This article is part of the supplement: Proceedings of the 6th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-meeting 2010)
FReDoWS: a method to automate molecular docking simulations with explicit receptor flexibility and snapshots selection
1 LABIO - Laboratório de Bioinformática, Modelagem e Simulação de Biossistemas. PPGCC, Faculdade de Informática, PUCRS, Av. Ipiranga, 6681 – Prédio 32, Sala 602, 90619-900, Porto Alegre, RS, Brazil
2 GPIN - Grupo de Pesquisa em Inteligência de Negócio. PPGCC, Faculdade de Informática, PUCRS, Av. Ipiranga, 6681 – Prédio 32, Sala 628, 90619-900, Porto Alegre, RS, Brazil
3 Programa de Pós-Graduação em Biologia Celular e Molecular, Faculdade de Biociências, PUCRS, Av. Ipiranga, 6681 – Prédio 12, Bloco A, Sala 204, 90619-900, Porto Alegre, RS, Brazil
Citation and License
BMC Genomics 2011, 12(Suppl 4):S6 doi:10.1186/1471-2164-12-S4-S6Published: 22 December 2011
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.
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.
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.