Guided structure-based ligand identification and design via artificial intelligence modeling.

Journal: Expert opinion on drug discovery
Published Date: Sep 23, 2021

Abstract

INTRODUCTION: The implementation of Artificial Intelligence (AI) methodologies to drug discovery (DD) are on the rise. Several applications have been developed for structure-based DD, where AI methods provide an alternative framework for the identification of ligands for validated therapeutic targets, as well as the design of ligands through generative models.

Authors

  • Juan I Di Filippo
    Computational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Pilar, Buenos Aires, Argentina; Austral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina.
  • Claudio N Cavasotto
    Computational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Pilar, Buenos Aires, Argentina; Facultad de Ciencias Biomédicas, and Facultad de Ingeniería, Universidad Austral, Pilar, Buenos Aires, Argentina; Austral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina. Electronic address: CCavasotto@austral.edu.ar.

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