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

PLoS Comput Biol. 2012;8(8):e1002665. doi: 10.1371/journal.pcbi.1002665. Epub 2012 Aug 30.

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 micros 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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Antiviral Agents / pharmacology
  • Drug Resistance, Viral* / genetics
  • Models, Molecular
  • Molecular Dynamics Simulation
  • Neuraminidase / metabolism*
  • Orthomyxoviridae / drug effects*
  • Orthomyxoviridae / enzymology
  • Oseltamivir / pharmacology
  • Thermodynamics
  • Zanamivir / pharmacology

Substances

  • Antiviral Agents
  • Oseltamivir
  • Neuraminidase
  • Zanamivir

Grant support

Support for this research was provided by the Military Infectious Diseases Research Program of the United States (US) Army Medical Research and Materiel Command, Fort Detrick, Maryland, and the US Department of Defense (DoD) High-Performance Computing Modernization Program. The opinions and assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting the views of the US Army or the US DoD. This paper has been approved for public release with unlimited distribution. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.