Some time ago, Simulations Plus, Inc., undertook a proof-of-principle study in which literature data on Plasmodium falciparum dihydroorotate dehydrogenase inhibitors was used in conjunction with phenotypic screening data [1] to identify a promising series of 3-aminopropylamino-4-quinalone antimalarial leads. Elaboration of this series produced several very active compounds, four of which were characterized in vitro with respect to five major cytochrome P450 (CYP) isoforms in a recombinant assay format. Oxidations were carried out in parallel with intact human liver microsomes (HLM) and the metabolites formed were analyzed by HPLC/mass spectrometry. The physicochemical characteristics of these compounds happen to make them particularly amenable to identification. This talk will describe how their predicted properties were used to assess how good the qualitative and quantitative agreement was between the metabolites obtained and what was expected based on our in silico models. The analysis workflow employed serves to illustrate how the multiple classification and regression models employed play off of each other in a realistic scenario as well as how ambiguities and apparent contradictions can be resolved.

Anticipating human metabolites in silico: An antimalarial case study

2019 Spring National Meeting

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