Machine Learning-Based Scoring Functions, Development and Applications with SAnDReS.

Journal: Current medicinal chemistry
Published Date:

Abstract

BACKGROUND: Analysis of atomic coordinates of protein-ligand complexes can provide three-dimensional data to generate computational models to evaluate binding affinity and thermodynamic state functions. Application of machine learning techniques can create models to assess protein-ligand potential energy and binding affinity. These methods show superior predictive performance when compared with classical scoring functions available in docking programs.

Authors

  • Gabriela Bitencourt-Ferreira
    Laboratory of Computational Systems Biology, School of Sciences, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Av. Ipiranga, 6681, Porto Alegre, RS 90619-900, Brazil.
  • Camila Rizzotto
    Pontifical Catholic University of Rio Grande do Sul - PUCRS, Porto Alegre-RS, Brazil.
  • Walter Filgueira de Azevedo Junior
    Pontifical Catholic University of Rio Grande do Sul - PUCRS, Porto Alegre-RS, Brazil.