title: QSAR modeling: where have you been? Where are you going to?
abstract: Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.
authors.affiliation: Vancouver Prostate Centre, University of British Columbia , Vancouver, British Columbia, V6H3Z6, Canada.
authors.forename: Artem
authors.initials: A
authors.lastname: Cherkasov
authors.forename: Eugene N
authors.initials: EN
authors.lastname: Muratov
authors.forename: Denis
authors.initials: D
authors.lastname: Fourches
authors.forename: Alexandre
authors.initials: A
authors.lastname: Varnek
authors.forename: Igor I
authors.initials: II
authors.lastname: Baskin
authors.forename: Mark
authors.initials: M
authors.lastname: Cronin
authors.forename: John
authors.initials: J
authors.lastname: Dearden
authors.forename: Paola
authors.initials: P
authors.lastname: Gramatica
authors.forename: Yvonne C
authors.initials: YC
authors.lastname: Martin
authors.forename: Roberto
authors.initials: R
authors.lastname: Todeschini
authors.forename: Viviana
authors.initials: V
authors.lastname: Consonni
authors.forename: Victor E
authors.initials: VE
authors.lastname: Kuz'min
authors.forename: Richard
authors.initials: R
authors.lastname: Cramer
authors.forename: Romualdo
authors.initials: R
authors.lastname: Benigni
authors.forename: Chihae
authors.initials: C
authors.lastname: Yang
authors.forename: James
authors.initials: J
authors.lastname: Rathman
authors.forename: Lothar
authors.initials: L
authors.lastname: Terfloth
authors.forename: Johann
authors.initials: J
authors.lastname: Gasteiger
authors.forename: Ann
authors.initials: A
authors.lastname: Richard
authors.forename: Alexander
authors.initials: A
authors.lastname: Tropsha
mesh_terms: D023181:Antimicrobial Cationic Peptides / Q000737:chemistry; D001185:Artificial Intelligence; D045424:Complex Mixtures / Q000737:chemistry; D016208:Databases, Factual; D015195:Drug Design; D049673:History, 20th Century; D049674:History, 21st Century; D008958:Models, Molecular; D049329:Nanostructures / Q000737:chemistry; D010599:Pharmacokinetics; D021281:Quantitative Structure-Activity Relationship; D011789:Quantum Theory; D014116:Toxicology / Q000379:methods
chemical_list: D023181:Antimicrobial Cationic Peptides; D045424:Complex Mixtures