Quantitative Predictions of Binding Free Energy Changes in Drug-Resistant Influenza Neuraminidase

Daniel R. Ripoll, Ilja V. Khavrutskii, Sidhartha Chaudhury, Jin Liu, Robert A. Kuschner, Anders Wallqvist, Jaques Reifman

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Quantitatively predicting changes in drug sensitivity associated with residue mutations is a major challenge in structural biology. By expanding the limits of free energy calculations, we successfully identified mutations in influenza neuraminidase (NA) that confer drug resistance to two antiviral drugs, zanamivir and oseltamivir. We augmented molecular dynamics (MD) with Hamiltonian Replica Exchange and calculated binding free energy changes for H274Y, N294S, and Y252H mutants. Based on experimental data, our calculations achieved high accuracy and precision compared with results from established computational methods. Analysis of 15 μs of aggregated MD trajectories provided insights into the molecular mechanisms underlying drug resistance that are at odds with current interpretations of the crystallographic data. Contrary to the notion that resistance is caused by mutant-induced changes in hydrophobicity of the binding pocket, our simulations showed that drug resistance mutations in NA led to subtle rearrangements in the protein structure and its dynamics that together alter the active-site electrostatic environment and modulate inhibitor binding. Importantly, different mutations confer resistance through different conformational changes, suggesting that a generalized mechanism for NA drug resistance is unlikely.

Original languageEnglish
Article numbere1002665
JournalPLoS Computational Biology
Volume8
Issue number8
DOIs
StatePublished - Aug 2012

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