Using multi-data hidden Markov models trained on local neighborhoods of protein structure to predict residue-residue contacts.

ABSTRACT:

Motivation

Correct prediction of residue-residue contacts in proteins that lack good templates with known structure would take ab initio protein structure prediction a large step forward. The lack of correct contacts, and in particular long-range contacts, is considered the main reason why these methods often fail.

Results

We propose a novel hidden Markov model (HMM)-based method for predicting residue-residue contacts from protein sequences using as training data homologous sequences, predicted secondary structure and a library of local neighborhoods (local descriptors of protein structure). The library consists of recurring structural entities incorporating short-, medium- and long-range interactions and is general enough to reassemble the cores of nearly all proteins in t

SUBMITTER: Bjorkholm P 

PROVIDER: S-EPMC2677742 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature