Difference between revisions of "Chou-Fasman"
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| − | The ''Chou-Fasman'' method of secondary structure prediction depends on assigning a set of prediction values to a residue and then applying a simple algorithm to those numbers.<ref name="Prevelige1989">Prevelige, Jr P, Fasman GD (1989). "Chou-Fasman Prediction of Secondary Structure, in Prediction of Protein Structure and the Principles of Protein Conformation", Plenum, New York (ed. G. B. Fasman). ISBN 0-306-43131-9.</ref> | + | The ''Chou-Fasman'' method of secondary structure prediction depends on assigning a set of prediction values to a residue and then applying a simple algorithm to those numbers.<ref name="Chou_predict0">Chou PY, Fasman GD. (1974). Prediction of protein conformation. ''Biochemistry.'' 13(2):222-45.</ref><ref name="Chou_predict1">Chou PY, Fasman GD. (1978). Empirical predictions of protein conformation. ''Annu Rev Biochem'' 47:251-76. </ref><ref name="Chou_predict2">Chou PY, Fasman GD. (1978). Prediction of the secondary structure of proteins from their amino acid sequence. ''Adv Enzymol Relat Areas Mol Biol.'' 47:45-148. </ref><ref name="Prevelige1989">Prevelige, Jr P, Fasman GD (1989). "Chou-Fasman Prediction of Secondary Structure, in Prediction of Protein Structure and the Principles of Protein Conformation", Plenum, New York (ed. G. B. Fasman). ISBN 0-306-43131-9.</ref> It is no longer used as a reliable prediction algorithm.<ref name="Kyngas">Kyngas J, Valjakka J. (1998). Unreliability of the Chou-Fasman parameters in predicting protein secondary structure. ''Protein Eng'' 11(5):345-8. PMID 9681866.</ref> The original parameters have been updated from a current dataset, along with modifications to the initial algorithm.<ref name="Chen">Chen H, Gu F, Huang Z. (2006). Improved Chou-Fasman method for protein secondary structure prediction. ''BMC Bioinformatics'' 7(Suppl 4):S14.</ref> |
==Chou-Fasman table== | ==Chou-Fasman table== | ||
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| − | ! colspan="8" bgcolor="#EFEFEF" | '''Chou-Fasman''' | + | ! colspan="8" bgcolor="#EFEFEF" | '''Chou-Fasman'''<ref name="Chou_param">Chou PY, Fasman GD. (1974). Conformational parameters for amino acids in helical, beta-sheet, and random coil regions calculated from proteins. ''Biochemistry'' 13(2):211-22.</ref> |
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==External links== | ==External links== | ||
*[http://swift.cmbi.kun.nl/swift/future/aainfo/contents.htm Amino Acid Information] | *[http://swift.cmbi.kun.nl/swift/future/aainfo/contents.htm Amino Acid Information] | ||
| + | *[[wikipedia:Chou-Fasman method]] | ||
[[Category:Bioinformatics]] | [[Category:Bioinformatics]] | ||
Revision as of 04:29, 24 April 2007
The Chou-Fasman method of secondary structure prediction depends on assigning a set of prediction values to a residue and then applying a simple algorithm to those numbers.[1][2][3][4] It is no longer used as a reliable prediction algorithm.[5] The original parameters have been updated from a current dataset, along with modifications to the initial algorithm.[6]
Chou-Fasman table
| Chou-Fasman[7] | |||||||
|---|---|---|---|---|---|---|---|
| Name | P(a) | P(b) | P(turn) | f(i) | f(i+1) | f(i+2) | f(i+3) |
| Alanine | 142 | 83 | 66 | 0.06 | 0.076 | 0.035 | 0.058 |
| Arginine | 98 | 93 | 95 | 0.070 | 0.106 | 0.099 | 0.085 |
| Aspartic Acid | 101 | 54 | 146 | 0.147 | 0.110 | 0.179 | 0.081 |
| Asparagine | 67 | 89 | 156 | 0.161 | 0.083 | 0.191 | 0.091 |
| Cysteine | 70 | 119 | 119 | 0.149 | 0.050 | 0.117 | 0.128 |
| Glutamic Acid | 151 | 037 | 74 | 0.056 | 0.060 | 0.077 | 0.064 |
| Glutamine | 111 | 110 | 98 | 0.074 | 0.098 | 0.037 | 0.098 |
| Glycine | 57 | 75 | 156 | 0.102 | 0.085 | 0.190 | 0.152 |
| Histidine | 100 | 87 | 95 | 0.140 | 0.047 | 0.093 | 0.054 |
| Isoleucine | 108 | 160 | 47 | 0.043 | 0.034 | 0.013 | 0.056 |
| Leucine | 121 | 130 | 59 | 0.061 | 0.025 | 0.036 | 0.070 |
| Lysine | 114 | 74 | 101 | 0.055 | 0.115 | 0.072 | 0.095 |
| Methionine | 145 | 105 | 60 | 0.068 | 0.082 | 0.014 | 0.055 |
| Phenylalanine | 113 | 138 | 60 | 0.059 | 0.041 | 0.065 | 0.065 |
| Proline | 57 | 55 | 152 | 0.102 | 0.301 | 0.034 | 0.068 |
| Serine | 77 | 75 | 143 | 0.120 | 0.139 | 0.125 | 0.106 |
| Threonine | 83 | 119 | 96 | 0.086 | 0.108 | 0.065 | 0.079 |
| Tryptophan | 108 | 137 | 96 | 0.077 | 0.013 | 0.064 | 0.167 |
| Tyrosine | 69 | 147 | 114 | 0.082 | 0.065 | 0.114 | 0.125 |
| Valine | 106 | 170 | 50 | 0.062 | 0.048 | 0.028 | 0.053 |
Algorithm
Contains the following steps:
- Assign all of the residues in the peptide the appropriate set of parameters.
- Scan through the peptide and identify regions where 4 out of 6 contiguous residues have
P(a-helix) > 100. That region is declared an alpha-helix. Extend the helix in both directions until a set of four contiguous residues that have an averageP(a-helix) < 100is reached. That is declared the end of the helix. If the segment defined by this procedure is longer than 5 residues and the averageP(a-helix) > P(b-sheet)for that segment, the segment can be assigned as a helix. - Repeat this procedure to locate all of the helical regions in the sequence.
- Scan through the peptide and identify a region where 3 out of 5 of the residues have a value of
P(b-sheet) > 100. That region is declared as a beta-sheet. Extend the sheet in both directions until a set of four contiguous residues that have an averageP(b-sheet) < 100is reached. That is declared the end of the beta-sheet. Any segment of the region located by this procedure is assigned as a beta-sheet if the averageP(b-sheet) > 105and the averageP(b-sheet) > P(a-helix)for that region. - Any region containing overlapping alpha-helical and beta-sheet assignments are taken to be helical if the average
P(a-helix) > P(b-sheet)for that region. It is a beta sheet if the averageP(b-sheet) > P(a-helix)for that region. - To identify a bend at residue number
j, calculate the following value:
p(t) = f(j)f(j+1)f(j+2)f(j+3)
where the f(j+1) value for the j+1 residue is used, the f(j+2) value for the j+2 residue is used and the f(j+3) value for the j+3 residue is used. If:
- (1)
p(t) > 0.000075; - (2) the average value for
P(turn) > 1.00in the tetrapeptide; and - (3) the averages for the tetrapeptide obey the inequality
P(a-helix) < P(turn) > P(b-sheet), then a beta-turn is predicted at that location.
References
- ↑ Chou PY, Fasman GD. (1974). Prediction of protein conformation. Biochemistry. 13(2):222-45.
- ↑ Chou PY, Fasman GD. (1978). Empirical predictions of protein conformation. Annu Rev Biochem 47:251-76.
- ↑ Chou PY, Fasman GD. (1978). Prediction of the secondary structure of proteins from their amino acid sequence. Adv Enzymol Relat Areas Mol Biol. 47:45-148.
- ↑ Prevelige, Jr P, Fasman GD (1989). "Chou-Fasman Prediction of Secondary Structure, in Prediction of Protein Structure and the Principles of Protein Conformation", Plenum, New York (ed. G. B. Fasman). ISBN 0-306-43131-9.
- ↑ Kyngas J, Valjakka J. (1998). Unreliability of the Chou-Fasman parameters in predicting protein secondary structure. Protein Eng 11(5):345-8. PMID 9681866.
- ↑ Chen H, Gu F, Huang Z. (2006). Improved Chou-Fasman method for protein secondary structure prediction. BMC Bioinformatics 7(Suppl 4):S14.
- ↑ Chou PY, Fasman GD. (1974). Conformational parameters for amino acids in helical, beta-sheet, and random coil regions calculated from proteins. Biochemistry 13(2):211-22.
