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AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.
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.
Affiliation
  • Arcon JP; Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.
  • Modenutti CP; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.
  • Avendaño D; Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.
  • Lopez ED; Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.
  • Defelipe LA; Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.
  • Ambrosio FA; Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.
  • Turjanski AG; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.
  • Forli S; Dipartimento di Scienze della Salute, Università degli Studi "Magna Græcia," Viale Europa, Catanzaro, Italy.
  • Marti MA; Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.
Bioinformatics ; 35(19): 3836-3838, 2019 10 01.
Article in En | MEDLINE | ID: mdl-30825370
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.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Software Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2019 Type: Article Affiliation country: Argentina

Full text: 1 Database: MEDLINE Main subject: Software Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2019 Type: Article Affiliation country: Argentina