Generic placeholder image

Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Research Article

Unveiling the Accuracy of Homology Modeling to Elucidate the Structure of GPCRs-HIV Co-receptor-CCR5 as a Case Study

Author(s): Vadivelu Aanand, Rajendran Anitha, Somarathinam Kanagasabai, Gunalan Seshan, Changdev G. Gadhe and Gugan Kothandan*

Volume 15, Issue 10, 2018

Page: [1068 - 1078] Pages: 11

DOI: 10.2174/1570180814666171120153956

Price: $65

Abstract

Background: Going through several difficulties in crystallizing GPCRs, deeper understanding of these proteins could be understood through homology modeling and mutational studies. Due to the unavailability of experimentally solved structures, in silico models could gain insights. CCR5 is a pharmaceutically significant GPCR and it has been well-characterized even before its xtal structure. Mutagenesis studies were carried out to designate the binding pockets of CCR5 with the help of homology models. This prompted us to bring out the indispensable nature of homology modeling with CCR5 as a case study.

Result: In this paper, we pointed out the advantages and limitations of homology modeling approaches through the comparison of previously reported in silico models of CCR5 with the recently emerged crystal structure. From our extensive literature studies, we found that homology modeling and associated mutagenesis studies shall provide greater understanding towards any receptor-ligand interaction and the amino acid residues involved in it. Adding a structural characteristic of the selected templates to make a multi-template model gave a new insight into homology modeling having its own merits and demerits.

Conclusion: Through our observations, we emphasize that homology modeling can be a valuable tool to understand those structurally unsolved, yet clinically important drug design and discovery targeting proteins such as GPCRs.

Keywords: GPCRs, homology modeling, CCR5, CXCR4, maraviroc, multi-template modeling.

Graphical Abstract


© 2024 Bentham Science Publishers | Privacy Policy