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Understanding structural variability in proteins using protein structural networks

Prabantu, Vasam Manjveekar and Gadiyaram, Vasundhara and Vishveshwara, Saraswathi and Srinivasan, Narayanaswamy (2022) Understanding structural variability in proteins using protein structural networks. In: Current Research in Structural Biology, 4 . pp. 134-145. ISSN 2665928X

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Official URL: https://doi.org/10.1016/j.crstbi.2022.04.002


Proteins perform their function by accessing a suitable conformer from the ensemble of available conformations. The conformational diversity of a chosen protein structure can be obtained by experimental methods under different conditions. A key issue is the accurate comparison of different conformations. A gold standard used for such a comparison is the root mean square deviation (RMSD) between the two structures. While extensive refinements of RMSD evaluation at the backbone level are available, a comprehensive framework including the side chain interaction is not well understood. Here we employ protein structure network (PSN) formalism, with the non-covalent interactions of side chain, explicitly treated. The PSNs thus constructed are compared through graph spectral method, which provides a comparison at the local and at the global structural level. In this work, PSNs of multiple crystal conformers of single-chain, single-domain proteins, are subject to pair-wise analysis to examine the dissimilarity in their network topologies and in order to determine the conformational diversity of their native structures. This information is utilized to classify the structural domains of proteins into different categories. It is observed that proteins typically tend to retain structure and interactions at the backbone level. However, some of them also depict variability in either their overall structure or only in their inter-residue connectivity at the sidechain level, or both. Variability of sub-networks based on solvent accessibility and secondary structure is studied. The types of specific interactions are found to contribute differently to structure variability. An ensemble analysis by computing the mathematical variance of edge-weights across multiple conformers provided information on the contribution to overall variability from each edge of the PSN. Interactions that are highly variable are identified and their impact on structure variability has been discussed with the help of a case study. The classification based on the present side-chain network-based studies provides a framework to correlate the structure-function relationships in protein structures.

Item Type: Journal Article
Publication: Current Research in Structural Biology
Publisher: Elsevier B.V.
Additional Information: The copyright of this article belongs to the Authors.
Keywords: Edge-weight variance; Protein classification; Protein structural networks; Protein structure comparison; Structural variability
Department/Centre: Division of Biological Sciences > Molecular Biophysics Unit
Date Deposited: 23 May 2022 04:28
Last Modified: 23 May 2022 04:28
URI: https://eprints.iisc.ac.in/id/eprint/72397

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