MAVISp: A Modular Structure-Based Framework for Protein Variant Effects
Open accessPreprint — published as 10.1002/pro.70548
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 arIants 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 reusability. MAVISp currently provides data over 1000 proteins, encompassing more than eight million variants. A team of biocurators regularly analyzes and updates protein entries using standardized workflows, incorporating free energy calculations or 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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PDBminer to Find and Annotate Protein Structures for Computational Analysis
Degn, K., Beltrame, L., Tiberti, M., & Papaleo, E. (2023) · doi:10.1101/2023.05.06.539447 · Cited by 6 · see citing works
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- Authors
- Arnaudi, M., Utichi, M., Degn, K., Tiberti, M., Beltrame, L., Krzesińska, K., Sánchez-Izquierdo Besora, P., Kiachaki, E., Scrima, S., Bauer, L., Meldgård, K., Melidi, A., Favaro, L., Oswal, A., Tedeschi, G., Dorčaková, T., Estad, A. H., Breitenstein, J., Safer, J., Saridaki, P., Sora, V., Maselli, F., Becker, P., Vinhas, J., Pettenella, A., Lambrughi, M., Cava, C., Rohlin, A., Nilbert, M., Iqbal, S., Sackett, P. W., Fas, B. A., & Papaleo, E.
- Affiliations
- Danish Cancer Society (DK)
- Technical University of Denmark (DK)
- Cancer Structural Biology, Danish Cancer Institute, 2100, Copenhagen, Denmark
- University of Chemistry and Technology, Prague (CZ)
- Broad Institute (US)
- Laboratoire de Biochimie Théorique (FR)
- Institute of Molecular Bioimaging and Physiology (IT)
- Istituto Universitario di Studi Superiori di Pavia (IT)
- Sahlgrenska University Hospital (SE)
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
- Corresponding author
- Papaleo, Elena
- ORCID
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2022-10-24
- Volume
- 35
- Issue
- 5
- Pages
- e70548-e70548
- OpenAlex
- W4307280601
- Cited by
- 20
- References
- 10
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 2 · 2023: 5 · 2022: 2
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- European High Performance Computing Joint Undertaking
- Västra Götalandsregionen
- Danmarks Grundforskningsfond (DNRF125)
- Novo Nordisk Fonden (NNF20OC0065262)
- LEO Fondet (LF17006, DNRF125)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- protein variants, variants of uncertain significance, pathogenic variant prediction, protein structure, free energy calculation, biomolecular simulation, biocuration, web server, variant interpretation
- MeSH terms
- Humans, Mutation, Protein Conformation, Proteins, Software, Genetic Variation, Databases, Protein
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