Prediction of the number of residue contacts in proteins.
Knowing the number of residue contacts in a protein is crucial for deriving constraints useful in modeling protein folding and/or scoring remote homology search. Here we focus on the prediction of residue contacts and show that this figure can be predicted with a neural network based method. The accuracy of the prediction is 12 percentage points higher than that of a simple statistical method. The neural network is used to discriminate between two different states of residue contacts, characterized by a contact number higher or lower than the average value of the residue distribution. When evolutionary information is taken into account, our method correctly predicts 69% of the residue states in the data base and it adds to the prediction of residue solvent accessibility. The predictor is available at htpp://www.biocomp.unibo.it
Fariselli
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P
Dept. of Biology University of Bologna, Italy. Piero@biocomp.unibo.it
Casadio
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R
D000818:Animals; D016208:Databases, Factual; D019143:Evolution, Molecular; D006801:Humans; D011237:Predictive Value of Tests; D011506:Proteins / Q000737:chemistry / Q000145:classification* / Q000235:genetics*; D020539:Sequence Analysis, Protein / Q000379:methods*
D011506:Proteins