Validation of protein structure models using network similarity score

Ghosh, Sambit and Gadiyaram, Vasundhara and Vishveshwara, Saraswathi (2017) Validation of protein structure models using network similarity score. In: PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 85 (9). pp. 1759-1776.

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Abstract

Accurate structural validation of proteins is of extreme importance in studies like protein structure prediction, analysis of molecular dynamic simulation trajectories and finding subtle changes in very similar structures. The benchmarks for today's structure validation are scoring methods like global distance test-total structure (GDT-TS), TM-score and root mean square deviations (RMSD). However, there is a lack of methods that look at both the protein backbone and side-chain structures at the global connectivity level and provide information about the differences in connectivity. To address this gap, a graph spectral based method (NSS-network similarity score) which has been recently developed to rigorously compare networks in diverse fields, is adopted to compare protein structures both at the backbone and at the side-chain noncovalent connectivity levels. In this study, we validate the performance of NSS by investigating protein structures from X-ray structures, modeling (including CASP models), and molecular dynamics simulations. Further, we systematically identify the local and the global regions of the structures contributing to the difference in NSS, through the components of the score, a feature unique to this spectral based scoring scheme. It is demonstrated that the method can quantify subtle differences in connectivity compared to a reference protein structure and can form a robust basis for protein structure comparison. Additionally, we have also introduced a network-based method to analyze fluctuations in side chain interactions (edge-weights) in an ensemble of structures, which can be an useful tool for the analysis of MID trajectories.

Item Type:	Journal Article
Publication:	PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Additional Information:	Copy right for this article belongs to the WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
Department/Centre:	Division of Biological Sciences > Molecular Biophysics Unit
Date Deposited:	16 Sep 2017 06:23
Last Modified:	16 Sep 2017 06:23
URI:	http://eprints.iisc.ac.in/id/eprint/57798

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