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="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>
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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="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'''<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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! 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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Latest revision as of 04:32, 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:

  1. Assign all of the residues in the peptide the appropriate set of parameters.
  2. 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 average P(a-helix) < 100 is reached. That is declared the end of the helix. If the segment defined by this procedure is longer than 5 residues and the average P(a-helix) > P(b-sheet) for that segment, the segment can be assigned as a helix.
  3. Repeat this procedure to locate all of the helical regions in the sequence.
  4. 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 average P(b-sheet) < 100 is 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 average P(b-sheet) > 105 and the average P(b-sheet) > P(a-helix) for that region.
  5. 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 average P(b-sheet) > P(a-helix) for that region.
  6. 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) > 1.00 in 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

  1. Chou PY, Fasman GD (1974). "Prediction of protein conformation". Biochemistry, 13(2):222-45.
  2. Chou PY, Fasman GD (1978). "Empirical predictions of protein conformation". Annu Rev Biochem, 47:251-76.
  3. 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.
  4. 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.
  5. Kyngas J, Valjakka J (1998). "Unreliability of the Chou-Fasman parameters in predicting protein secondary structure". Protein Eng, 11(5):345-8. PMID 9681866.
  6. Chen H, Gu F, Huang Z (2006). "Improved Chou-Fasman method for protein secondary structure prediction". BMC Bioinformatics, 7(Suppl 4):S14.
  7. 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.

External links