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      Mechanism of 150-cavity formation in influenza neuraminidase

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          Abstract

          The recently discovered 150-cavity in the active site of group-1 influenza A neuraminidase (NA) proteins provides a target for rational structure-based drug development to counter the increasing frequency of antiviral resistance in influenza. Surprisingly, the 2009 H1N1 pandemic virus (09N1) neuramidase was crystalized without the 150-cavity characteristic of group-1 NAs. Here we demonstrate, through a total sum of 1.6 μs of biophysical simulations, that 09N1 NA exists in solution preferentially with an open 150-cavity. Comparison with simulations using avian N1, human N2 and 09N1 with a I149V mutation and an extensive bioinformatics analysis suggests that the conservation of a key salt bridge is crucial in the stabilization of the 150-cavity across both subtypes. This result provides an atomic-level structural understanding of the recent finding that antiviral compounds designed to take advantage of contacts in the 150-cavity can inactivate both 2009 H1N1 pandemic and avian H5N1 viruses.

          Abstract

          Group-1 influenza A neuramidase proteins have a 150-cavity that can be targeted by drugs, but the 2009 H1N1 virus neuramidase is not thought to have a 150-cavity. Here, biophysical simulations show that the 2009 H1N1 neuramidase exists in solution with an open 150-cavity, which is stabilized by a salt bridge.

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          Most cited references15

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          Very fast empirical prediction and rationalization of protein pKa values.

          A very fast empirical method is presented for structure-based protein pKa prediction and rationalization. The desolvation effects and intra-protein interactions, which cause variations in pKa values of protein ionizable groups, are empirically related to the positions and chemical nature of the groups proximate to the pKa sites. A computer program is written to automatically predict pKa values based on these empirical relationships within a couple of seconds. Unusual pKa values at buried active sites, which are among the most interesting protein pKa values, are predicted very well with the empirical method. A test on 233 carboxyl, 12 cysteine, 45 histidine, and 24 lysine pKa values in various proteins shows a root-mean-square deviation (RMSD) of 0.89 from experimental values. Removal of the 29 pKa values that are upper or lower limits results in an RMSD = 0.79 for the remaining 285 pKa values. Proteins 2005. 2005 Wiley-Liss, Inc.
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            Reduced surface: an efficient way to compute molecular surfaces.

            Because of their wide use in molecular modeling, methods to compute molecular surfaces have received a lot of interest in recent years. However, most of the proposed algorithms compute the analytical representation of only the solvent-accessible surface. There are a few programs that compute the analytical representation of the solvent-excluded surface, but they often have problems handling singular cases of self-intersecting surfaces and tend to fail on large molecules (more than 10,000 atoms). We describe here a program called MSMS, which is shown to be fast and reliable in computing molecular surfaces. It relies on the use of the reduced surface that is briefly defined here and from which the solvent-accessible and solvent-excluded surfaces are computed. The four algorithms composing MSMS are described and their complexity is analyzed. Special attention is given to the handling of self-intersecting parts of the solvent-excluded surface called singularities. The program has been compared with Connolly's program PQMS [M.L. Connolly (1993) Journal of Molecular Graphics, Vol. 11, pp. 139-141] on a set of 709 molecules taken from the Brookhaven Data Base. MSMS was able to compute topologically correct surfaces for each molecule in the set. Moreover, the actual time spent to compute surfaces is in agreement with the theoretical complexity of the program, which is shown to be O[n log(n)] for n atoms. On a Hewlett-Packard 9000/735 workstation, MSMS takes 0.73 s to produce a triangulated solvent-excluded surface for crambin (1 crn, 46 residues, 327 atoms, 4772 triangles), 4.6 s for thermolysin (3tln, 316 residues, 2437 atoms, 26462 triangles), and 104.53 s for glutamine synthetase (2gls, 5676 residues, 43632 atoms, 476665 triangles).
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              The structure of H5N1 avian influenza neuraminidase suggests new opportunities for drug design.

              The worldwide spread of H5N1 avian influenza has raised concerns that this virus might acquire the ability to pass readily among humans and cause a pandemic. Two anti-influenza drugs currently being used to treat infected patients are oseltamivir (Tamiflu) and zanamivir (Relenza), both of which target the neuraminidase enzyme of the virus. Reports of the emergence of drug resistance make the development of new anti-influenza molecules a priority. Neuraminidases from influenza type A viruses form two genetically distinct groups: group-1 contains the N1 neuraminidase of the H5N1 avian virus and group-2 contains the N2 and N9 enzymes used for the structure-based design of current drugs. Here we show by X-ray crystallography that these two groups are structurally distinct. Group-1 neuraminidases contain a cavity adjacent to their active sites that closes on ligand binding. Our analysis suggests that it may be possible to exploit the size and location of the group-1 cavity to develop new anti-influenza drugs.
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                Author and article information

                Journal
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                July 2011
                12 July 2011
                : 2
                : 388
                Affiliations
                [1 ]simpleDepartment of Pharmaceutical Sciences, Computer Science and Chemistry, University of California , Irvine, California 92697USA.
                [2 ]simpleNational Biomedical Computation Resource, University of California , simpleSan Diego , La Jolla, California 92093USA.
                [3 ]simpleDepartment of Chemistry and Biochemistry, San Diego Supercomputer Center, University of California , simpleSan Diego , La Jolla California 92093USA.
                [4 ]simpleDepartment of Ecology and Evolutionary Biology, University of California , Irvine, California 92697USA.
                Author notes
                Article
                ncomms1390
                10.1038/ncomms1390
                3144582
                21750542
                65b015f5-5019-408f-81a8-1418a4cde404
                Copyright © 2011, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/

                History
                : 20 April 2011
                : 13 June 2011
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