ArticleScientific reports2020
Identification of pathogenic missense mutations using protein stability predictors.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed.
- Disease-associated genetic variants can cause missense effects in tissue-specific protein isoforms.Nature communications · 2026Article
- Actually, what is a gain-of-function mutation?Genetics · 2026Article
- Screen for signatures of positive selection in the core genome ofMicrobial genomics · 2026Article
- HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction.bioRxiv : the preprint server for biology · 2026Article
- Functional assessment of protein variants in structured domains by fluorescence cross-correlation spectroscopy.Scientific reports · 2026Article
- Uncovering differential tolerance to deletions versus substitutions with a protein language model.Cell systems · 2025Article
- ConPath 2.0: an optimized consensus strategy for assessing the potential pathogenicity of hRPE65 missense variants.Journal of molecular modeling · 2025Article
- Pantethine ameliorates dilated cardiomyopathy features in PPCS deficiency disorder in patients and cell line models.Communications medicine · 2025Article
- Computational prediction of deleterious nonsynonymous SNPs in the CTNS gene: implications for cystinosis.BMC genomic data · 2025Article
- ACMG/AMP interpretation of BRCA1 missense variants: Structure-informed scores add evidence strength granularity to the PP3/BP4 computational evidence.American journal of human genetics · 2025Article
- A new view of missense mutations in α-mannosidosis using molecular dynamics conformational ensembles.Protein science : a publication of the Protein Society · 2025Article
- QAFI: a novel method for quantitative estimation of missense variant impact using protein-specific predictors and ensemble learning.Human genetics · 2025Article
- Assessing the predicted impact of single amino acid substitutions in calmodulin for CAGI6 challenges.Human genetics · 2025Article
- Use of patient-derived cell models for characterization of compound heterozygous hypomorphic C2CD3 variants in a patient with isolated nephronophthisis.Human molecular genetics · 2025Article
- Exploring the impact of deleterious missense nonsynonymous single nucleotide polymorphisms in the DRD4 gene using computational approaches.Scientific reports · 2025Article
- Exploring Evolution to Uncover Insights Into Protein Mutational Stability.Molecular biology and evolution · 2025Article
- Restoring adapter protein complex 4 function with small molecules: an in silico approach to spastic paraplegia 50.Protein science : a publication of the Protein Society · 2025Article
- Complementary Roles of Structure and Variant Effect Predictors in RyR1 Clinical Interpretation.Human mutation · 2025Article
- A methodology for calculating the rarity of diverse proteins based on functional specificity and thermodynamic stability.PloS one · 2025Article
- Using AI-predicted protein structures as a reference to predict loss-of-function activity in tumor suppressor breast cancer genes.Computational and structural biotechnology journal · 2024Article
12 more citing papers are in PubMed but not listed here.
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3 authors.
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Abstract
Attempts at using protein structures to identify disease-causing mutations have been dominated by the idea that most pathogenic mutations are disruptive at a structural level. Therefore, computational stability predictors, which assess whether a mutation is likely to be stabilising or destabilising to protein structure, have been commonly used when evaluating new candidate disease variants, despite not having been developed specifically for this purpose. We therefore tested 13 different stability predictors for their ability to discriminate between pathogenic and putatively benign missense variants. We find that one method, FoldX, significantly outperforms all other predictors in the identification of disease variants. Moreover, we demonstrate that employing predicted absolute energy change scores improves performance of nearly all predictors in distinguishing pathogenic from benign variants. Importantly, however, we observe that the utility of computational stability predictors is highly heterogeneous across different proteins, and that they are all inferior to the best performing variant effect predictors for identifying pathogenic mutations. We suggest that this is largely due to alternate molecular mechanisms other than protein destabilisation underlying many pathogenic mutations. Thus, better ways of incorporating protein structural information and molecular mechanisms into computational variant effect predictors will be required for improved disease variant prioritisation.
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