Metabolic Soft Spot Identification and Compound Optimization in Early Discovery Phases Using MetaSite and LC-MS/MS Validation

Abstract

Metabolic stability is a key property to enable drugs to reach therapeutic concentrations. Microsomal clearance assays are used to dial out labile compounds in early discovery phases. However, because they do not provide any information on soft spots, the rational design of more stable compounds remains challenging. A robust soft spot identification procedure combining in silico prediction ranking using MetaSite and mass-spectrometric confirmation is described. MetaSite's first rank order predictions were experimentally confirmed for only about 55% of the compounds. For another 29% of the compounds, the second (20%) or the third (9%) rank order predictions were detected. This automatic and high-throughput reprioritization of a likely soft-spot increases the likelihood of working on the right soft spot from about 50% to more than 80%. With this information, the structure-metabolism relationships are likely to be understood faster and earlier in drug discovery.