In-silico screening and analysis of missense SNPs in human CYP3A4/5 affecting drug-enzyme interactions of FDA-approved COVID-19 antiviral drugs - Amro A. Abdelazim; Mohamad Maged; Ahmed I. Abdelmaksoud; Sameh E. Hassanein (Scientific Reports)
Abstract Single nucleotide polymorphisms (SNPs) represent the prevailing form of genetic variations observed in the human population. Such variations could alter the encoded enzymes’ activities. CYP3A4/5 enzymes are involved in metabolizing drugs, notably antivirals against SARS-CoV-2. In this work, we computationally investigated antiviral-enzyme interactions of CYP3A4/5 genetic variants. We also examined the deleterious impact of 751 missense single nucleotide polymorphisms (SNPs) within the CYP3A4/5 genes. An ensemble of bioinformatics tools, [SIFT, PolyPhen-2, cadd, revel, metaLr, mutation assessor, Panther, SNP&GO, PhD-SNP, SNAP, Meta-SNP, FATHMM, I-Mutant, MuPro, INPS, CONSURF, GPS 5.0, MusiteDeep and NetPhos], identified a total of 94 variants (47 SNPs in CYP3A4, 47 SNPs in CYP3A5) to potentially impact the structural integrity as well as the activity of the CYP3A4/5 enzymes. Molecular docking was done to recognize the structural stability and binding properties of the CYP3A4/5 protein isoforms with 3 FDA-approved antiviral drugs. Our findings indicated that the CYP3A4 gene variants; R418T, I335T and R130P and the CYP3A5 gene variants; I335T, L133P and R130Q are considered the most deleterious missense SNPs. These mutants potentially affect drug-enzyme binding and hence may alter therapeutic response. Cataloguing deleterious SNPs is essential for personalized gene-based pharmacotherapy.