Molecular Dynamics Simulations Suggest that Electrostatic Funnel Directs Binding of Tamiflu to Influenza N1 Neuraminidases

Oseltamivir (Tamiflu) is currently the frontline antiviral drug employed to fight the flu virus in infected individuals by inhibiting neuraminidase, a flu protein responsible for the release of newly synthesized virions. However, oseltamivir resistance has become a critical problem due to rapid mutation of the flu virus. Unfortunately, how mutations actually confer drug resistance is not well understood. In this study, we employ molecular dynamics (MD) and steered molecular dynamics (SMD) simulations, as well as graphics processing unit (GPU)-accelerated electrostatic mapping, to uncover the mechanism behind point mutation induced oseltamivir-resistance in both H5N1 “avian” and H1N1pdm “swine” flu N1-subtype neuraminidases. The simulations reveal an electrostatic binding funnel that plays a key role in directing oseltamivir into and out of its binding site on N1 neuraminidase. The binding pathway for oseltamivir suggests how mutations disrupt drug binding and how new drugs may circumvent the resistance mechanisms

Independent-Trajectories Thermodynamic-Integration Free-Energy Changes for Biomolecular Systems: Determinants of H5N1 Avian Influenza Virus Neuraminidase Inhibition by Peramivir

Free-energy changes are essential physicochemical quantities for understanding most biochemical processes. Yet, the application of accurate thermodynamic-integration (TI) computation to biological and macromolecular systems is limited by finite-sampling artifacts. In this paper, we employ independent-trajectories thermodynamic-integration (IT-TI) computation to estimate improved free-energy changes and their uncertainties for (bio)molecular systems. IT-TI aids sampling statistics of the thermodynamic macrostates for flexible associating partners by ensemble averaging of multiple, independent simulation trajectories. We study peramivir (PVR) inhibition of the H5N1 avian influenza virus neuraminidase flexible receptor (N1). Binding site loops 150 and 119 are highly mobile, as revealed by N1-PVR 20-ns molecular dynamics. Due to such heterogeneous sampling, standard TI binding free-energy estimates span a rather large free-energy range, from a 19% underestimation to a 29% overestimation of the experimental reference value (−62.2 ± 1.8 kJ mol−1). Remarkably, our IT-TI binding free-energy estimate (−61.1 ± 5.4 kJ mol−1) agrees with a 2% relative difference. In addition, IT-TI runs provide a statistics-based free-energy uncertainty for the process of interest. Using ∼800 ns of overall sampling, we investigate N1-PVR binding determinants by IT-TI alchemical modifications of PVR moieties. These results emphasize the dominant electrostatic contribution, particularly through the N1 E277−PVR guanidinium interaction. Future drug development may be also guided by properly tuning ligand flexibility and hydrophobicity. IT-TI will allow estimation of relative free energies for systems of increasing size, with improved reliability by employing large-scale distributed computing