ArticleNature communications2020
Inferring the molecular and phenotypic impact of amino acid variants with MutPred2.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 541 papers.
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Who cites it
541 citing papers in PubMed, 823 citations in OpenAlex.
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- HTSNPedia: A Molecular Perspective and Risk Estimator Database for Hypertension-Associated Genes.Biochemical genetics · 2026Article
- Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation-Informed Protein Language Model.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
481 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors at 7 institutions in 3 countries.
Funding
Abstract
Identifying pathogenic variants and underlying functional alterations is challenging. To this end, we introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions over existing methods, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. Whilst its prioritization performance is state-of-the-art, a distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific aspects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the identification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neurodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism-driven studies of human inherited disease have the potential to significantly accelerate the discovery of clinically actionable variants.
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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.