Transmembrane protein alignment and fold recognition based on predicted topology.

ABSTRACT:

Background

Although Transmembrane Proteins (TMPs) are highly important in various biological processes and pharmaceutical developments, general prediction of TMP structures is still far from satisfactory. Because TMPs have significantly different physicochemical properties from soluble proteins, current protein structure prediction tools for soluble proteins may not work well for TMPs. With the increasing number of experimental TMP structures available, template-based methods have the potential to become broadly applicable for TMP structure prediction. However, the current fold recognition methods for TMPs are not as well developed as they are for soluble proteins.

Methodology

We developed a novel TMP Fold Recognition method, TMFR, to recognize TMP folds based on sequence-to-structure pairwise alignment. The method utilizes topology-based features in alignment together with sequence profile and solvent accessibility. It also incorporates a gap penalty that depends on predicted topology structure segments. Given the difference between ?-helical transmembrane protein (?TMP) and ?-strands transmembrane protein (?TMP), parameters of scoring functions are trained respectively for these two protein categories using 58 ?TMPs and 17 ?TMPs in a non-redundant training dataset.

Results

We compared our method with HHalign, a leading alignment tool using a non-redundant testing dataset including 72 ?TMPs and 30 ?TMPs. Our method achieved 10% and 9% better accuracies than HHalign in ?TMPs and ?TMPs, respectively. The raw score generated by TMFR is negatively correlated with the structure similarity between the target and the template, which indicates its effectiveness for fold recognition. The result demonstrates TMFR provides an effective TMP-specific fold recognition and alignment method.

SUBMITTER: Wang H 

PROVIDER: S-EPMC3716705 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature