title: Desirability-based multi-objective QSAR in drug discovery.
abstract: The adjustment of multiple criteria in hit-to-lead identification and lead optimization is a major advance in drug discovery. Thus, the development of approaches able to handle additional criteria for the early simultaneous treatment of the most important properties determining the pharmaceutical profile of a drug candidate is an emergent issue in this area. In this paper, we review a desirability-based multi-objective QSAR method allowing the joint handling of multiple properties of interest in drug discovery: the MOOP-DESIRE methodology. This methodology adapts desirability theory concepts allowing the holistic modeling of the many and conflicting biological properties determining the therapeutic utility of a drug candidate. Here we survey their suitability for key tasks involving the use of chemoinformatics methods in medicinal chemistry and drug discovery.
authors.affiliation: Departamento de Química, FCUP, Rua do Campo Alegre, 687, 4169-007 Porto, Portugal. maikelcm@uclv.edu.cu
authors.forename: Maykel
authors.initials: M
authors.lastname: Cruz-Monteagudo
authors.forename: M Natalia D S
authors.initials: MN
authors.lastname: Cordeiro
authors.forename: Eduardo
authors.initials: E
authors.lastname: Tejera
authors.forename: Elena Rosa
authors.initials: ER
authors.lastname: Dominguez
authors.forename: Fernanda
authors.initials: F
authors.lastname: Borges
mesh_terms: D000465:Algorithms; D000818:Animals; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D021281:Quantitative Structure-Activity Relationship