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Editor, Senior Moderator
Top Leads for Swine Influenza A/H1N1 Virus Revealed by Steered Molecular Dynamics Approach
Binh Khanh Mai?, Man Hoang Viet?, and Mai Suan Li*?
Institute for Computational Science and Technology, 6 Quarter, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam, and Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
J. Chem. Inf. Model., Article ASAP
DOI: 10.1021/ci100346s
Publication Date (Web): November 23, 2010
Copyright ? 2010 American Chemical Society
Since March 2009, the rapid spread of infection during the recent A/H1N1 swine flu pandemic has raised concerns of a far more dangerous outcome should this virus become resistant to current drug therapies. Currently oseltamivir (tamiflu) is intensively used for the treatment of influenza and is reported effective for 2009 A/H1N1 virus. However, as this virus is evolving fast, some drug-resistant strains are emerging. Therefore, it is critical to seek alternative treatments and identify roots of the drug resistance. In this paper, we use the steered molecular dynamics (SMD) approach to estimate the binding affinity of ligands to the glycoprotein neuraminidase. Our idea is based on the hypothesis that the larger is the force needed to unbind a ligand from a receptor the higher its binding affinity. Using all-atom models with Gromos force field 43a1 and explicit water, we have studied the binding ability of 32 ligands to glycoprotein neuraminidase from swine flu virus A/H1N1. The electrostatic interaction is shown to play a more important role in binding affinity than the van der Waals one. We have found that four ligands 141562, 5069, 46080, and 117079 from the NSC set are the most promising candidates to cope with this virus, while peramivir, oseltamivir, and zanamivir are ranked 8, 11, and 20. The observation that these four ligands are better than existing commercial drugs has been also confirmed by our results on the binding free energies obtained by the molecular mechanics−Poisson−Boltzmann surface area (MM-PBSA) method. Our prediction may be useful for the therapeutic application.
http://pubs.acs.org/doi/abs/10.1021/ci100346s
Binh Khanh Mai?, Man Hoang Viet?, and Mai Suan Li*?
Institute for Computational Science and Technology, 6 Quarter, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam, and Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
J. Chem. Inf. Model., Article ASAP
DOI: 10.1021/ci100346s
Publication Date (Web): November 23, 2010
Copyright ? 2010 American Chemical Society
Since March 2009, the rapid spread of infection during the recent A/H1N1 swine flu pandemic has raised concerns of a far more dangerous outcome should this virus become resistant to current drug therapies. Currently oseltamivir (tamiflu) is intensively used for the treatment of influenza and is reported effective for 2009 A/H1N1 virus. However, as this virus is evolving fast, some drug-resistant strains are emerging. Therefore, it is critical to seek alternative treatments and identify roots of the drug resistance. In this paper, we use the steered molecular dynamics (SMD) approach to estimate the binding affinity of ligands to the glycoprotein neuraminidase. Our idea is based on the hypothesis that the larger is the force needed to unbind a ligand from a receptor the higher its binding affinity. Using all-atom models with Gromos force field 43a1 and explicit water, we have studied the binding ability of 32 ligands to glycoprotein neuraminidase from swine flu virus A/H1N1. The electrostatic interaction is shown to play a more important role in binding affinity than the van der Waals one. We have found that four ligands 141562, 5069, 46080, and 117079 from the NSC set are the most promising candidates to cope with this virus, while peramivir, oseltamivir, and zanamivir are ranked 8, 11, and 20. The observation that these four ligands are better than existing commercial drugs has been also confirmed by our results on the binding free energies obtained by the molecular mechanics−Poisson−Boltzmann surface area (MM-PBSA) method. Our prediction may be useful for the therapeutic application.
http://pubs.acs.org/doi/abs/10.1021/ci100346s