Exploring Scoring Function Space: Developing Computational Models for Drug Discovery

BITENCOURT-FERREIRA, GABRIELA; VILLARREAL, MARCOS A.; QUIROGA, RODRIGO; BIZIUKOVA, NADEZHDA; POROIKOV, VLADIMIR; TARASOVA, OLGA; DE AZEVEDO JUNIOR, WALTER FILGUEIRA

CURRENT MEDICINAL CHEMISTRY.

BENTHAM SCIENCE PUBL LTD

Año: 2023 vol. 30

0929-8673

ackground: The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery.Objective: Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity.Methods: We searched the articles available in PubMed related to the scoring function space. We also utilized crystallographic structures found in the protein data bank (PDB) to represent the protein space.Results: The application of systems-level approaches to address receptor-drug interactions allows us to have a holistic view of the process of drug discovery. The scoring function space adds flexibility to the process since it makes it possible to see drug discovery as a relationship involving mathematical spaces.Conclusion: The application of the concept of scoring function space has provided us with an integrate