 -3 -6
-4 -5 -4 -6 -5 -7 -5 -9 -8 8 -1 -5 0 -2 -7 -6 -2 -12 -5 2
-5 -8 -6 -11 -13 -4 -8 -9 -5 -1 7 -7 1 -2 -6 -7 -6 -5 -6 -2
-6 1 0 -4 -12 -2 -4 -6 -5 -5 -7 6 -1 -12 -6 -3 -2 -10 -8 -8
-4 -3 -7 -9 -12 -3 -6 -7 -9 0 1 -1 11 -3 -7 -5 -3 -11 -10 -1
-7 -8 -8 -13 -11 -11 -12 -8 -5 -2 -2 -12 -3 9 -9 -6 -8 -4 2 -7
-1 -3 -5 -7 -7 -2 -5 -5 -3 -7 -6 -6 -7 -9 8 -1 -3 -12 -12 -5
0 -2 0 -3 -2 -4 -4 -1 -5 -6 -7 -3 -5 -6 -1 6 1 -4 -6 -5
0 -5 -1 -4 -7 -5 -5 -5 -6 -2 -6 -2 -3 -8 -3 1 7 -11 -6 -2
-12 -1 -7 -13 -14 -11 -15 -13 -6 -12 -5 -10 -11 -4 -12 -4 -11 13 -4 -14
-7 -9 -4 -10 -3 -10 -8 -12 -3 -5 -6 -8 -10 2 -12 -6 -6 -4 10 -6
-2 -7 -7 -7 -5 -6 -6 -5 -6 2 -2 -8 -1 -7 -5 -5 -2 -14 -6 7
-15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15 -15
//
H HENS920104
D BLOSUM50 substitution matrix (Henikoff-Henikoff, 1992)
R LIT:1902106 PMID:1438297
A Henikoff, S. and Henikoff, J.G.
T Amino acid substitution matrices from protein blocks
J Proc. Natl. Acad. Sci. USA 89, 10915-10919 (1992)
* # Matrix made by matblas from blosum50.iij
* # BLOSUM Clustered Scoring Matrix in 1/3 Bit Units
* # Blocks Database = /data/blocks_5.0/blocks.dat
* # Cluster Percentage: >= 50
* # Entropy = 0.4808, Expected = -0.3573
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5 -2 -1 -2 -1 -1 -1 0 -2 -1 -2 -1 -1 -3 -1 1 0 -3 -2 0
-2 7 -1 -2 -4 1 0 -3 0 -4 -3 3 -2 -3 -3 -1 -1 -3 -1 -3
-1 -1 7 2 -2 0 0 0 1 -3 -4 0 -2 -4 -2 1 0 -4 -2 -3
-2 -2 2 8 -4 0 2 -1 -1 -4 -4 -1 -4 -5 -1 0 -1 -5 -3 -4
-1 -4 -2 -4 13 -3 -3 -3 -3 -2 -2 -3 -2 -2 -4 -1 -1 -5 -3 -1
-1 1 0 0 -3 7 2 -2 1 -3 -2 2 0 -4 -1 0 -1 -1 -1 -3
-1 0 0 2 -3 2 6 -3 0 -4 -3 1 -2 -3 -1 -1 -1 -3 -2 -3
0 -3 0 -1 -3 -2 -3 8 -2 -4 -4 -2 -3 -4 -2 0 -2 -3 -3 -4
-2 0 1 -1 -3 1 0 -2 10 -4 -3 0 -1 -1 -2 -1 -2 -3 2 -4
-1 -4 -3 -4 -2 -3 -4 -4 -4 5 2 -3 2 0 -3 -3 -1 -3 -1 4
-2 -3 -4 -4 -2 -2 -3 -4 -3 2 5 -3 3 1 -4 -3 -1 -2 -1 1
-1 3 0 -1 -3 2 1 -2 0 -3 -3 6 -2 -4 -1 0 -1 -3 -2 -3
-1 -2 -2 -4 -2 0 -2 -3 -1 2 3 -2 7 0 -3 -2 -1 -1 0 1
-3 -3 -4 -5 -2 -4 -3 -4 -1 0 1 -4 0 8 -4 -3 -2 1 4 -1
-1 -3 -2 -1 -4 -1 -1 -2 -2 -3 -4 -1 -3 -4 10 -1 -1 -4 -3 -3
1 -1 1 0 -1 0 -1 0 -1 -3 -3 0 -2 -3 -1 5 2 -4 -2 -2
0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 2 5 -3 -2 0
-3 -3 -4 -5 -5 -1 -3 -3 -3 -3 -2 -3 -1 1 -4 -4 -3 15 2 -3
-2 -1 -2 -3 -3 -1 -2 -3 2 -1 -1 -2 0 4 -3 -2 -2 2 8 -1
0 -3 -3 -4 -1 -3 -3 -4 -4 4 1 -3 1 -1 -3 -2 0 -3 -1 5
//
H QUIB020101
D STROMA score matrix for the alignment of known distant homologs
(Qian-Goldstein, 2002)
R PMID:12211027
A Qian, B. and Goldstein, R.A.
T Optimization of a new score function for the generation of accurate
alignments
J Proteins. 48, 605-610 (2002)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.5
0.2 5.2
1.1 0.7 2.5
1 0.1 3.3 5.3
1.2 -1.3 -1.9 -3.1 11.5
-0.1 2 1.9 1.1 -2.5 3.6
1.2 1.9 2.3 3.2 -2.4 1.7 3.7
1.4 -0.2 0.7 0.9 -1.3 -0.3 0.5 7.5
-1.4 1.5 1.4 0.5 -1.7 1.4 0.3 -1.7 6.8
0.3 -1.9 -2.4 -2.9 -3.2 -0.9 -3.1 -3.7 -1.8 4.5
-0.2 -1.5 -2.4 -3.4 -1.6 -1.2 -1.5 -3.8 -2.4 3.4 5.2
-0.2 3.4 1.6 1.4 -3 2.2 1.2 0.4 1.1 -1.5 -2 3.9
-0.2 -1.4 -2.1 -2.8 -1.3 -0.6 -2 -3.8 -0.8 2.2 3.1 -0.5 5.4
-1.6 -3.2 -2.5 -3.7 -0.8 -1.7 -13.7 -4.7 -0.9 2.2 3.7 -2.8 1.7 7
0.7 -0.6 -0.1 -0.2 -3.6 1 0 -0.8 -2.1 -2.4 -1.4 0.2 -1.9 -4.1 8.1
1.7 0.2 1.4 1.7 0.7 0.9 1.1 1.6 -0.1 -1.1 -0.8 1.4 -1.1 -2.5 2 2.8
1.7 0.2 1.4 0.1 0.3 -0.1 1.6 -0.6 -0.2 0 0.3 1 -0.3 -0.8 1.1 2.6 0.4
-3.3 -1.5 -4 -5.7 -0.5 -2.9 -4.7 -4.2 -1.2 -1.8 -1.2 -3 -0.6 3.7 -5 -2.8 -2.9 14.9
-1.8 -0.9 -0.8 -2.9 -0.3 -1.5 -2.2 -4.8 2.9 0.2 0.8 -1.5 0.5 5.2 -3.3 -0.9 -0.8 4.9 8.1
1.9 -2.8 -0.9 -2.5 0.7 -1.5 -1.3 -1.4 -2.5 4.5 3.4 -1 1.7 0.9 -1.1 -3 1.5 -2.5 0.3 4.2
//
H NAOD960101
D Substitution matrix derived from the single residue interchanges at spatially
conserved regions of proteins (Naor et al., 1996)
R PMID:8601843
A Naor, D., Fischer, D., Jernigan, R.L., Wolfson, H.J. and Nussinov, R.
T Amino Acid Pair Interchanges at Spatially Conserved Locations (Naor et al)
J Journal of Molecular Biology 256, 924-938 (1996)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
4
0 7
0 4 8
0 4 8 11
2 -5 -5 -4 14
0 5 5 6 -4 7
0 8 6 7 -6 8 11
0 0 5 4 0 0 0 12
-1 3 2 3 -2 1 2 3 5
-2 -7 -9 -9 4 -7 -9 -7 -3 10
0 -5 -7 -8 2 -5 -6 -6 -3 7 9
0 9 6 7 -7 7 9 0 1 -9 -7 13
0 -2 -3 -4 2 -2 -2 -3 -1 3 5 -4 4
-1 -5 -6 -6 3 -5 -6 -3 -2 6 6 -7 3 6
0 1 6 6 -1 1 0 6 2 -8 -8 3 -6 -4 19
0 2 4 4 -3 2 3 4 2 -5 -5 3 -3 -4 3 5
0 1 2 2 -2 1 3 0 0 -3 -3 2 -2 -2 1 2 3
0 -3 -4 -4 0 -2 -3 -1 -1 4 2 -5 1 3 -5 -2 0 9
0 -2 -2 -3 0 -1 -2 -1 0 2 1 -3 1 2 -3 -1 0 2 3
-2 -6 -8 -9 4 -8 -9 -5 -2 9 5 -8 2 5 -5 -4 -1 4 2 9
//
H RUSR970101
D Substitution matrix based on structural alignments of analogous proteins
(Russell et al., 1997)
R PMID:9199410
A Russell, R.B., Saqi, M.A.S., Sayle, R.A., Bates, P.A. and Sternberg, M.J.E.
T Recognition of analogous and homologous protein folds: Analysis of sequence
and structure conservation
J Journal of Molecular Biology 269, 423-439 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-2
1 0
0 2 0
0 3 2 -2
2 -3 -4 0 12
1 -2 2 3 2 0
2 2 2 6 -8 6 -2
1 2 3 3 -1 -1 3 0
-1 2 7 2 5 0 -11 -5 -3
1 1 -4 -4 -1 1 -4 0 1 2
3 -2 0 -1 4 -2 -1 -2 3 3 -3
1 4 1 0 -1 3 2 2 2 -4 0 0
4 -5 -1 -1 3 -1 -3 1 3 1 8 1 -9
-1 5 1 -3 -1 -6 -4 -1 0 5 3 0 0 -3
2 1 0 3 -1 1 1 0 2 2 0 4 -17 4 -1
0 2 5 3 -5 0 2 4 1 -1 -1 0 -3 -2 5 -10
1 0 1 3 2 3 2 0 5 0 -3 -2 3 3 -1 4 0
-4 -5 -3 -4 1 -1 -1 0 2 2 4 3 0 11 2 0 3 5
1 3 -3 0 0 2 -2 1 3 3 3 0 4 0 -3 2 1 -12 -4
-1 -4 -1 -2 7 2 -3 -3 0 4 6 0 3 5 -1 1 0 2 3 -1
//
H RUSR970102
D Substitution matrix based on structural alignments of remote homolous proteins
(Russell et al., 1997)
R PMID:919941
A Russell, R.B., Saqi, M.A.S., Sayle, R.A., Bates, P.A. and Sternberg, M.J.E.
T Recognition of analogous and homologous protein folds: Analysis of sequence and
structure conservation
J Journal of Molecular Biology 269, 423-439 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0
0 4
0 0 3
-1 0 5 5
2 -1 0 -1 13
-1 3 2 3 -6 4
0 2 0 5 -4 2 3
1 0 1 1 -1 0 -1 6
-2 2 4 2 1 4 3 -1 11
0 0 -8 -7 1 -3 -3 -4 -4 1
0 -2 -2 -7 2 -5 -2 -4 0 7 2
1 6 1 1 0 4 4 0 1 -6 -4 2
0 0 -3 -6 1 0 -3 -3 1 5 6 -1 3
0 -3 -1 -6 3 -2 -5 -6 0 4 4 -4 4 5
0 -1 2 1 -1 0 2 0 1 -2 -5 0 -3 -1 7
2 0 3 2 -1 4 1 0 -4 -4 -2 0 -2 0 2 0
0 0 4 1 -2 -2 0 0 1 0 0 2 2 -2 1 4 0
-1 2 0 -5 2 -3 -2 -2 0 3 0 -2 3 4 -2 1 -4 16
0 2 0 -2 4 1 -1 -1 2 0 0 0 1 7 0 0 -1 8 3
1 -1 -3 -3 2 -1 -2 -2 -3 7 3 -2 3 3 0 -1 0 -2 1 0
//
H RUSR970103
D Substitution matrix based on structural alignments of analogous and remote homolous
proteins (Russell et al., 1997)
R PMID:9199410
A Russell, R.B., Saqi, M.A.S., Sayle, R.A., Bates, P.A. and Sternberg, M.J.E.
T Recognition of analogous and homologous protein folds: Analysis of sequence and
structure conservation
J Journal of Molecular Biology 269, 423-439 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-2
1 0
0 0 0
-1 0 1 0
2 -4 -1 0 12
0 1 3 3 -4 0
1 2 0 4 -8 4 0
0 1 2 2 0 0 1 1
0 3 3 3 2 0 -1 -3 1
1 1 -7 -3 -4 0 -3 -1 -1 0
2 -2 0 -3 2 -2 0 -2 2 5 0
1 3 0 2 2 4 3 1 3 -5 -2 -1
2 0 -3 -2 1 0 -1 0 3 4 6 0 -5
0 -1 1 -4 3 -3 -5 -3 0 4 4 -1 0 0
0 0 1 3 0 0 1 1 2 0 -2 1 0 1 0
0 0 4 2 -3 1 2 0 -1 -3 0 0 -4 0 5 -3
0 0 3 2 0 0 1 0 3 0 -1 1 2 0 1 3 -2
0 0 -1 -5 2 -1 -3 -1 0 4 1 0 3 5 2 2 0 7
0 3 0 -1 1 0 -1 0 1 2 0 0 1 5 -1 0 0 4 -1
0 0 0 -1 5 0 -2 -1 -1 5 4 0 1 3 -1 0 0 0 2 -2
//
H OGAK980101
D Substitution matrix derived from structural alignments by maximizing entropy
(Ogata et al., 1998)
R PMID:10522237
A Ogata, K., Ohya, M. and Umeyama, H.
T Amino acid similarity matrix for homology modeling derived from structural
alignment and optimized by the Monte Carlo method
J Journal of Molecular Graphics and Modelling 16, 178-254 (1998)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-4.8
-7.0 -6.2
-7.1 -7.3 -4.8
-6.9 -7.3 -6.3 -5.0
-7.7 -8.3 -8.6 -8.3 -3.2
-7.0 -7.5 -7.1 -7.3 -8.3 -6.5
-6.7 -7.5 -6.5 -6.4 -10.2 -6.8 -5.4
-5.8 -7.5 -6.8 -6.3 -7.5 -7.6 -7.4 -4.2
-7.7 -8.1 -6.8 -8.1 -9.3 -7.7 -7.8 -7.7 -6.1
-7.1 -7.7 -7.6 -8.3 -9.0 -7.9 -8.3 -8.0 -8.2 -5.5
-6.7 -7.9 -7.7 -7.1 -7.7 -7.4 -7.4 -8.0 -8.1 -5.5 -4.0
-6.7 -6.6 -6.8 -6.9 -8.5 -6.7 -6.7 -6.8 -7.6 -8.1 -7.2 -5.5
-8.0 -7.8 -7.4 -8.2 -8.7 -8.5 -8.1 -8.2 -9.7 -7.4 -7.0 -8.2 -6.7
-7.9 -8.1 -8.2 -9.5 -8.9 -8.6 -8.2 -8.1 -8.2 -7.2 -6.6 -8.8 -8.5 -5.7
-6.8 -7.9 -8.0 -7.3 -8.3 -8.1 -7.8 -7.2 -7.5 -7.2 -6.6 -7.5 -8.8 -8.8 -5.7
-5.6 -6.9 -6.5 -5.7 -8.2 -7.0 -6.6 -6.3 -7.0 -7.2 -6.4 -6.6 -7.5 -8.3 -6.8 -4.6
-6.2 -6.8 -6.4 -6.5 -7.5 -7.0 -6.8 -6.7 -8.0 -7.1 -6.2 -6.3 -7.3 -7.7 -6.7 -5.5 -5.0
-9.0 -9.4 -8.6 -9.8 -12.0 -8.3 -7.9 -7.2 -9.7 -7.7 -6.8 -9.5 -7.2 -6.9 -10.4 -7.6 -7.6 -5.0
-7.5 -8.4 -7.0 -7.2 -10.6 -7.3 -7.5 -7.5 -6.8 -7.4 -6.6 -7.3 -7.9 -6.0 -8.1 -7.3 -6.8 -6.5 -4.7
-5.9 -7.4 -7.2 -7.1 -8.1 -7.5 -7.3 -7.3 -7.5 -5.7 -5.8 -6.7 -7.2 -7.1 -7.5 -6.8 -6.2 -7.8 -7.2 -4.8
//
H KANM000101
D Substitution matrix (OPTIMA) derived by maximizing discrimination between
homologs and non-homologs (Kann et al., 2000)
R PMID:11056037
A Kann, M., Qian, B. and Goldstein, R.A.
T Optimization of a new score function for the detection of remote homologs
J Proteins: Structure, Function, and Genetics 41, 498-503 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
36
-9 56
-19 4 59
-20 -18 18 65
6 -29 -30 -30 99
-3 12 2 2 -30 46
-10 3 3 20 -39 19 40
4 -18 7 -10 -29 -20 -23 67
-19 3 12 -7 -29 3 2 -18 86
-5 -28 -32 -34 -6 -30 -33 -41 -28 35
-7 -20 -32 -43 -6 -23 -31 -42 -27 28 32
-10 31 1 -4 -29 15 14 -18 -7 -31 -21 37
-9 -10 -19 -30 -8 1 -21 -30 -19 12 24 -12 51
-19 -30 -29 -33 -18 -29 -32 -32 -8 8 17 -29 2 57
-5 -18 -17 -7 -30 -11 -7 -18 -18 -30 -33 -10 -21 -39 74
12 -11 10 4 -10 0 -1 2 -9 -20 -22 3 -10 -19 -8 36
0 -8 0 -10 -7 -7 -6 -17 -20 -8 -13 -8 -7 -18 -11 18 48
-29 -29 -39 -40 -18 -19 -29 -19 -18 -28 -15 -30 -8 14 -38 -29 -19 110
-19 -15 -19 -20 -18 -9 -21 -29 20 -8 -2 -17 -9 37 -28 -19 -17 22 69
6 -32 -31 -31 -6 -19 -28 -30 -29 35 18 -23 10 0 -18 -22 6 -28 -9 38
//
H NGPC000101
D Substitution matrix (PHAT) built from hydrophobic and transmembrane regions
of the Blocks database (Ng et al., 2000)
R PMID:11108698
A Ng, P.C., Henikoff, J.G. and Henikoff, S.
T PHAT: a transmembrane-specific substitution matrix
J Bioinformatics 16, 760-766 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5
-6 9
-2 -3 11
-5 -7 2 12
1 -8 -2 -7 7
-3 -2 2 0 -5 9
-5 -6 0 6 -7 1 12
1 -5 -1 -2 -2 -2 -3 9
-3 -4 4 -1 -7 2 -1 -4 11
0 -6 -3 -5 -3 -3 -5 -2 -5 5
-1 -6 -3 -5 -2 -3 -5 -2 -4 2 4
-7 -1 -2 -5 -10 -1 -4 -5 -5 -7 -7 5
-1 -6 -2 -5 -2 -1 -5 -1 -4 3 2 -6 6
-1 -7 -1 -5 0 -2 -5 -2 -2 0 1 -7 0 6
-3 -7 -4 -5 -8 -3 -5 -3 -6 -4 -5 -4 -5 -5 13
2 -6 1 -4 1 -1 -3 1 -2 -2 -2 -5 -2 -2 -3 6
0 -6 -1 -5 -1 -3 -5 -1 -4 -1 -1 -6 0 -2 -4 1 3
-4 -7 -5 -7 -4 1 -7 -5 -3 -4 -3 -8 -4 0 -6 -5 -7 11
-3 -6 2 -4 -1 0 -2 -3 3 -3 -2 -4 -2 4 -5 -2 -3 1 11
1 -7 -3 -5 -2 -3 -5 -2 -5 3 1 -8 1 -1 -4 -2 0 -4 -3 4
//
H MUET010101
D Non-symmetric substitution matrix (SLIM) for detection of homologous
transmembrane proteins (Mueller et al., 2001)
R PMID:11473008
A Mueller, T., Rahmann, S. and Rehmsmeier, M.
T Non-symmetric score matrices and the detection of homologous transmembrane
proteins
J Bioinformatics 17 Suppl 1, S182-S189 (2001)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5.0
-5.5 10.0
-3.0 -4.5 8.0
-6.5 -9.5 -0.5 9.0
2.5 -5.0 -2.5 -7.5 11.0
-4.0 -2.5 -1.0 -2.5 -3.5 7.0
-7.0 -9.0 -4.5 2.0 -7.0 -2.5 7.0
0.5 -5.5 -3.0 -4.5 -1.5 -3.5 -6.5 7.0
-3.0 -4.5 2.5 -3.5 -5.0 -0.5 -3.0 -5.5 10.0
0.0 -5.5 -4.0 -6.5 -0.5 -3.5 -7.0 -2.5 -4.0 6.0
0.0 -4.5 -3.5 -6.0 1.0 -3.5 -7.0 -2.0 -4.0 3.5 5.0
-5.5 -0.5 -3.5 -5.0 -7.0 -2.0 -7.5 -4.5 -5.5 -5.5 -6.0 6.0
0.0 -4.0 -3.0 -6.0 1.0 -1.5 -6.0 -1.5 -4.0 4.0 4.0 -5.5 7.0
0.0 -5.5 -2.0 -5.5 2.5 -2.0 -5.5 -1.0 -1.0 1.5 2.5 -5.5 2.5 8.0
-4.0 -8.0 -6.0 -7.0 -9.0 -6.0 -7.0 -4.5 -8.0 -4.0 -5.0 -4.5 -5.0 -4.5 11.0
2.0 -6.0 0.5 -5.5 3.0 -2.5 -5.0 0.5 -2.5 -1.5 -1.5 -5.0 -1.0 -0.5 -4.0 6.0
1.5 -5.0 -1.5 -5.5 1.0 -3.5 -6.5 -1.5 -3.5 0.5 0.5 -5.0 1.5 0.0 -3.5 1.5 4.0
-2.5 -4.5 -4.0 -6.5 -0.5 1.0 -6.0 -4.0 -1.0 -1.5 -0.5 -5.5 -0.5 3.5 -4.5 -3.0 -4.5 15.0
-3.5 -5.5 0.0 -5.5 0.5 -2.0 -5.5 -3.5 2.5 -2.5 -1.5 -3.5 -1.5 5.0 -5.5 -2.0 -2.5 2.0 11.0
1.5 -6.0 -4.5 -6.0 1.0 -3.5 -6.5 -2.5 -4.5 4.5 2.5 -7.0 2.5 1.0 -4.0 -1.0 1.0 -2.0 -2.5 5.0
//
H MUET020101
D Substitution matrix (VTML160) obtained by maximum likelihood estimation
(Mueller et al., 2002)
R PMID:11752185
A Mueller, T., Spang, R. and Vingron, M.
T Estimating amino acid substitution models: A comparison of Dayhoff's
estimator, the resolvent approach and a maximum likelihood method
J Molecular Biology and Evolution 19, 8-13 (2002)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5
-2 7
-1 0 7
-1 -3 3 7
1 -3 -3 -5 13
-1 2 0 1 -4 6
-1 -1 0 3 -5 2 6
0 -3 0 -1 -2 -3 -2 8
-2 1 1 0 -2 2 -1 -3 9
-1 -4 -4 -6 -1 -4 -5 -7 -4 6
-2 -3 -4 -6 -4 -2 -4 -6 -3 3 6
-1 4 0 0 -4 2 1 -2 0 -4 -3 5
-1 -2 -3 -5 -1 -1 -3 -5 -3 2 4 -2 8
-3 -5 -5 -7 -4 -4 -6 -6 0 0 2 -5 1 9
0 -2 -2 -1 -3 -1 -1 -3 -2 -4 -3 -1 -4 -5 9
1 -1 1 0 1 0 0 0 -1 -3 -3 -1 -3 -3 0 4
1 -1 0 -1 0 -1 -1 -2 -1 -1 -2 -1 -1 -3 -1 2 5
-5 -4 -5 -7 -7 -6 -7 -5 -1 -2 -1 -5 -4 3 -5 -4 -6 16
-3 -3 -2 -5 -1 -4 -3 -5 3 -2 -1 -3 -2 6 -6 -2 -3 4 10
0 -4 -4 -4 1 -3 -3 -5 -3 4 2 -3 1 -1 -3 -2 0 -5 -3 5
//
H MUET020102
D Substitution matrix (VTML250) obtained by maximum likelihood estimation
(Mueller et al., 2002)
R 11752185
A Mueller, T., Spang, R. and Vingron, M.
T Estimating amino acid substitution models: A comparison of Dayhoff's
estimator, the resolvent approach and a maximum likelihood method
J Molecular Biology and Evolution 19, 8-13 (2002)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2
-1 5
0 0 4
0 -1 2 5
1 -2 -1 -3 11
0 2 1 1 -2 3
0 0 1 3 -3 2 4
1 -1 0 0 -1 -1 -1 7
-1 1 1 0 -1 1 0 -1 6
-1 -2 -3 -4 0 -2 -3 -4 -2 4
-1 -2 -3 -4 -2 -2 -3 -4 -2 3 4
-1 3 1 0 -2 2 1 -1 0 -2 -2 3
-1 -1 -2 -3 0 -1 -2 -3 -2 2 3 -1 4
-2 -3 -3 -5 -2 -2 -4 -4 0 1 2 -3 1 7
0 -1 -1 0 -2 0 0 -1 -1 -3 -2 0 -2 -3 7
1 0 1 0 1 0 0 0 0 -2 -2 0 -1 -2 0 2
1 -1 0 0 0 0 0 -1 0 0 -1 0 0 -2 0 1 3
-3 -3 -4 -5 -4 -4 -5 -4 0 -1 0 -3 -2 3 -3 -3 -4 14
-2 -2 -1 -3 0 -2 -2 -4 2 -1 0 -2 -1 5 -4 -1 -2 4 8
0 -2 -2 -3 1 -2 -2 -3 -2 3 2 -2 2 0 -2 -1 0 -3 -1 3
//
H CROG050101
D Substitution matrix computed from the Dirichlet Mixture Model
(Crooks-Brenner, 2005)
R PMID:15531614
A Crooks, G.E. and Brenner, S.E.
T An alternative model of amino acid replacement
J Bioinformatics 21, 975-980 (2005)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
4
-2 6
-2 -1 7
-2 -1 1 7
0 -4 -3 -4 12
-1 1 0 0 -3 6
-1 0 0 1 -4 1 5
-1 -3 -1 -1 -3 -2 -2 7
-2 0 0 -1 -3 0 -1 -2 9
-2 -3 -5 -6 -1 -3 -4 -6 -3 5
-2 -3 -4 -5 -2 -3 -4 -5 -3 2 5
-2 2 0 0 -4 1 1 -2 -1 -4 -3 5
-1 -2 -3 -4 -1 -2 -3 -4 -2 1 2 -2 7
-2 -3 -4 -5 -2 -3 -4 -5 -1 0 1 -4 1 7
-1 -2 -2 -1 -3 -1 -1 -2 -2 -4 -3 -1 -3 -3 8
0 -1 0 0 -2 0 -1 -1 -1 -4 -3 -1 -2 -3 -1 4
-1 -1 -1 -1 -1 -1 -1 -2 -1 -2 -2 -1 -1 -2 -2 1 5
-3 -2 -3 -4 -2 -2 -3 -4 0 -1 -1 -3 0 3 -3 -3 -2 12
-2 -2 -2 -3 -2 -2 -3 -4 0 -1 -1 -3 0 3 -3 -2 -2 3 8
-1 -3 -4 -5 0 -3 -4 -5 -3 3 1 -3 1 0 -3 -3 -1 -2 -2 5
//
