Genomic landscape of drug binding and pharmacogenetic variation across diverse populations using SNPdrug3D.

Abstract

One of the promises of precision medicine is to understand and act on inter-individual genetic differences in drug responses. SNPdrug3D contains the complete genomic landscape of missense single nucleotide variants (SNV) across the human proteome and at a population-wide level that could affect drug binding. Here, we map SNVs in over 80,000 individuals from the Singapore SG10K Health and gnomAD cohorts to identify ~1.17 million variants mapped to residues near ~6000 bound drugs in protein-drug complexes and experimentally verify effects of selected SNVs, including previously uncharacterized variants, on drug binding in relevant proteins ranging from kinases to cytochrome P450s (CYPs). The latter led to a specific predictor for interpreting variants in the CYP family that outperforms existing tools in the prediction of pharmacogenetic effects based on database-annotated (AUROC = 0.9) or assay-based (AUROC = 0.8) test sets. By placing variants and drugs in structural contexts, SNPdrug3D aids drug development by pre-emptively flagging potential resistance sites based on population-specific variability.