ArticlePloS one2024
Benchmarking AlphaMissense pathogenicity predictions against cystic fibrosis variants.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 32 citations in OpenAlex.
- A comprehensive map of missense trafficking variants in rhodopsin and their response to pharmacologic correction.Science advances · 2026Article
- AlphaMissense prediction for the evaluation of missense variants in the diagnostic setting of neuromuscular disorders.Journal of neuromuscular diseases · 2026Article
- Characterization of two ultra-rare CFTR variants, P.Leu999del and P.Glu1104Lys, with unknown theratyping profiles.Orphanet journal of rare diseases · 2026Article
- VUStruct: A compute pipeline for high throughput and personalized structural biology.PLoS computational biology · 2026Article
- The p.(Leu97Ile) variant expands the genetic landscape of NEFL-associated Charcot-Marie-tooth neuropathies.Human molecular genetics · 2026Article
- Gene-specific pathogenicity predictor for chromatin remodeling BAF complex-associated neurodevelopmental disorders.HGG advances · 2026Article
- High-throughput biochemical phenotyping of SHP2 variants reveals the molecular basis of diseases and allosteric drug inhibition.bioRxiv : the preprint server for biology · 2026Article
- Deciphering gain-of-function from loss-of-function variants with AlphaMissense: A case study with the mechanosensitive PIEZO1 ion channel protein.Biochemistry and biophysics reports · 2026Article
- Leveraging in-silico deep learning and computational analyses to predict the pathogenicity of ROBO4 variants of uncertain significance in aortic aneurysm and dissection patients.BMC cardiovascular disorders · 2026Article
- DyVarMap: Integrating Conformational Dynamics and Interpretable Machine Learning for Cancer-Associated Missense Variant Classification in FGFR2.Bioengineering (Basel, Switzerland) · 2026Article
- Classification models distinguish functional and trafficking effects of KCNQ1 variants to enhance variant interpretation.bioRxiv : the preprint server for biology · 2025Article
- Gene Specific Pathogenicity Predictor for Chromatin-Remodeling BAF Complex-Associated Neurodevelopmental Disorders.bioRxiv : the preprint server for biology · 2025Article
- Benchmarking AlphaMissense pathogenicity predictions againstBiochemistry and biophysics reports · 2025Article
- Detection of protein structural hotspots using AI distillation and explainability: application to the DAX-1 protein.NAR genomics and bioinformatics · 2025Article
- Recent developments in cystic fibrosis drug discovery: where are we today?Expert opinion on drug discovery · 2025Review
- Proteostasis landscapes of cystic fibrosis variants reveal drug response vulnerability.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- A novel seven-tier framework for the classification of MEFV missense variants using adaptive and rigid classifiers.Scientific reports · 2025Article
- Proteostasis Landscapes of Cystic Fibrosis Variants Reveals Drug Response Vulnerability.bioRxiv : the preprint server for biology · 2025Article
- Genetic variant classification by predicted protein structure: A case study on IRF6.Computational and structural biotechnology journal · 2024Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Variants in the cystic fibrosis transmembrane conductance regulator gene (CFTR) result in cystic fibrosis-a lethal autosomal recessive disorder. Missense variants that alter a single amino acid in the CFTR protein are among the most common cystic fibrosis variants, yet tools for accurately predicting molecular consequences of missense variants have been limited to date. AlphaMissense (AM) is a new technology that predicts the pathogenicity of missense variants based on dual learned protein structure and evolutionary features. Here, we evaluated the ability of AM to predict the pathogenicity of CFTR missense variants. AM predicted a high pathogenicity for CFTR residues overall, resulting in a high false positive rate and fair classification performance on CF variants from the CFTR2.org database. AM pathogenicity score correlated modestly with pathogenicity metrics from persons with CF including sweat chloride level, pancreatic insufficiency rate, and Pseudomonas aeruginosa infection rate. Correlation was also modest with CFTR trafficking and folding competency in vitro. By contrast, the AM score correlated well with CFTR channel function in vitro-demonstrating the dual structure and evolutionary training approach learns important functional information despite lacking such data during training. Different performance across metrics indicated AM may determine if polymorphisms in CFTR are recessive CF variants yet cannot differentiate mechanistic effects or the nature of pathophysiology. Finally, AM predictions offered limited utility to inform on the pharmacological response of CF variants i.e., theratype. Development of new approaches to differentiate the biochemical and pharmacological properties of CFTR variants is therefore still needed to refine the targeting of emerging precision CF therapeutics.
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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.