Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening
Clara Blanes-Mira,
Pilar Fernández-Aguado,
Jorge de Andrés-López,
Asia Fernández-Carvajal,
Antonio Ferrer-Montiel,
Gregorio Fernández-Ballester
Affiliations
Clara Blanes-Mira
Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE), Universidad Miguel Hernández, Av. de la Universidad s/n, 03202 Elche, Spain
Pilar Fernández-Aguado
Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE), Universidad Miguel Hernández, Av. de la Universidad s/n, 03202 Elche, Spain
Jorge de Andrés-López
Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE), Universidad Miguel Hernández, Av. de la Universidad s/n, 03202 Elche, Spain
Asia Fernández-Carvajal
Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE), Universidad Miguel Hernández, Av. de la Universidad s/n, 03202 Elche, Spain
Antonio Ferrer-Montiel
Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE), Universidad Miguel Hernández, Av. de la Universidad s/n, 03202 Elche, Spain
Gregorio Fernández-Ballester
Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE), Universidad Miguel Hernández, Av. de la Universidad s/n, 03202 Elche, Spain
The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.