BCL::contact-low confidence fold recognition hits boost protein contact prediction and de novo structure determination.

ABSTRACT: Knowledge of all residue-residue contacts within a protein allows determination of the protein fold. Accurate prediction of even a subset of long-range contacts (contacts between amino acids far apart in sequence) can be instrumental for determining tertiary structure. Here we present BCL::Contact, a novel contact prediction method that utilizes artificial neural networks (ANNs) and specializes in the prediction of medium to long-range contacts. BCL::Contact comes in two modes: sequence-based and structure-based. The sequence-based mode uses only sequence information and has individual ANNs specialized for helix-helix, helix-strand, strand-helix, strand-strand, and sheet-sheet contacts. The structure-based mode combines results from 32-fold recognition methods with sequence information to

SUBMITTER: Karakas M 

PROVIDER: S-EPMC3148831 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature