ArticleHuman mutation2015
On human disease-causing amino acid variants: statistical study of sequence and structural patterns.
Article in Human mutation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
85 citing papers in PubMed, 173 citations in OpenAlex.
- A simple probabilistic AlphaFold interaction score.Protein science : a publication of the Protein Society · 2026Article
- Why variant effect predictors and multiplexed assays agree and disagree.Nature communications · 2026Article
- Generative Protein Design: From Deep Learning Algorithms to Translational Applications.International journal of molecular sciences · 2026Review
- Beyond contacts: The important role of the support region in protein complex assembly.Protein science : a publication of the Protein Society · 2026Article
- Modeling the Effects of Single Nucleotide Polymorphisms (SNPs) on the Structure and Function of the HumanHuman mutation · 2026Article
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- Classification of driver and passenger mutations in different cancer types using deep neural networks.Bioinformatics advances · 2026Article
- Potentially Deleterious Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs) in the HumanHuman mutation · 2026Article
- Genetic and functional evidence implicates amedRxiv : the preprint server for health sciences · 2025Article
- Functional and Structural Characterization of Pathogenicity of Human Arginine-Histidine Variants.Journal of computational biophysics and chemistry · 2025Article
- Calibrated Variant Effect Prediction at the Residue Level Using Conditional Score Distributions.bioRxiv : the preprint server for biology · 2025Article
- Comprehensive computational analysis of PKCδ non-synonymous variants identifies rs1703863535 as a potential breast cancer biomarker.BMC cancer · 2025Article
- Benchmarking Free Energy Calculations: Analysis of Single and Double Mutations Across Two Simulation Software Platforms for Two Protein Systems.bioRxiv : the preprint server for biology · 2025Article
- Impact of frequent ARID1A mutations on protein stability provides insights into cancer pathogenesis.Scientific reports · 2025Article
- Challenges in bridging the gap between protein structure prediction and functional interpretation.Proteins · 2025Article
- Impact of Frequent ARID1A Mutations on Protein Stability: Insights into Cancer Pathogenesis.Research square · 2024Article
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- AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.Human genomics · 2024Article
- SAAMBE-MEM: a sequence-based method for predicting binding free energy change upon mutation in membrane protein-protein complexes.Bioinformatics (Oxford, England) · 2024Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Statistical analysis was carried out on large set of naturally occurring human amino acid variations, and it was demonstrated that there is a preference for some amino acid substitutions to be associated with diseases. At an amino acid sequence level, it was shown that the disease-causing variants frequently involve drastic changes in amino acid physicochemical properties of proteins such as charge, hydrophobicity, and geometry. Structural analysis of variants involved in diseases and being frequently observed in human population showed similar trends: disease-causing variants tend to cause more changes in hydrogen bond network and salt bridges as compared with harmless amino acid mutations. Analysis of thermodynamics data reported in the literature, both experimental and computational, indicated that disease-causing variants tend to destabilize proteins and their interactions, which prompted us to investigate the effects of amino acid mutations on large databases of experimentally measured energy changes in unrelated proteins. Although the experimental datasets were linked neither to diseases nor exclusory to human proteins, the observed trends were the same: amino acid mutations tend to destabilize proteins and their interactions. Having in mind that structural and thermodynamics properties are interrelated, it is pointed out that any large change in any of them is anticipated to cause a disease.
Indexed as
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What OpenQuestion holds
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.