Predicting residue-residue contacts and helix-helix interactions in transmembrane proteins using an integrative feature-based random forest approach.

ABSTRACT: Integral membrane proteins constitute 25-30% of genomes and play crucial roles in many biological processes. However, less than 1% of membrane protein structures are in the Protein Data Bank. In this context, it is important to develop reliable computational methods for predicting the structures of membrane proteins. Here, we present the first application of random forest (RF) for residue-residue contact prediction in transmembrane proteins, which we term as TMhhcp. Rigorous cross-validation tests indicate that the built RF models provide a more favorable prediction performance compared with two state-of-the-art methods, i.e., TMHcon and MEMPACK. Using a strict leave-one-protein-out jackknifing procedure, they were capable of reaching the top L/5 prediction accuracies of 49.5% and 48.8% fo

SUBMITTER: Wang XF 

PROVIDER: S-EPMC3203928 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature