TOPO: Improving remote homologue recognition via identifying common protein structure framework

TL;DR

TOPO introduces a novel method to enhance remote homologue recognition in protein structure prediction by identifying common structural frameworks, addressing limitations of existing threading approaches for distant homologs.

Contribution

The paper proposes a new framework that improves remote homologue recognition by focusing on common protein structure frameworks, advancing fold recognition accuracy.

Findings

Enhanced recognition of remote homologues.

Improved accuracy over existing threading methods.

Potential for better protein structure prediction.

Abstract

Protein structure prediction remains a challenge in the field of computational biology. Traditional protein structure prediction approaches include template-based modelling (say, homology modelling, and threading), and ab initio. A threading algorithm takes a query protein sequence as input, recognizes the most likely fold, and finally reports the alignments of the query sequence to structure-known templates as output. The existing threading approaches mainly utilizes the information of protein sequence profile, solvent accessibility, contact probability, etc., and correctly recognize folds for some proteins. However, the existing threading approaches show poorly performance for remote homology proteins. How to improve the fold recognition for remote homology proteins remains to be a difficult task for protein structure prediction.