Difference between revisions of "Chou-Fasman"
From Christoph's Personal Wiki
Line 70: | Line 70: | ||
==References== | ==References== | ||
<references/> | <references/> | ||
+ | ==External links== | ||
+ | *[http://swift.cmbi.kun.nl/swift/future/aainfo/contents.htm Amino Acid Information] | ||
[[Category:Bioinformatics]] | [[Category:Bioinformatics]] |
Revision as of 07:32, 20 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]
Chou-Fasman table
Chou-Fasman | |||||||
---|---|---|---|---|---|---|---|
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 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
- ↑ 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.