AutoDock Bias: improving binding mode prediction and virtual screening using known protein–ligand interactions

Abstract 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 d...

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Veröffentlicht in:Bioinformatics 2019-10, Vol.35 (19), p.3836-3838
Hauptverfasser: Arcon, Juan Pablo, Modenutti, Carlos P, Avendaño, Demian, Lopez, Elias D, Defelipe, Lucas A, Ambrosio, Francesca Alessandra, Turjanski, Adrian G, Forli, Stefano, Marti, Marcelo A
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Sprache:eng
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Zusammenfassung:Abstract 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.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btz152