A graph-theoretic approach for classification and structure prediction of transmembrane β-barrel proteins.

ABSTRACT:

Background

Transmembrane β-barrel proteins are a special class of transmembrane proteins which play several key roles in human body and diseases. Due to experimental difficulties, the number of transmembrane β-barrel proteins with known structures is very small. Over the years, a number of learning-based methods have been introduced for recognition and structure prediction of transmembrane β-barrel proteins. Most of these methods emphasize on homology search rather than any biological or chemical basis.

Results

We present a novel graph-theoretic model for classification and structure prediction of transmembrane β-barrel proteins. This model folds proteins based on energy minimization rather than a homology search, avoiding any assumption on availability of training dataset.

SUBMITTER: Tran Vdu T 

PROVIDER: S-EPMC3394416 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature