Chou-Fasman - Revision history

Christoph at 04:32, 24 April 2007

2007-04-24T04:32:14Z

Christoph at 04:29, 24 April 2007

2007-04-24T04:29:09Z

Christoph: /* Algorithm */

2007-04-24T04:23:32Z

‎Algorithm

Christoph: /* Chou-Fasman table */

2007-04-21T01:54:22Z

‎Chou-Fasman table

Christoph at 07:32, 20 April 2007

2007-04-20T07:32:08Z

Christoph at 07:31, 20 April 2007

2007-04-20T07:31:14Z

New page

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>

==Chou-Fasman table==
<div style="float:left; margin:0px 0px 0px 0px;">
{| align="center" style="border: 1px solid #999; background-color:#FFFFFF"
|-
! colspan="8" bgcolor="#EFEFEF" | '''Chou-Fasman'''
|--align="center" style="background-color:#1188ee; color:#ffffff;"
!Name
!P(a)
!P(b)
!P(turn)
!f(i)
!f(i+1)
!f(i+2)
!f(i+3)
|-align="right"
|align="left"|Alanine || 142 || 83 || 66 || 0.06 || 0.076 || 0.035 || 0.058
|--align="right" bgcolor="#eee"
|align="left"|Arginine || 98 || 93 || 95 || 0.070 || 0.106 || 0.099 || 0.085
|-align="right"
|align="left"|Aspartic Acid || 101 || 54 || 146 || 0.147 || 0.110 || 0.179 || 0.081
|--align="right" bgcolor="#eee"
|align="left"|Asparagine || 67 || 89 || 156 || 0.161 || 0.083 || 0.191 || 0.091
|-align="right"
|align="left"|Cysteine || 70 || 119 || 119 || 0.149 || 0.050 || 0.117 || 0.128
|--align="right" bgcolor="#eee"
|align="left"|Glutamic Acid || 151 || 037 || 74 || 0.056 || 0.060 || 0.077 || 0.064
|-align="right"
|align="left"|Glutamine || 111 || 110 || 98 || 0.074 || 0.098 || 0.037 || 0.098
|--align="right" bgcolor="#eee"
|align="left"|Glycine || 57 || 75 || 156 || 0.102 || 0.085 || 0.190 || 0.152
|-align="right"
|align="left"|Histidine || 100 || 87 || 95 || 0.140 || 0.047 || 0.093 || 0.054
|--align="right" bgcolor="#eee"
|align="left"|Isoleucine || 108 || 160 || 47 || 0.043 || 0.034 || 0.013 || 0.056
|-align="right"
|align="left"|Leucine || 121 || 130 || 59 || 0.061 || 0.025 || 0.036 || 0.070
|--align="right" bgcolor="#eee"
|align="left"|Lysine || 114 || 74 || 101 || 0.055 || 0.115 || 0.072 || 0.095
|-align="right"
|align="left"|Methionine || 145 || 105 || 60 || 0.068 || 0.082 || 0.014 || 0.055
|--align="right" bgcolor="#eee"
|align="left"|Phenylalanine || 113 || 138 || 60 || 0.059 || 0.041 || 0.065 || 0.065
|-align="right"
|align="left"|Proline || 57 || 55 || 152 || 0.102 || 0.301 || 0.034 || 0.068
|--align="right" bgcolor="#eee"
|align="left"|Serine || 77 || 75 || 143 || 0.120 || 0.139 || 0.125 || 0.106
|-align="right"
|align="left"|Threonine || 83 || 119 || 96 || 0.086 || 0.108 || 0.065 || 0.079
|--align="right" bgcolor="#eee"
|align="left"|Tryptophan || 108 || 137 || 96 || 0.077 || 0.013 || 0.064 || 0.167
|-align="right"
|align="left"|Tyrosine || 69 || 147 || 114 || 0.082 || 0.065 || 0.114 || 0.125
|--align="right" bgcolor="#eee"
|align="left"|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 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.
#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 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.
#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.
#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==
<references/>

[[Category:Bioinformatics]]

@@ Line 1: / Line 1: @@
-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>
+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==
@@ Line 5: / Line 5: @@
 {| align="center" style="border: 1px solid #999; background-color:#FFFFFF"
 |-
-! 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>
+! 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>
 |--align="center" style="background-color:#1188ee; color:#000;"
 !Name

@@ Line 1: / Line 1: @@
-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==
@@ Line 5: / Line 5: @@
 {| align="center" style="border: 1px solid #999; background-color:#FFFFFF"
 |-
-! 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>
 |--align="center" style="background-color:#1188ee; color:#000;"
 !Name
@@ Line 75: / Line 75: @@
 ==External links==
 *[http://swift.cmbi.kun.nl/swift/future/aainfo/contents.htm Amino Acid Information]
 [[Category:Bioinformatics]]

@@ Line 6: / Line 6: @@
 |-
 ! colspan="8" bgcolor="#EFEFEF" | '''Chou-Fasman'''
-|--align="center" style="background-color:#1188ee; color:#ffffff;"
+|--align="center" style="background-color:#1188ee; color:#000;"
 !Name
-!P(a)
+!<tt>P(a)</tt>
-!P(b)
+!<tt>P(b)</tt>
-!P(turn)
+!<tt>P(turn)</tt>
-!f(i)
+!<tt>f(i)</tt>
-!f(i+1)
+!<tt>f(i+1)</tt>
-!f(i+2)
+!<tt>f(i+2)</tt>
-!f(i+3)
+!<tt>f(i+3)</tt>
 |-align="right"
 |align="left"|Alanine || 142 || 83 || 66 || 0.06 || 0.076 || 0.035 || 0.058

@@ Line 60: / Line 60: @@
 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 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.
+#Scan through the peptide and identify regions where 4 out of 6 contiguous residues have <code>P(a-helix) > 100</code>. That region is declared an alpha-helix. Extend the helix in both directions until a set of four contiguous residues that have an average <code>P(a-helix) < 100</code> 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 <code>P(a-helix) > P(b-sheet)</code> 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 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.
+#Scan through the peptide and identify a region where 3 out of 5 of the residues have a value of <code>P(b-sheet) > 100</code>. 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 <code>P(b-sheet) < 100</code> 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 <code>P(b-sheet) > 105</code> and the average <code>P(b-sheet) > P(a-helix)</code> 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 average P(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 <code>P(a-helix) > P(b-sheet)</code> for that region. It is a beta sheet if the average <code>P(b-sheet) > P(a-helix)</code> for that region.
-#To identify a bend at residue number j, calculate the following value:
+#To identify a bend at residue number <code>j</code>, 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.
+where the <code>f(j+1)</code> value for the <code>j+1</code> residue is used, the <code>f(j+2)</code> value for the <code>j+2</code> residue is used and the <code>f(j+3)</code> value for the <code>j+3</code> residue is used. If:
 ==References==