AutoDock Bias: improving binding mode prediction and virtual screening using known protein–ligand interactions
Summary: The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics....
| Autores: | , , , , , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/123543 |
| Acesso em linha: | http://hdl.handle.net/11336/123543 |
| Access Level: | acceso abierto |
| Palavra-chave: | bioinformatica docking drug design autodock https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
| Resumo: | Summary: The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics. AutoDock Bias is a straightforward and easy to use script-based method that allows the introduction of different types of user-defined biases for fine-tuning AutoDock4 docking calculations. Availability and implementation: AutoDock Bias is distributed with MGLTools (since version 1.5.7), and freely available on the web at http://ccsb.scripps.edu/mgltools/ or http://autodockbias.wordpress.com. Supplementary information: Supplementary data are available at Bioinformatics online. |
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