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      SwissDock, a protein-small molecule docking web service based on EADock DSS

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          Abstract

          Most life science processes involve, at the atomic scale, recognition between two molecules. The prediction of such interactions at the molecular level, by so-called docking software, is a non-trivial task. Docking programs have a wide range of applications ranging from protein engineering to drug design. This article presents SwissDock, a web server dedicated to the docking of small molecules on target proteins. It is based on the EADock DSS engine, combined with setup scripts for curating common problems and for preparing both the target protein and the ligand input files. An efficient Ajax/HTML interface was designed and implemented so that scientists can easily submit dockings and retrieve the predicted complexes. For automated docking tasks, a programmatic SOAP interface has been set up and template programs can be downloaded in Perl, Python and PHP. The web site also provides an access to a database of manually curated complexes, based on the Ligand Protein Database. A wiki and a forum are available to the community to promote interactions between users. The SwissDock web site is available online at http://www.swissdock.ch. We believe it constitutes a step toward generalizing the use of docking tools beyond the traditional molecular modeling community.

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          Most cited references32

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          Kemp elimination catalysts by computational enzyme design.

          The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination-a model reaction for proton transfer from carbon-with measured rate enhancements of up to 10(5) and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a >200-fold increase in k(cat)/K(m) (k(cat)/K(m) of 2,600 M(-1)s(-1) and k(cat)/k(uncat) of >10(6)). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.
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            The many roles of computation in drug discovery.

            An overview is given on the diverse uses of computational chemistry in drug discovery. Particular emphasis is placed on virtual screening, de novo design, evaluation of drug-likeness, and advanced methods for determining protein-ligand binding.
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              Merck molecular force field. II. MMFF94 van der Waals and electrostatic parameters for intermolecular interactions

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                Author and article information

                Journal
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                1 July 2011
                1 July 2011
                28 May 2011
                28 May 2011
                : 39
                : Web Server issue , Web Server issue
                : W270-W277
                Affiliations
                1Swiss Institute of Bioinformatics (SIB), Quartier Sorge, Bâtiment Génopode, CH-1015 Lausanne, 2Ludwig Institute for Cancer Research, Ltd and 3Pluridisciplinary Center for Clinical Oncology (CePO), Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
                Author notes
                *To whom correspondence should be addressed. Tel: +41 (0)21 692 40 53, Fax: +41 (0)21 692 40 65. Email: olivier.michielin@ 123456unil.ch
                Correspondence may also be addressed to Vincent Zoete, Tel: +41 (0)21 692 40 82, Fax: +41 (0)21 692 40 65. Email: vincent.zoete@ 123456unil.ch
                Article
                gkr366
                10.1093/nar/gkr366
                3125772
                21624888
                8b3ae6e8-f2f8-4b7d-baa1-22d4af4e28a5
                © The Author(s) 2011. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 February 2011
                : 12 April 2011
                : 27 April 2011
                Page count
                Pages: 8
                Categories
                Articles

                Genetics
                Genetics

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