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An In Silico Evaluation of Deleterious Nonsynonymous Single Nucleotide Polymorphisms in the ErbB3 Oncogene
1Bioinformatics Center, Department of Bioscience and Biotechnology, Banasthali University , Rajasthan, India .
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.
Insights
This study identifies critical single nucleotide polymorphisms (SNPs) in the ErbB3 gene, revealing potential cancer-driving mutations. These findings highlight specific ErbB3 variations impacting protein function and cancer development.
Area of Science:
- Genomics
- Molecular Biology
- Cancer Research
Background:
- ErbB3 is a key oncogenic target implicated in various cancers.
- Single nucleotide polymorphisms (SNPs) can alter protein function and contribute to disease.
- Nonsynonymous SNPs (nsSNPs) are particularly significant due to their impact on protein sequence and structure.
Purpose of the Study:
- To computationally evaluate the structural and functional consequences of SNPs in the ErbB3 gene.
- To identify specific nsSNPs and synonymous SNPs in ErbB3 that may affect protein function and splicing.
- To pinpoint critical mutations in ErbB3 associated with cancer development.
Main Methods:
- Analysis of 531 ErbB3 SNPs, focusing on 77 coding nsSNPs.
- Utilized SIFT and PolyPhen algorithms for predicting the functional impact of nsSNPs.
- Employed I-Mutant 3.0, MuStab, and iPTree-STAB for computing mutant protein stability.
- Applied FASTSNP to identify synonymous SNPs affecting splicing regulation.
Main Results:
- Identified 20 nsSNPs predicted to alter ErbB3 protein function.
- Seven crucial point mutations (V89M, V105G, C290Y, I418N, R669C, I744T, A1131T) were identified as nsSNPs.
- Discovered 14 synonymous SNPs with potential impacts on splicing regulation.
- Seven novel hotspots in ErbB3 were identified as potentially cancer-related if mutated.
Conclusions:
- The study computationally identified significant nsSNPs and synonymous SNPs in ErbB3.
- Specific ErbB3 mutations identified may play a role in cancer pathogenesis.
- These findings provide insights into ErbB3's role in cancer and potential diagnostic markers.
