AUTHOR=Seo Myung-Eui , Min Byung-Joo , Heo Nayoon , Lee Kye Hwa , Kim Ju Han
TITLE=Comprehensive in vitro and in silico assessments of metabolic capabilities of 24 genomic variants of CYP2C19 using two different substrates
JOURNAL=Frontiers in Pharmacology
VOLUME=14
YEAR=2023
URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2023.1055991
DOI=10.3389/fphar.2023.1055991
ISSN=1663-9812
ABSTRACT=Introduction: Most hepatically cleared drugs are metabolized by cytochromes P450 (CYPs), and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provide curated clinical references for CYPs to apply individual genome data for optimized drug therapy. However, incorporating novel pharmacogenetic variants into guidelines takes considerable time.
Methods: We comprehensively assessed the drug metabolizing capabilities of CYP2C19 variants discovered through population sequencing of two substrates, S-mephenytoin and omeprazole.
Results: Based on established functional assays, 75% (18/24) of the variants not yet described in Pharmacogene Variation (PharmVar) had significantly altered drug metabolizing capabilities. Of them, seven variants with inappreciable protein expression were evaluated as protein damaging by all three in silico prediction algorithms, Sorting intolerant from tolerant (SIFT), Polymorphism Phenotyping v2 (PolyPhen-2), and Combined annotation dependent depletion (CADD). The five variants with decreased metabolic capability (<50%) of wild type for either substrates were evaluated as protein damaging by all three in silico prediction algorithms, except CADD exact score of NM_000769.4:c.593T>C that was 19.68 (<20.0). In the crystal structure of the five polymorphic proteins, each altered residue of all those proteins was observed to affect the key structures of drug binding specificity. We also identified polymorphic proteins indicating different tendencies of metabolic capability between the two substrates (5/24).
Discussion: Therefore, we propose a methodology that combines in silico prediction algorithms and functional assays on polymorphic CYPs with multiple substrates to evaluate the changes in the metabolism of all possible genomic variants in CYP genes. The approach would reinforce existing guidelines and provide information for prescribing appropriate medicines for individual patients.