Interpreting human genetic variation at atomic resolution.

Computational structural genomics: models of gene products and their organization in biomolecular complexes, integrating sequences, motifs, domains, molecular structures, molecular dynamics simulations, multi-omics annotations and artificial intelligence-driven tools

The widespread adoption of clinical sequencing and large-scale national and international genomics initiatives has transformed genomic medicine, yet interpretation of many variants remains limited. 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, using models of gene products and their organization within biomolecular complexes of protein, DNA, RNA and small molecules. In this Perspective, the authors highlight how CSG has yielded a comprehensive, mechanistic understanding of how interindividual genetic variants function, by integrating sequence information, motifs, domains, molecular structures, molecular dynamics simulations, multi-omics annotations and artificial intelligence-driven tools. These technologies enable prediction of variant effects at atomic resolution and support their simultaneous classification according to mechanisms of dysfunction.

Synthesis written by Geno'X. For the full original abstract, please refer to the source publication.

Moving from static annotation to a mechanism of dysfunction addresses a real limit that the authors state upfront: interpretation of many variants remains limited despite large-scale clinical sequencing. This is, however, a Perspective: the abstract describes no documented literature search, no number of studies, no quantified tool performance and no validation on patient data. Predicting an effect at atomic resolution does not yet say what ACMG/AMP level of evidence to draw from it, and that conversion will determine use in the laboratory.

Analysis by Dr Thibaut Benquey