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Identification of deleterious single nucleotide polymorphism (SNP)s in the human TBX5 gene & prediction of their structural & functional consequences: An in silico approach.

ABSTRACT: T-box transcription factor 5 gene (TBX5) encodes the transcription factor TBX5, which plays a crucial role in the development of heart and upper limbs. Damaging single nucleotide variants in this gene alter the protein structure, disturb the functions of TBX5, and ultimately cause Holt-Oram Syndrome (HOS). By analyzing the available single nucleotide polymorphism information in the dbSNP database, this study was designed to identify the most deleterious TBX5 SNPs through in silico approaches and predict their structural and functional consequences. Fifty-eight missense substitutions were found damaging by sequence homology-based tools: SIFT and PROVEAN, and structure homology-based tool PolyPhen-2. Various disease association meta-predictors further scrutinized these SNPs. Additionally, conservation profile of the amino acid residues, their surface accessibility, stability, and structural integrity of the native protein upon mutations were assessed. From these analyses, finally 5 SNPs were detected as the most damaging ones: [rs1565941579 (P85S), rs1269970792 (W121R), rs772248871 (V153D), rs769113870 (E208D), and rs1318021626 (I222N)]. Analyses of stop-lost, nonsense, UTR, and splice site SNPs were also conducted. Through integrative bioinformatics analyses, this study has identified the SNPs that are deleterious to the TBX5 protein structure and have the potential to cause HOS. Further wet-lab experiments can validate these findings.

SUBMITTER: Mahfuz AMUB

PROVIDER: S-EPMC8646135 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Discovering Deleterious Single Nucleotide Polymorphisms of Human AKT1 Oncogene: An In Silico Study.

Project description:BackgroundAKT1 is a serine/threonine kinase necessary for the mediation of apoptosis, angiogenesis, metabolism, and cell proliferation in both normal and cancerous cells. The mutations in the AKT1 gene have been associated with different types of cancer. Further, the AKT1 gene mutations are also reported to be associated with other diseases such as Proteus syndrome and Cowden syndromes. Hence, this study aims to identify the deleterious AKT1 missense SNPs and predict their effect on the function and structure of the AKT1 protein using various computational tools.MethodsExtensive in silico approaches were applied to identify deleterious SNPs of the human AKT1 gene and assessment of their impact on the function and structure of the AKT1 protein. The association of these highly deleterious missense SNPs with different forms of cancers was also analyzed. The in silico approach can help in reducing the cost and time required to identify SNPs associated with diseases.ResultsIn this study, 12 highly deleterious SNPs were identified which could affect the structure and function of the AKT1 protein. Out of the 12, four SNPs-namely, G157R, G159V, G336D, and H265Y-were predicted to be located at highly conserved residues. G157R could affect the ligand binding to the AKT1 protein. Another highly deleterious SNP, R273Q, was predicted to be associated with liver cancer.ConclusionsThis study can be useful for pharmacogenomics, molecular diagnosis of diseases, and developing inhibitors of the AKT1 oncogene.

| S-EPMC10381612 | biostudies-literature

The Single-Nucleotide Polymorphism (SNP) Validity to Detect Omicron Variants.

Project description:IntroductionMutation of SARS-CoV-2 has generated several variants of concern (VOC) which spread promptly worldwide. These emerging variants affected global strategies to overcome COVID-19. Variants of SARS-CoV-2 are determined by the whole genome sequencing (WGS) assay, which is time-consuming, with limited availability (only in several laboratories). Hence, a faster and more accessible examination is needed. The single-nucleotide polymorphism (SNP) method is one of the options for genomic variation surveillance that can help provide an answer to this challenge. This study aims to determine the validity of the SNP method with PCR to detect omicron variants of SARS-CoV-2 compared with the gold standard, WGS.MethodsThis is a diagnostic analysis of 140 confirmed COVID-19 nasopharyngeal samples taken from the Kemayoran COVID Emergency Hospital Laboratory and the West Java Provincial Health Laboratory from April to October 2022. Data analysis was carried out to determine conformity and validity values.ResultsAnalysis using Cohen's kappa coefficient test showed high conformity between SNP and WGS (p value <0.001; kappa coefficient = 0.948). SNP showed great validity values on omicron BA.1 (90% sensitivity; 100% specificity), omicron BA.2 (100% sensitivity; 99% specificity), and omicron BA.4/5 (99.2% sensitivity; 100% specificity).ConclusionThe SNP method can be a more time-efficient alternative to detect omicron variants of SARS-CoV-2 and distinguish their sublineages (BA.1, BA.2, and BA.4/5) by two different specific gene mutations in combination analysis (ΔH69/V70 and Q493R mutations).

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