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Protein Engineering, Vol. 12, No. 1, 15-21, January 1999
© 1999 Oxford University Press

A neural network based predictor of residue contacts in proteins

P. Fariselli1 and R. Casadio1,2,3

1 Biocomputing Group (Centro Interdipartimentale per le Ricerche Biotecnologiche) and 2 Laboratory of Biophysics, Department of Biology, University of Bologna, Via Irnerio, 42, 40126 Bologna, Italy

We describe a method based on neural networks for predicting contact maps of proteins using as input chemico-physical and evolutionary information. Neural networks are trained on a data set comprising the contact maps of 200 non-homologous proteins of well resolved three-dimensional structures. The systems learn the association rules between the covalent structure of each protein and its correspondent contact map by means of a standard back propagation algorithm. Validation of the predictor on the training set and on 408 proteins of known structure which are not homologous to those contained in the training set indicate that this method scores higher than statistical approaches previously described and based on correlated mutations and sequence information.

Keywords: neural networks/protein structure prediction/contact maps/multiple sequence information

3 To whom correspondence should be addressed


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