The role of genomic variants in disease, including cancer, continues to expand thanks to the advent of advanced sequencing techniques integrated into clinical practice. The rapid growth in the identification of genomic variants has led to the classification of many variants as Variants of Uncertain Significance (VUS) or with conflicting evidence, posing challenges in their interpretation and application. Here we introduce MAVISp ( M ulti-layered A ssessment of V arIants by S tructure for p roteins), a modular structural framework for variant interpretation. We also provide a web server ( https://services.healthtech.dtu.dk/services/MAVISp-1.0/ ), to enhance data accessibility, consultation, and re-usability. Currently, MAVISp offers analyses for more than 200 different proteins, encompassing approximately 85000 variants. A dedicated team of biocurators and reviewers continuously analyze and update protein targets using standardized workflows, incorporating high-throughput free energy calculations or biomolecular simulations. Here, we illustrate the potential of the MAVISp approach through a selection of case studies. Our framework aids in the interpretation of genomic variants, particularly those categorized as VUS, and holds great potential for advancing the understanding and application of genomics in disease research.

MAVISp: A Modular Structure-Based Framework for Genomic Variant Interpretation