In-silico analysis of nsSNPs in human CYP3A4/5 and their effects on drug-enzymes interactions of FDA-approved COVID-19 antiviral drugs: A pharmacogenetic study

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 have a pivotal role in metabolising 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 non-synonymous single nucleotide polymorphisms (nsSNPs) within the CYP3A4/5 genes. An ensemble of bioinformatics tools, [SIFT, PolyPhen, cadd, revel, metaLr, mutation assessor, Panther, SNP&GO, PhD-SNP, SNAP, Meta-SNP, FATHMM, I-Mutante, MuPro, INPS, CONSURF, GPS 5.0, MusiteDeep and NetPhos], identified a total of 94 variants (47 nsSNPs in CYP3A4, 47 nsSNPs 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. It was concluded that for the gene CYP3A4; the variants R418T, I335T and R130P while the CYP3A5 SNPs; I335T, L133P and R130Q are considered the most deleterious nsSNPs, potentially affecting drug-binding. Cataloguing deleterious SNPs is vital for personalized gene-based pharmacotherapy.