Mutation analysis of pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) in WFS1 gene through computational approaches

Impact of Missense Variants on the Structure and Function of Polycystic Ovary Syndrome-Associated HSD17B1 Gene

HSD17B1 regulates estrogen availability in the ovary, and its dysregulation is linked to cyst formation in polycystic ovary syndrome. This study aimed to understand the role of missense variants in HSD17B1 dysfunction. Bioinformatic tools (sift, polyphen2, panther, snps & go, phd-snp, pmut, snap and revel score) were used to identify the deleterious missense variants of HSD17B1 gene. InterPro and Pfam tools were utilized to predict the functional domain of these deleterious variants, and its impact on structure and stability of HSD17B1 was analyzed by Hope, MutPred2, I-Mutant 2.0, and Mupro. Further, the AutoDock was used to determine the binding affinity of NADP to HSD17B1 protein. Finally, the HSD17B1 expression in clinical samples was analyzed using qRT-PCR. Of the 355 missense variants identified, five (rs202173252, rs149630844, rs146159533, rs200202791, and rs138503851) variants were deleterious, pocketed at the NADP binding domain and located at the conserved region of HSD17B1. Further, series of in silico prediction and molecular docking shows only the variant T191I (rs138503851) has an adverse effect on HSD17B1 function because of increased unfavorable bonds and non-interaction of adenine and nicotinamide of NADP to the Glycine94 and Leucine93 of HSD17B1. Additionally, a two-fold reduced expression of HSD17B1 in peripheral blood of PCOS subjects was observed, compared to healthy individuals. Overall, these results indicate that rs138503851 genetic variant of HSD17B1 may affect estrogen synthesis in PCOS. However, further clinical studies are warranted to validate the presence of rs138503851 genetic variant to identify the potential females who are predisposal to the development of PCOS.

Transcriptional variation and RNA polymorphism among different Lentinula edodes (Berk.) Pegler strains

BACKGROUND

Lentinula edodes is a commercially important mushroom known for its nutritional and therapeutic values. However, the molecular mechanisms underlying the distinct nutritional and physiological attributes of various L. edodes strains are not well understood. This study focused on three Lentinula strains (DMRO-356, DMRO-623, and DMRO-388s) with different nutritional and productivity profiles. Illumina sequencing was used to perform a whole-transcriptome analysis, conducting 100-base pair paired-end sequencing of total messenger RNA (mRNA) in duplicate, resulting in 28-48 million sequencing reads per strain. After rigorous data filtering, over 99% of high-quality reads were retained, and more than 95% were aligned to the Lentinula genome.

RESULTS

Differential gene expression analyses identified 2210 differentially expressed genes between DMRO-356 and DMRO-623, 862 between DMRO-356 and DMRO-388s, and 2212 between DMRO-623 and DMRO-388s. Significant genetic variations were found among the strains, including 7753 single nucleotide polymorphisms (SNPs) in DMRO-356 versus DMRO-623 and 4080 SNPs in DMRO-356 versus DMRO-388s. Additionally, 349 insertions/deletions (InDels) were found in DMRO-356/DMRO-623 and 218 in DMRO-356/DMRO-388 s. Non-synonymous SNPs, which alter amino acid compositions, were analyzed, showing a preference for polar over charged amino acids.

CONCLUSION

These differentially expressed genes were associated with various nutritional and developmental processes, highlighting the importance of genetic variations in shaping amino acid composition and potentially affecting protein function. This study is the first comprehensive exploration of transcriptional differences among Lentinula strains available for its cultivation, providing valuable insights to enhance mushroom quality and productivity. © 2024 Society of Chemical Industry.

In-silico screening and analysis of missense SNPs in human CYP3A4/5 affecting drug-enzyme interactions of FDA-approved COVID-19 antiviral drugs

Single nucleotide polymorphisms (SNPs) represent the prevailing form of genetic variations observed in the human population. Such variations could alter the encoded enzymes' activities. CYP3A4/5 enzymes are involved in metabolizing drugs, notably antivirals against SARS-CoV-2. In this work, we computationally investigated antiviral-enzyme interactions of CYP3A4/5 genetic variants. We also examined the deleterious impact of 751 missense single nucleotide polymorphisms (SNPs) within the CYP3A4/5 genes. An ensemble of bioinformatics tools, [SIFT, PolyPhen-2, cadd, revel, metaLr, mutation assessor, Panther, SNP&GO, PhD-SNP, SNAP, Meta-SNP, FATHMM, I-Mutant, MuPro, INPS, CONSURF, GPS 5.0, MusiteDeep and NetPhos], identified a total of 94 variants (47 SNPs in CYP3A4, 47 SNPs in CYP3A5) to potentially impact the structural integrity as well as the activity of the CYP3A4/5 enzymes. Molecular docking was done to recognize the structural stability and binding properties of the CYP3A4/5 protein isoforms with 3 FDA-approved antiviral drugs. Our findings indicated that the CYP3A4 gene variants; R418T, I335T and R130P and the CYP3A5 gene variants; I335T, L133P and R130Q are considered the most deleterious missense SNPs. These mutants potentially affect drug-enzyme binding and hence may alter therapeutic response. Cataloguing deleterious SNPs is essential for personalized gene-based pharmacotherapy.

Analysis of nonsynonymous SNPs in candidate genes that influence bovine temperament and evaluation of their effect in Brahman cattle

BACKGROUND

Temperament is an important production trait in cattle and multiple strategies had been developed to generate molecular markers to assist animal selection. As nonsynonymous single nucleotide polymorphisms are markers with the potential to affect gene functions, they could be useful to predict phenotypic effects. Genetic selection of less stress-responsive, temperamental animals is desirable from an economic and welfare point of view.

METHODS AND RESULTS

Two nonsynonymous single nucleotide polymorphisms identified in HTR1B and SLC18A2 candidate genes for temperament were analyzed in silico to determine their effects on protein structure. Those nsSNPs allowing changes in proteins were selected for a temperament association analysis in a Brahman population. Transversion effects on protein structure were evaluated in silico for each amino acid change model, revealing structural changes in the proteins of the HTR1B and SLC18A2 genes. The selected nsSNPs were genotyped in a Brahman population (n = 138), and their genotypic effects on three temperament traits were analyzed: exit velocity, pen score, and temperament score. Only the SNP rs209984404-HTR1B (C/A) showed a significant association (P = 0.0144) with pen score. The heterozygous genotype showed a pen score value 1.17 points lower than that of the homozygous CC genotype.

CONCLUSION

The results showed that in silico analysis could direct the selection of nsSNPs with the potential to change the protein. Non-synonymous single nucleotide polymorphisms causing structural changes and reduced protein stability were identified. Only rs209984404-HTR1B shows that the allele affecting protein stability was associated with the genotype linked to docility in cattle.

Genetic insights into obesity: in silico identification of pathogenic SNPs in MBOAT4 gene and their structural molecular dynamics consequences

Membrane Bound O-Acyltransferase Domain-Containing 4 (MBOAT4) protein catalyzes ghrelin acylation, leading to prominent ghrelin activity, hence characterizing its role as an anti-obesity target. We extracted 625 exonic SNPs from the ENSEMBL database and one phenotype-based missense mutation associated with obesity (A46T) from the HGMD (Human Gene Mutation Database). These were differentiated on deleterious missense SNPs of the MBOAT4 gene through MAF (minor allele frequency: <0.01) cut-off criteria in relation to some bioinformatics-based supervised machine learning tools. We found 8 rare-coding and harmful missense SNPs. The consensus classifier (PredictSNP) tool predicted that the SNP (G57S, C: rs561065025) was the most pathogenic. Several trained in silico algorithms have predicted decreased protein stability [ΔΔG (kcal/mol)] function in the presence of these rare-coding pathogenic mutations in the MBOAT4 gene. Then, a stereochemical quality check (i.e. validation and assessment) of the 3D model was performed, followed by a blind cavity docking approach, used to search for druggable cavities and molecular interactions with citrus flavonoids of the Rutaceae family, ranked with energetic estimations. Significant interactions with Phloretin 3',5'-Di-C-Glucoside were also observed at R304, W306, N307, A311, L314 and H338 with (iGEMDOCK: -95.82 kcal/mol and AutoDock: -7.80 kcal/mol). The RMSD values and other variables of MD simulation analyses on this protein further validated its significant interactions with the above flavonoids. The MBOAT4 gene and its molecular interactions could serve as an interventional future anti-obesity target. The current study's findings will benefit future prospects for large population-based studies and drug development, particularly for generating personalized medicine.Communicated by Ramaswamy H. Sarma.

In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies

Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson's disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case-control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches.