Modeling Promiscuity Based on in vitro Safety Pharmacology Profiling Data
Khalil Azzaoui, Jacques Hamon, Bernard Faller, Steven Whitebread, Edgar Jacoby, Andreas Bender, Jeremy L. Jenkins, László Urbán · ChemMedChem · 2007
This study describes a method for mining and modeling binding data obtained from a large panel of targets (in vitro safety pharmacology) to distinguish differences between promiscuous and selective compounds. Two naïve Bayes models for promiscuity and selectivity were generated and validated on a test set as well as publicly available drug databases. The model shows a higher score (lower promiscuity) for marketed drugs than for compounds in early development or compounds that failed during clinical development. Such models can be used in triaging high-throughput screening data or for lead optimization.