G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design

Protein Science : a Publication of the Protein Society
Hui Sun Lee, Wonpil Im

Abstract

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA...Continue Reading

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Citations

Mar 5, 2019·Journal of Computational Chemistry·Hui Sun Lee, Wonpil Im
Sep 12, 2018·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Ke HanChengzhi Zhang
Mar 21, 2020·Scientific Reports·Marta M Stepniewska-DziubinskaPawel Siedlecki
Jul 24, 2021·Journal of Chemical Information and Modeling·Hugo GuterresWonpil Im
Dec 19, 2020·Journal of Chemical Information and Modeling·Hugo GuterresWonpil Im
Nov 11, 2021·Journal of Chemical Information and Modeling·Hugo GuterresWonpil Im

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