Artificial Intelligence: A Novel Approach for Drug Discovery.

Journal: Trends in pharmacological sciences
Published Date: Jul 3, 2019

Abstract

Molecular dynamics (MD) simulations can mechanistically explain receptor function. However, the enormous data sets that they may imply can be a hurdle. Plante and colleagues (Molecules, 2019) recently described a machine learning approach to the analysis of MD simulations. The approach successfully classified ligands and identified functional receptor motifs and thus it seems promising for mechanism-based drug discovery.

Authors

  • Óscar Díaz
    ONEKIN Research Group, University of the Basque Country, UPV/EHU, Leioa, Spain. oscar.diaz@ehu.eu.
  • James A R Dalton
    Laboratory of Molecular Neuropharmacology and Bioinformatics, Unitat de Bioestadística and Institut de Neurociències, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain; Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, 08193, Bellaterra, Spain; Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.
  • Jesús Giraldo
    Institut de Neurociències - Unitat de Bioestadìstica, Universitat Autònoma de Barcelona, 08193, Cerdanyola del Vallès, Spain. jesus.giraldo@uab.es.

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