title: A data mining method to facilitate SAR transfer.
abstract: A challenging practical problem in medicinal chemistry is the transfer of SAR information from one chemical series to another. Currently, there are no computational methods available to rationalize or support this process. Herein, we present a data mining approach that enables the identification of alternative analog series with different core structures, corresponding substitution patterns, and comparable potency progression. Scaffolds can be exchanged between these series and new analogs suggested that incorporate preferred R-groups. The methodology can be applied to search for alternative analog series if one series is known or, alternatively, to systematically assess SAR transfer potential in compound databases.
authors.affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, Germany.
authors.forename: Anne Mai
authors.initials: AM
authors.lastname: Wassermann
authors.forename: Jürgen
authors.initials: J
authors.lastname: Bajorath
mesh_terms: D000465:Algorithms; D002626:Chemistry, Pharmaceutical / Q000379:methods*; D003198:Computer Simulation; D057225:Data Mining; D016208:Databases, Factual; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D004791:Enzyme Inhibitors / Q000737:chemistry / Q000494:pharmacology; D006801:Humans; D008956:Models, Chemical; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000032:analysis* / Q000737:chemistry; D011506:Proteins / Q000037:antagonists & inhibitors / Q000737:chemistry / Q000378:metabolism; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D004791:Enzyme Inhibitors; D004364:Pharmaceutical Preparations; D011506:Proteins