MAVISp : A modular structure‐based framework for protein variant effects

Abstract The role of genomic variants in disease has expanded significantly with the advent of advanced sequencing techniques. The rapid increase in identified genomic variants has led to many variants being classified as Variants of Uncertain Significance or as having conflicting evidence, posing challenges for their interpretation and characterization. Additionally, current methods for predicting pathogenic variants often lack insights into the underlying molecular mechanisms. Here, we introduce MAVISp ( M ulti‐layered A ssessment of V ar I ants by S tructure for p roteins), a modular structural framework for variant effects, accompanied by a web server ( https://services.healthtech.dtu.dk/services/MAVISp-1.0/ ) to enhance data accessibility, consultation, and re‐usability. MAVISp currently provides data on over 1000 proteins, encompassing more than 10 million variants. A team of biocurators regularly analyzes and updates protein entries using standardized workflows, incorporating free‐energy calculations and biomolecular simulations. We illustrate the utility of MAVISp through selected case studies. The framework facilitates the analysis of variant effects at the protein level and has the potential to advance the understanding and application of mutational data in disease research.