ArticlePloS one2013
Cancer missense mutations alter binding properties of proteins and their interaction networks.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 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
71 citing papers in PubMed, 126 citations in OpenAlex.
- Predicting interaction-specific protein-protein interaction perturbations by missense variants with MutPred-PPI.bioRxiv : the preprint server for biology · 2026Article
- Uncovering genetic variations in HTR2A and miRNAs drivers of breast cancer risk in African American women.Journal of breast cancer research · 2026Article
- DBP-CanPred: a machine learning model for predicting cancer-causing mutations in DNA-binding proteins.Frontiers in bioinformatics · 2026Article
- AI cancer driver mutation predictions are valid in real-world data.Nature communications · 2025Article
- Decoding the effects of mutation on protein interactions using machine learning.Biophysics reviews · 2025Review
- Identification of molecular targets of Trigonelline for treating breast cancer through network pharmacology and bioinformatics-based prediction.Molecular diversity · 2024Article
- AAindexNC: Estimating the Physicochemical Properties of Non-Canonical Amino Acids, Including Those Derived from the PDB and PDBeChem Databank.International journal of molecular sciences · 2024Article
- Pathogenic nsSNPs of protein kinase C-eta with hepatocellular carcinoma susceptibility.Cancer cell international · 2024Article
- Review
- Strength of selection in lung tumors correlates with clinical features better than tumor mutation burden.Scientific reports · 2024Article
- DeepPPAPredMut: deep ensemble method for predicting the binding affinity change in protein-protein complexes upon mutation.Bioinformatics (Oxford, England) · 2024Article
- Computational analysis of protein-protein interactions of cancer drivers in renal cell carcinoma.FEBS open bio · 2024Article
- Article
- Cancer driver mutations: predictions and reality.Trends in molecular medicine · 2023Review
- A mutation-induced drug resistance database (MdrDB).Communications chemistry · 2023Article
- PROT-ON: A structure-based detection of designer PROTein interface MutatiONs.Frontiers in molecular biosciences · 2023Article
- ASCARIS: Positional feature annotation and protein structure-based representation of single amino acid variations.Computational and structural biotechnology journal · 2023Article
- Analyses of Mutation Displacements from Homology Models.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.Frontiers in genetics · 2023Article
- Computed cancer interactome explains the effects of somatic mutations in cancers.Protein science : a publication of the Protein Society · 2022Article
11 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
8 authors at 5 institutions in 2 countries.
Funding
Abstract
Many studies have shown that missense mutations might play an important role in carcinogenesis. However, the extent to which cancer mutations might affect biomolecular interactions remains unclear. Here, we map glioblastoma missense mutations on the human protein interactome, model the structures of affected protein complexes and decipher the effect of mutations on protein-protein, protein-nucleic acid and protein-ion binding interfaces. Although some missense mutations over-stabilize protein complexes, we found that the overall effect of mutations is destabilizing, mostly affecting the electrostatic component of binding energy. We also showed that mutations on interfaces resulted in more drastic changes of amino acid physico-chemical properties than mutations occurring outside the interfaces. Analysis of glioblastoma mutations on interfaces allowed us to stratify cancer-related interactions, identify potential driver genes, and propose two dozen additional cancer biomarkers, including those specific to functions of the nervous system. Such an analysis also offered insight into the molecular mechanism of the phenotypic outcomes of mutations, including effects on complex stability, activity, binding and turnover rate. As a result of mutated protein and gene network analysis, we observed that interactions of proteins with mutations mapped on interfaces had higher bottleneck properties compared to interactions with mutations elsewhere on the protein or unaffected interactions. Such observations suggest that genes with mutations directly affecting protein binding properties are preferably located in central network positions and may influence critical nodes and edges in signal transduction networks.
Indexed as
Identifiers
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.