Interpreting human genetic variation at atomic resolution.

Abstract

The widespread adoption of clinical sequencing and large-scale national and international genomics initiatives has transformed genomic medicine. These efforts have enabled new diagnostic tests and computational tools for processing sequencing-derived information, yet interpretation of many variants remains limited. In parallel, over the last two decades, computational structural genomics (CSG) has emerged as a complementary approach that shifts from static genetic annotation to dynamic, mechanistic interpretation by leveraging models of gene products and their organization within biomolecular complexes of protein, DNA, RNA and small molecules. In this Perspective, we highlight how CSG has resulted in a comprehensive and mechanistic understanding of how interindividual genetic variants function, by integrating sequence information, motifs, domains, molecular structures, molecular dynamics simulations, multi-omics data annotations and artificial intelligence-driven tools. These advanced technologies enable prediction of variant effects at atomic resolution and support simultaneous classification according to their mechanisms of dysfunction.