In silico analysis of consequences of non-synonymous SNPs of Slc11a2 gene in Indian bovines

Advancing molecular modeling and reverse vaccinology in broad-spectrum yellow fever virus vaccine development

Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant ( β -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a( +) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus.

Computational analysis of non-synonymous single nucleotide polymorphism in the bovine PKLR geneComputational analysis of bovine PKLR gene

Pyruvate kinase (PKLR) is a potential candidate gene for milk production traits in cows. The main aim of this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the PKLR gene by using several computational tools. In silico tools including SIFT, Polyphen-2, SNAP2 and Panther indicated only 18 nsSNPs out of 170 were considered deleterious. The analysis of proteins' stability change due to amino acid substitution performed by the use of the I-mutant, MUpro, CUPSTAT, SDM and Dynamut confirmed that 9 nsSNPs decreased protein stability. ConSurf analysis predicted that all 18 nsSNPs were evolutionary moderately or highly conserved. Two different domains of PKLR protein were revealed by the InterPro tool with 12 nsSNPs positioned in the Pyruvate Kinase barrel domain and 6 nsSNP present in the Pyruvate Kinase C Terminal. The PKLR 3D model was predicted by MODELLER software and validated via Ramachandran plot and Prosa which indicated a good quality model. The analysis of energy minimizations for the native and mutated structures was performed by SWISS PDB viewer with GROMOS 96 program and showed that 3 structural and 4 functional residues had total energy higher than the native model. These findings indicate that these mutant structures (rs441424814, rs449326723, rs476805413, rs472263384, rs474320860, rs475521477, rs441633284) were less stable than the native model. Molecular Dynamics simulations were performed to confirm the impact of nsSNPs on the protein structure and function. The present study provides useful information about functional SNPs that have an impact on PKLR protein in cattle.Communicated by Ramaswamy H. Sarma.

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.

Genome-wide in silico analysis leads to identification of deleterious L290V mutation in RBBP5 gene in Bos indicus

Genome-wide deleterious mutations were identified in zebu cattle (Bos indicus) using in silico approach. The ddRAD sequence data of Sahiwal cattle were annotated and aligned with the cattle reference genome (ARS-UCD1.2). A total of 279,383 SNPs were identified at Read Depth10, which were further filtered to 692 missense SNPs. These SNPs were further analyzed, for functional consequences, by using Variant Effect Predictor, PolyPhen, PROVEAN, and PANTHER tools. A total of 18 SNPs, were finally identified as deleterious, and among these, 12 SNPs were mapped on nine different genes. ERRAT, ProSA-web, Project HOPE, TM-Align, and YASSARA tools, further confirmed the protein malfunctioning of one missense (L290V) mutation of Retinoblastoma binding protein-5 (RBBP5) gene, transcribing a cell cycle regulatory protein and associated with Retinoblastoma in human. This derived bioinformatics pipeline may be useful for preliminarily identifying the deleterious DNA mutations in livestock, specifically in absence of any genetic disease records.

Computational screening and analysis of deleterious nsSNPs in human p14ARF (CDKN2A gene) protein using molecular dynamic simulation approach

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments.Communicated by Ramaswamy H. Sarma.

Exploring the Structural and Functional Effects of Nonsynonymous SNPs in the Human Serotonin Transporter Gene Through In Silico Approaches

The sodium-dependent serotonin transporter SLC6A4 (solute carrier family 6 member 4) gene encodes an intrinsic membrane protein that transmits the serotonin neurotransmitter from synaptic clefts into presynaptic neurons. The product of the SLC6A4 gene is related to the regulation of mood and social behavior, sleep, appetite, memory, digestion, and sexual desire. This protein is a target for antidepressant and psychostimulant drugs, thus prolonged neurotransmitter signaling remains blocked. In this study, the functional consequences of nsSNPs in the human SLC6A4 gene were explored through computational tools: PhD-SNP, SIFT, Align GVGD, PROVEAN, PMut, nsSNP Analyzer, SNPs&GO, SNAP2, PolyPhen2, and PANTHER to identify the most deleterious and damaging nsSNPs. Then the mutant protein stabilities were assessed using I-Mutant, MUpro, and MutPred2; amino acid conservation using ConSurf, and posttranslational modification analysis using MusiteDEEP and PROSPER. Furthermore, the 3-dimensional (3D) model of the mutated proteins was predicted and validated using SPARKS-X, Verify3D, and PROCHECK. The protein–ligand binding sites were analyzed using the COACH meta-server. Results from this study predicted that T192M, G342E, R607C, W282S, R104C, P131L, P156L, and N351S were the most structurally and functionally significant nsSNPs in the human SLC6A4 gene. Arg607 and Pro156 were the predicted sites for posttranslational modifications, and Thr192 and Try282 were the ligand-binding sites in the human SLC6A4 gene. The analyzed data also suggested that R104C, P131L, P156L, T192M, G342E, and W282S mutants might affect the binding of sodium ions with this protein. Taken together, this study provided important information on structurally and functionally important nsSNPs of the human SLC6A4 gene for further experimental validation. In the future, these damaging nsSNPs of the SLC6A4 gene have the potential to be evaluated as prognostic biomarkers for SLC6A4-related disorder diagnosis and research.

In Silico Tools for Analysis of Single-Nucleotide Polymorphisms in the Bovine Transferrin Gene

Dairy cattle with a high milk yield are susceptible to many infectious diseases, such as mastitis. Subclinical mastitis (SCM) is the most prevalent form of mastitis that predominantly affects animal health, and causes adverse effects on the quality and quantity of milk. In dairy animals, subclinical mastitis often remains undetected, as no gross changes in udder characteristics are visible. In the present study, 135 Holstein Friesian dairy animals were selected and screened as healthy (n = 25) and mastitic (n = 110) based on diagnostic tests such as the California mastitis test, pH, electrical conductivity, and somatic cell count. In this study, the somatic cell count was used as a gold-standard test in differentiating subclinical mastitis animals from healthy ones. The present study was carried out to study polymorphisms in the bovine transferrin gene in cows (with subclinical mastitis and healthy). For the early detection of resistant/or susceptible animals, a useful marker could be provided by the detection of single-nucleotide polymorphisms (SNPs) in the transferrin gene, which are often associated with mammary innate immune response. The sequencing results revealed three nucleotide substitutions: two transversions (230 A > C, 231 C > A) and one transition (294 A > G) in susceptible cows as compared to disease-free subjects. The nucleotide variations at position 230 (GAC > GCA) and 231 (GAC > GCA) were nonsynonymous, and corresponded to an amino acid change from aspartic acid to alanine; whereas at position 294 (GAA > GAG), the mutation was synonymous. In the present study, many in silico tools were taken into consideration to determine the effect of SNPs on protein structure and function. The PROVEAN tool found the amino acid substitution to be neutral and deleterious. PolyPhen-2 revealed the amino acid variations at positions 320 and 321 to most likely be damaging; and at the 341 position, the variations were benign. The I-Mutant and MUpro tools found that the protein stability decreased for nonsynonymous variations. The SIFT tool revealed the protein function was likely to be affected in nonsynonymous variations, with no change in the case of synonymous ones. Phylogenetic analysis of the bovine transferrin gene revealed a close relation of the CA allele with the Bos taurus transferrin, while the G allele was closely related to a cross of Bos indicus × Bos taurus serotransferrins, followed by the Bison bison transferrin. The least relation was shown by both alleles to Capra hircus, Ovis aries, and Bubalus bubalis.

Association of PON1, TNF-α and TGF-β gene polymorphisms with prognosis in oral and oropharyngeal squamous cell carcinoma

OBJECTIVE

The oral and oropharyngeal squamous cell carcinoma (OOSCC) accounts for 90-95% of tumours in the oral cavity. Single nucleotide polymorphism (SNP) in the coding region of PON1, tumour necrosis factor-alpha (TNF-α) and transforming growth factor-beta (TGF-β) have been associated with to development of different cancers. Our aim was to investigate the prognostic value of PON1 (rs854560 and rs662), TNF-α (rs1800629 and rs361525) and TGF-β (rs1800469) SNPs in OOSCC.

MATERIALS AND METHODS

We genotyped 163 OOSCC patients and 146 patients from group of control for PON1 (rs854560 and rs662), TNF-α (rs1800629 and rs361525) and TGF-β (rs1800469) SNPs by real-time polymerase chain reaction (PCR).

RESULTS

TNF-α (rs1800629) GG genotype was significantly more frequent in intraoral lesions and clinical stages III and IV, while the polymorphic AA genotype in lip lesion and clinical stages I and II. Moreover, TGF-β (rs1800469) AG and AA genotypes were significantly more frequent in larger tumours (T3 e T4). TNF-α (rs1800629) AG genotype had poor survival and patients carrying the PON1 (rs662) TT genotype tended to poor survival.

CONCLUSIONS

Results suggest that the rs1800629 and rs1800469 could exert influence in the more aggressive behaviour of OOSCC and the genotypes AG of rs1800629, and TT of rs662 could be markers with prognostic value in OOSCC.

cis-9-Hexadecenal, a Natural Compound Targeting Cell Wall Organization, Critical Growth Factor, and Virulence of Aspergillus fumigatus

Aspergillus fumigatus causes several nosocomial pulmonary infections and accounts for high morbidity and mortality rate globally. Among various virulence factors, 1,8-dihydroxynaphthalene-melanin plays an important role in the survival during unfavorable conditions both in vivo and in vitro, masks various molecular patterns associated with A. fumigatus, and protects it from the host immune system. In the present study, we aim to understand the potential of cis-9-hexadecenal as an antimelanogenic compound and its role in modulating other associated virulence factors in A. fumigatus. cis-9-Hexadecenal is a bioactive compound that belongs to C₁₆ mono-unsaturated fatty-aldehyde groups. Minimum effective concentration of cis-9-hexadecenal affecting A. fumigatus melanin biosynthesis was determined using broth microdilution method. The spectrophotometric analysis revealed reduced melanin content (91%) and hydrophobicity (59%) at 0.293 mM of cis-9-hexadecenal. Cell surface organizational changes using electron microscopy showed altered demelanized smooth A. fumigatus conidial surface without any protrusions after cis-9-hexadecenal treatment. The transcript analysis of polyketide synthase (PKS) pksP/alb1 gene was quantified through qRT-PCR which revealed an upregulated expression. Total proteome profiling conducted through LC-MS-MS showed upregulated PKS enzyme but other downstream proteins involved in the 1,8-dihydroxynaphthalene-melanin biosynthesis pathway were absent. The homology modeling of PKS using Expasy's web server predicted that PKS is stable at varied conditions and is hydrophilic in nature. The Ramachandran plot by PROCHECK confirmed the 3-D structure of PKS to be reliable. Docking analysis using AutoDock-4.2.6 predicted the binding of cis-9-hexadecenal and PKS at Thr-264 and Ser-171 residue via hydrogen bonding at a low binding energy of -4.95 kcal/mol.

Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function

Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the biological significance of functional single-nucleotide polymorphisms (SNPs) using wet laboratory experiments is an arduous task hence the computational analysis of putative SNPs is essential before conducting a study on a large population. SNP in the leptin receptor (LEPR) could result in the retention of intracellular signalling due to the structural and functional instability of the receptor causing abnormal reproductive function in human. In this first comprehensive computational analysis of LEPR gene mutation, we have identified and analyzed the functional consequence and structural significance of the SNPs in LEPR using recently developed several computational algorithms. Thirteen deleterious mutations such as W13C, S93G, I232R, Q307H, Y354C, E497A, Q571H, R612H, K656N, T690A, T699M V741M, and L760R were identified in the LEPR gene coding region. Backpropagation algorithm has been developed to forestall the deleterious nature of SNP and to validate the outcome of the tested computational tools. From ConSurf prediction three SNPs (Q571H, R612H, and T699M) were highly conserved on LEPR protein and the most deleterious variant R612H had one hydrogen bond abolished and severely reduced protein stability. Molecular docking suggested that the mutant (R612H) LEPR had lowest binding energy than native LEPR with the ligand molecule. Thus the energetically destructive changeover of ARG to HIS in R612H could possibly affect the LEPR protein structural stability and functional constancy due to interruption in the amino acid interactions and could result in reproductive disorders in human and increases the complication in obstetric and pregnancy outcome.

Computational Analysis of High-Risk SNPs in Human DBY Gene Responsible for Male Infertility: A Functional and Structural Impact

BACKGROUND

DEAD-box helicase 3, Y-linked (DBY) is a candidate gene of the AZF region which is involved in spermatogenesis process. Mutations in the DBY gene may disrupt the spermatogenesis and lead to infertility in men. Identification of functionally neutral mutation from the disease-causing mutation is the biggest challenge in human genetic variation analysis. Owing to the importance of DBY in male infertility, functional analysis was carried out to reveal the association between genetic mutation and phenotypic variation through various in silico approaches.

METHODS

The present study analyzed the functional consequences of the nsSNPs in human DBY gene using SIFT, PolyPhen 2, PROVEAN, SNAP2, PMut, nsSNPAnalyzer, PhD-SNP and SNPs&GO along with stability analysis through I-Mutant2.0, MuPro and iPTREE-STAB. The conservational analysis of amino acid residues, biophysical properties and conserved domains of the DBY protein was analyzed using various computational tools. The 3D structure of the protein was generated using SPARKS-X and validated using RAMPAGE.

RESULTS

Out of 1130 SNPs reported in dbSNP, only one nsSNP (G300D) was found to have a functional effect on stability as well as the function of the DBY protein. The results showed the presence of G300 in the putative structure of DBY domain.

CONCLUSION

To the best of our knowledge, this is the first study to detect pathologically significant nsSNPs (G300D) through a computational approach in the DBY which can be useful for development in potent drug discovery studies.

Computational analysis for the determination of deleterious nsSNPs in human MTHFD1 gene

Single nucleotide polymorphisms (SNPs) are the most common genetic polymorphisms and play a major role in many inherited diseases. Methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) is one of the enzymes involved in folate metabolism. In the present study, the functional and structural consequences of nsSNPs of human MTHFD1 gene was analyzed using various computational tools like SIFT, PolyPhen2, PANTHER, PROVEAN, SNAP2, nsSNPAnalyzer, PhD-SNP, SNPs&GO, I-Mutant, MuPro, ConSurf, InterPro, NCBI Conserved Domain Search tool, ModPred, SPARKS-X, RAMPAGE, FT Site and PyMol. Out of 327 nsSNPs form human MTHFD1 gene, total 45 SNPs were predicted as functionally most significant SNPs, among which 17 were highly conserved and functional, 17 were highly conserved and structural residues. Among 45 most significant SNPs, 15 were predicted to be involved in post translational modifications. The p.Gly165Arg may interfere in homodimer interface formation. The p.Asn439Lys and p.Asp445Asn may interfere in binding interactions of MTHFD1 protein with cesium cation and potassium. The two SNPs (p.Asp562Gly and p.Gly637Cys) might interfere in interactions of MTHFD1 with ligand.