ArticleBioResearch open access2013
An In Silico Evaluation of Deleterious Nonsynonymous Single Nucleotide Polymorphisms in the ErbB3 Oncogene.
Article in BioResearch open access, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- Trial
- Association Between ERBB2 and ERBB3 Polymorphisms and Dyslipidaemia and Serum Lipid Levels in a Chinese Population.Biochemical genetics · 2026Article
- Genetic Influences in Breast Cancer Drug Resistance.Breast cancer (Dove Medical Press) · 2021Review
- Risk prediction and marker selection in nonsynonymous single nucleotide polymorphisms using whole genome sequencing data.Animal cells and systems · 2020Article
- Molecular andF1000Research · 2018Article
- Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer.Scientific reports · 2017Article
- Molecular level understanding of resistance to nalidixic acid in Salmonella enteric serovar typhimurium associates with the S83F sequence type.European biophysics journal : EBJ · 2016Article
- Functional and Structural Consequences of Damaging Single Nucleotide Polymorphisms in Human Prostate Cancer Predisposition Gene RNASEL.BioMed research international · 2015Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ErbB3 is a significant oncogenic target that is involved in the development of numerous malignancies. In the present in silico study, we evaluated the structural and functional impact of single nucleotide polymorphisms (SNPs) on the ErbB3 gene. The nonsynonymous SNPs (nsSNPs) are known to be deleterious or disease-causing variations because they alter protein sequence, structure, and function. Out of a total 531 SNPs in ErbB3, we investigated 77 coding nsSNPs and observed that 20 of them could be expected to alter the protein's function based on the predictions of both sequence homology-based (SIFT) and structural homology-based (Polyphen) algorithms. Thereafter, we computed the stability of mutants in units of free energy using I-Mutant 3.0, MuStab, and iPTree-STAB programs and identified seven crucial point mutations (V89M, V105G, C290Y, I418N, R669C, I744T, and A1131T) in epidermal growth factor receptor 3 that are manifested as nsSNPs. Furthermore, FASTSNP determined 14 synonymous SNPs that may have a profound impact on splicing regulation. The computational study identified seven novel hotspots predicted to maintain the native structural conformation and functional activity of ErbB3 and may account for cancer if mutated.
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Registered trials
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