Use of machine learning approaches for novel drug discovery.

Journal: Expert opinion on drug discovery
Published Date:

Abstract

INTRODUCTION: The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds.

Authors

  • Angélica Nakagawa Lima
    a Centro de Ciências Naturais e Humanas , Universidade Federal do ABC , São Paulo , Brazil.
  • Eric Allison Philot
    a Centro de Ciências Naturais e Humanas , Universidade Federal do ABC , São Paulo , Brazil.
  • Gustavo Henrique Goulart Trossini
    b Departamento de Farmácia, Faculdade de Ciências Farmacêuticas , Universidade de São Paulo , São Paulo , Brazil.
  • Luis Paulo Barbour Scott
    c Centro de Matemática, Computação e Cognição , Universidade Federal do ABC , São Paulo , Brazil.
  • Vinícius Gonçalves Maltarollo
    Federal University of ABC (UFABC), Centre for Natural Sciences and Humanities , Santa Adélia Street, 166, Bangu, Santo André -SP , Brazil.
  • Kathia Maria Honorio