An optimized TOPS+ comparison method for enhanced TOPS models.

Abstract:

BACKGROUND:Although methods based on highly abstract descriptions of protein structures, such as VAST and TOPS, can perform very fast protein structure comparison, the results can lack a high degree of biological significance. Previously we have discussed the basic mechanisms of our novel method for structure comparison based on our TOPS+ model (Topological descriptions of Protein Structures Enhanced with Ligand Information). In this paper we show how these results can be significantly improved using parameter optimization, and we call the resulting optimised TOPS+ method as advanced TOPS+ comparison method i.e. advTOPS+. RESULTS:We have developed a TOPS+ string model as an improvement to the TOPS 123 graph model by considering loops as secondary structure elements (SSEs) in addition to helices and strands, representing ligands as first class objects, and describing interactions between SSEs, and SSEs and ligands, by incoming and outgoing arcs, annotating SSEs with the interaction direction and type. Benchmarking results of an all-against-all pairwise comparison using a large dataset of 2,620 non-redundant structures from the PDB40 dataset 4 demonstrate the biological significance, in terms of SCOP classification at the superfamily level, of our TOPS+ comparison method. CONCLUSIONS:Our advanced TOPS+ comparison shows better performance on the PDB40 dataset 4 compared to our basic TOPS+ method, giving 90% accuracy for SCOP alpha+beta; a 6% increase in accuracy compared to the TOPS and basic TOPS+ methods. It also outperforms the TOPS, basic TOPS+ and SSAP comparison methods on the Chew-Kedem dataset 5, achieving 98% accuracy. SOFTWARE AVAILABILITY:The TOPS+ comparison server is available at http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/.

journal_name

BMC Bioinformatics

journal_title

BMC bioinformatics

authors

Veeramalai M,Gilbert D,Valiente G

doi

10.1186/1471-2105-11-138

subject

Has Abstract

pub_date

2010-03-17 00:00:00

pages

138

issn

1471-2105

pii

1471-2105-11-138

journal_volume

11

pub_type

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