UMass Chan Medical School Faculty Publications

UMMS Affiliation

Department of Biochemistry and Molecular Pharmacology

Publication Date


Document Type



Biochemistry, Biophysics, and Structural Biology | Cellular and Molecular Physiology | Comparative and Evolutionary Physiology | Evolution | Structural Biology


Drug resistance is caused by mutations that change the balance of recognition favoring substrate cleavage over inhibitor binding. Here, a structural dynamics perspective of the regained wild-type functioning in mutant HIV-1 proteases with coevolution of the natural substrates is provided. The collective dynamics of mutant structures of the protease bound to p1-p6 and NC-p1 substrates are assessed using the Anisotropic Network Model (ANM). The drug-induced protease mutations perturb the mechanistically crucial hinge axes that involve key sites for substrate binding and dimerization and mainly coordinate the intrinsic dynamics. Yet with substrate coevolution, while the wild-type dynamic behavior is restored in both p1-p6 ((LP) (1'F)p1-p6D30N/N88D) and NC-p1 ((AP) (2) (V)NC-p1V82A) bound proteases, the dynamic behavior of the NC-p1 bound protease variants (NC-p1V82A and (AP) (2) (V)NC-p1V82A) rather resemble those of the proteases bound to the other substrates, which is consistent with experimental studies. The orientational variations of residue fluctuations along the hinge axes in mutant structures justify the existence of coevolution in p1-p6 and NC-p1 substrates, that is, the dynamic behavior of hinge residues should contribute to the interdependent nature of substrate recognition. Overall, this study aids in the understanding of the structural dynamics basis of drug resistance and evolutionary optimization in the HIV-1 protease system.


HIV-1 protease, coevolution, elastic network model, fluctuations

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Copyright © 2014 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

DOI of Published Version



Evol Appl. 2015 Feb;8(2):185-98. doi: 10.1111/eva.12241. Epub 2015 Jan 11. Link to article on publisher's site

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Link to Article in PubMed

Journal/Book/Conference Title

Evolutionary applications

PubMed ID