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The interplay of structure and dynamics: Insights from a survey of HIV‐1 reverse transcriptase crystal structures
Author(s) -
Seckler James M.,
Leioatts Nicholas,
Miao Hongyu,
Grossfield Alan
Publication year - 2013
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.24325
Subject(s) - reverse transcriptase , mechanism (biology) , computational biology , human immunodeficiency virus (hiv) , dynamics (music) , drug discovery , protein structure , function (biology) , molecular dynamics , chemistry , biological system , biophysics , biology , bioinformatics , rna , physics , microbiology and biotechnology , virology , biochemistry , computational chemistry , gene , quantum mechanics , acoustics
HIV‐1 reverse transcriptase (RT) is a critical drug target for HIV treatment, and understanding the exact mechanisms of its function and inhibition would significantly accelerate the development of new anti‐HIV drugs. It is well known that structure plays a critical role in protein function, but for RT, structural information has proven to be insufficient—despite enormous effort—to explain the mechanism of inhibition and drug resistance of non‐nucleoside RT inhibitors. We hypothesize that the missing link is dynamics, information about the motions of the system. However, many of the techniques that give the best information about dynamics, such as solution nuclear magnetic resonance and molecular dynamics simulations, cannot be easily applied to a protein as large as RT. As an alternative, we combine elastic network modeling with simultaneous hierarchical clustering of structural and dynamic data. We present an extensive survey of the dynamics of RT bound to a variety of ligands and with a number of mutations, revealing a novel mechanism for drug resistance to non‐nucleoside RT inhibitors. Hydrophobic core mutations restore active‐state motion to multiple functionally significant regions of HIV‐1 RT. This model arises out of a combination of structural and dynamic information, rather than exclusively from one or the other. Proteins 2013; 81:1792–1801. © 2013 Wiley Periodicals, Inc.