In silico analysis of non-synonymous single nucleotide polymorphisms of human DEFB1 gene

Subbiah, Harini Venkata; Babu, P. B. Ramesh; Usha, S.

doi:10.1186/s43042-020-00110-3

Cited by 21 publications

(18 citation statements)

References 36 publications

(37 reference statements)

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“…The I-MUTANT 3.0 suit (https://bio.tools/i-mutant_suite) was utilized to prognosticate the impact of mutations on the stability of the HRAS protein, with the MUpro program (https://mupro. proteomics.ics.uci.edu/) being employed to validate the outcomes (Venkata Subbiah et al, 2020). Both servers rely on the same algorithm and are designed to evaluate the influence of mutations on protein stability, whether it is enhancing or diminishing it (Dehouck et al, 2011).…”

Section: Influence Of Non-synonymous Mutations On Protein Stability (...mentioning

confidence: 99%

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function

Ali¹,

Ali²,

Qamar³

et al. 2023

Front. Chem.

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The HRAS gene plays a crucial role in regulating essential cellular processes for life, and this gene's misregulation is linked to the development of various types of cancers. Nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of HRAS can cause detrimental mutations that disrupt wild-type protein function. In the current investigation, we have employed in-silico methodologies to anticipate the consequences of infrequent genetic variations on the functional properties of the HRAS protein. We have discovered a total of 50 nsSNPs, of which 23 were located in the exon region of the HRAS gene and denoting that they were expected to cause harm or be deleterious. Out of these 23, 10 nsSNPs ([G60V], [G60D], [R123P], [D38H], [I46T], [G115R], [R123G], [P11OL], [A59L], and [G13R]) were identified as having the most delterious effect based on results of SIFT analysis and PolyPhen2 scores ranging from 0.53 to 69. The DDG values −3.21 kcal/mol to 0.87 kcal/mol represent the free energy change associated with protein stability upon mutation. Interestingly, we identified that the three mutations (Y4C, T58I, and Y12E) were found to improve the structural stability of the protein. We performed molecular dynamics (MD) simulations to investigate the structural and dynamic effects of HRAS mutations. Our results showed that the stable model of HRAS had a significantly lower energy value of −18756 kj/mol compared to the initial model of −108915 kj/mol. The RMSD value for the wild-type complex was 4.40 Å, and the binding energies for the G60V, G60D, and D38H mutants were −107.09 kcal/mol, −109.42 kcal/mol, and −107.18 kcal/mol, respectively as compared to wild-type HRAS protein had −105.85 kcal/mol. The result of our investigation presents convincing corroboration for the potential functional significance of nsSNPs in augmenting HRAS expression and adding to the activation of malignant oncogenic signalling pathways.

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Section: Influence Of Non-synonymous Mutations On Protein Stability (...mentioning

confidence: 99%

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function

Ali¹,

Ali²,

Qamar³

et al. 2023

Front. Chem.

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“…DEFB1 has been predicted to interact with CCR6, a chemokine receptor expressed by specific immune cells such as memory T cells and dendritic cells. 43 The high affinity between β-defensins and CCR6 helps in recruiting these immune cells to the site of microbial invasion. 44 This may partially explain our results that enriched tumor-infiltrating CD4 + T CM cells were detected in OSCC patients with DEFB1 overexpression.…”

Section: Discussionmentioning

confidence: 99%

Tumor-Infiltrating CD4+ Central Memory T Cells Correlated with Favorable Prognosis in Oral Squamous Cell Carcinoma

Wu¹,

Zhang²,

Xiong³

et al. 2022

JIR

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Objective Oral squamous cell carcinoma (OSCC) is the most frequent oral malignancy with a poor prognosis, in which tumor-infiltrating immune cells may play a critical role. Therefore, our study aims to screen potential immune cells and immune-related genes for predicting OSCC prognosis. Methods A total of 310 OSCC patients with full transcriptional data and clinical characteristics were extracted from the TCGA database. Then, we obtained their abundance of tumor-infiltrating immune cells on TIMER 2.0 and analyzed them using xCell method. Univariate and multivariate Cox regressions were applied successively to identify the immune cells associated with overall survival of OSCC patients. Furthermore, we screened the prognostic genes that related to the identified immune cells and validated their expressions by immunohistochemistry. Results CD4 + central memory T (T CM ) cell was recognized as the sole independent immune cell correlated with OSCC prognosis ( p = 0.0085). A novel nomogram based on CD4 + T CM cell abundance was established for predicting the prognosis of OSCC patients, with calibration plots showing good performance for 1-, 3-, 5-year overall survival. Thirty-four related prognostic genes were screened according to the differential abundance of CD4 + T CM cell infiltration. In immunohistochemistry analysis, DEFB1 showed a significant positive relationship with the density of CD4 + T CM cells ( p = 0.0075). Conclusion CD4 + central memory T cell was proposed as an independent prognostic biomarker for OSCC patients. DEFB1 might positively regulate the abundance of tumor-infiltrating CD4 + T CM cells, thus improving OSCC prognosis. Our findings may provide a new insight into better prognosis prediction and precise medicine for OSCC.

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“…In human genome, non-synonymous single nucleotide polymorphisms account for about 50% of allele variation of all hereditary diseases 44 . It can help in improving medication strategies by facilitating more tailored personalized treatment to patients 45 . Also, new compounds can be tested to correct the effects of those mutations studying the effects generated by nsSNPs in disease-associated proteins.…”

Section: Discussionmentioning

confidence: 99%

Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability

Reza

Ferdous

Emon

et al. 2021

Sci Rep

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Genetic polymorphisms in DNA damage repair and tumor suppressor genes have been associated with increasing the risk of several types of cancer. Analyses of putative functional single nucleotide polymorphisms (SNP) in such genes can greatly improve human health by guiding choice of therapeutics. In this study, we selected nine genes responsible for various cancer types for gene enrichment analysis and found that BRCA1, ATM, and TP53 were more enriched in connectivity. Therefore, we used different computational algorithms to classify the nonsynonymous SNPs which are deleterious to the structure and/or function of these three proteins. The present study showed that the major pathogenic variants (V1687G and V1736G of BRCA1, I2865T and V2906A of ATM, V216G and L194H of TP53) might have a greater impact on the destabilization of the proteins. To stabilize the high-risk SNPs, we performed mutation site-specific molecular docking analysis and validated using molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) studies. Additionally, SNPs of untranslated regions of these genes affecting miRNA binding were characterized. Hence, this study will assist in developing precision medicines for cancer types related to these polymorphisms.

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In silico analysis of non-synonymous single nucleotide polymorphisms of human DEFB1 gene

Cited by 21 publications

References 36 publications

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function

Tumor-Infiltrating CD4+ Central Memory T Cells Correlated with Favorable Prognosis in Oral Squamous Cell Carcinoma

Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability

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