ArticleProtein science : a publication of the Protein Society2026
MAVISp: A modular structure-based framework for protein variant effects.
Article in Protein science : a publication of the Protein Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Interpreting the effects of DNA polymerase variants at the structural level.Molecular oncology · 2026Article
- Defining the molecular tolerance-to-damage landscape of SMARCA4 helicase genetic alterations.bioRxiv : the preprint server for biology · 2026Article
- Decoding phospho-regulation and flanking regions in autophagy-associated short linear motifs.Communications biology · 2025Article
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Authors and funding
33 authors.
Funding
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 (Multi-layered Assessment of VarIants by Structure for proteins), 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.