Dinosolve: a protein disulfide bonding prediction server using context-based features to enhance prediction accuracy.

ABSTRACT:

Background

Disulfide bonds play an important role in protein folding and structure stability. Accurately predicting disulfide bonds from protein sequences is important for modeling the structural and functional characteristics of many proteins.

Methods

In this work, we introduce an approach of enhancing disulfide bonding prediction accuracy by taking advantage of context-based features. We firstly derive the first-order and second-order mean-force potentials according to the amino acid environment around the cysteine residues from large number of cysteine samples. The mean-force potentials are integrated as context-based scores to estimate the favorability of a cysteine residue in disulfide bonding state as well as a cysteine pair in disulfide bond connectivity. These contex

SUBMITTER: Yaseen A 

PROVIDER: S-EPMC3849605 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature