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dc.contributor.author Machado, Karina dos Santos
dc.contributor.author Schroeder, Evelyn Koeche
dc.contributor.author Ruiz, Duncan Dubugras Alcoba
dc.contributor.author Cohen, Elisangela Machado Leal
dc.contributor.author Souza, Osmar Norberto de
dc.date.accessioned 2015-05-28T16:42:37Z
dc.date.available 2015-05-28T16:42:37Z
dc.date.issued 2011
dc.identifier.citation MACHADO, Karina dos Santos et al. FReDoWS: a method to automate molecular docking simulations with explicit receptor flexibility and snapshots selection. BMC Genomics, v. 12, supl. 4, p. 1-13, 2011. Disponível em: <http://www.biomedcentral.com/1471-2164/12/S4/S6>. Acesso em: 15 maio 2015. pt_BR
dc.identifier.issn 1471-2164
dc.identifier.uri http://repositorio.furg.br/handle/1/4921
dc.description.abstract Background: In silico molecular docking is an essential step in modern drug discovery when driven by a well defined macromolecular target. Hence, the process is called structure-based or rational drug design (RDD). In the docking step of RDD the macromolecule or receptor is usually considered a rigid body. However, we know from biology that macromolecules such as enzymes and membrane receptors are inherently flexible. Accounting for this flexibility in molecular docking experiments is not trivial. One possibility, which we call a fully-flexible receptor model, is to use a molecular dynamics simulation trajectory of the receptor to simulate its explicit flexibility. To benefit from this concept, which has been known since 2000, it is essential to develop and improve new tools that enable molecular docking simulations of fully-flexible receptor models. Results: We have developed a Flexible-Receptor Docking Workflow System (FReDoWS) to automate molecular docking simulations using a fully-flexible receptor model. In addition, it includes a snapshot selection feature to facilitate acceleration the virtual screening of ligands for well defined disease targets. FReDoWS usefulness is demonstrated by investigating the docking of four different ligands to flexible models of Mycobacterium tuberculosis’ wild type InhA enzyme and mutants I21V and I16T. We find that all four ligands bind effectively to this receptor as expected from the literature on similar, but wet experiments. Conclusions: A work that would usually need the manual execution of many computer programs, and the manipulation of thousands of files, was efficiently and automatically performed by FReDoWS. Its friendly interface allows the user to change the docking and execution parameters. Besides, the snapshot selection feature allowed the acceleration of docking simulations. We expect FReDoWS to help us explore more of the role flexibility plays in receptor-ligand interactions. FReDoWS can be made available upon request to the authors pt_BR
dc.language.iso eng pt_BR
dc.rights open access pt_BR
dc.title FReDoWS: a method to automate molecular docking simulations with explicit receptor flexibility and snapshots selection pt_BR
dc.type article pt_BR
dc.identifier.doi 10.1186/1471-2164-12-S4-S6 pt_BR


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