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Zyxin functions as a regulator of the restructuring of the actin cytoskeleton during the process of repairing tissue damage, cell movement and attachment. It has also been identified as a potential gene involved in chicken coccidiosis. In order to gain a deeper understanding of these phenomena, we employed a collection of computer-based techniques and databases to examine the amino acid sequence, structural dynamics, molecular interactions, and activities of the gene. Our analysis revealed that Zyxin contains two non-synonymous SNPs (A > C at position 22 and G > A at position 137) at exon 1. Also, there existed a non-synonymous SNPs in Exon 3 (A>C and A>T both at position 861) of the gene with Synonymous SNPs observed only in exon 3 (A>G at position 812 and 854, T > C at position 863). The genetic diversity revealed in these chicken populations indicates the presence of genetic variation, with Naked neck chickens showing a considerably higher frequency of particular SNPs. Two non-synonymous single nucleotide polymorphisms (nsSNPs) were forecasted to exert a profound influence on the structure, stability, and activities of Zyxin, thereby heightening the vulnerability to coccidiosis.

Introduction: The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods: nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results: Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 76 dangerous, and I-Mutant found 66 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions: Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.

Background and Aim Nonsynonymous single nucleotide polymorphisms (nsSNPs) in angiotensin Type II receptor (AGTR2) have been identified as a potential cause of cardiovascular illness in humans. Identifying structurally and functionally relevant alterations in AGTR2 is critical to investigate possible therapeutic targets. Methods A comprehensive computational pipeline was employed to evaluate deleterious nsSNPs using multiple prediction algorithms, including SIFT, PolyPhen‐2, CADD, REVEL, Mutation Assessor, MetaLR, I‐Mutant, MutPred, and Phylo3D. Molecular docking and molecular dynamic simulation strategies were further utilized to thoroughly validate these nsSNPs. Additionally, gene–gene interaction networks were constructed to explore AGTR2′s functional associations. Results Our findings indicated that four nsSNPs, including rs200599388, rs1556673810, rs3729979, and rs1556673736, potentially have the most deleterious effect on the AGTR2 gene. MD simulations revealed that these variants induced increased structural fluctuations and conformational instability compared with the wild‐type protein. Gene–gene interaction analysis indicated that AGTR2 participates in several key regulatory pathways relevant to cardiovascular physiology. Conclusion These findings will form the basis to design precision medicines for cardiovascular diseases in the future and welcome further preclinical and clinical investigations.

Glutathione Peroxidase 1 (GPx1) gene has been reported for its role in cellular redox homeostasis, and the dysregulation of its expression is linked with the progression of diverse cancers. Non-synonymous single nucleotide polymorphism (nsSNPs) have been emerged as the crucial factors, playing their role in GPx1 overexpression. To understand the deleterious mutational effects on the structure and function of GPx1 enzyme, we delved deeper into the exploration of possibly damaging nsSNPs using in-silico based approaches. Eight widely utilized computational tools were employed to roughly shortlist the deleterious nsSNPs. Their damaging effects on structure and function of the genes were evaluated by using different bioinformatics tools. Subsequently, the three final proposed deleterious mutants including mutations rs373838463, rs2107818892, and rs763687242, were docked with their reported binder, TNF receptor-associated factor 2 (TRAF2). The lowest binding affinity and stability of the docked mutant complexes as compared to the wild type GPx1 were validated by molecular dynamic simulation. Finally, the comparison of RMSD, RMSF, RoG and hydrogen bond analyses between wild-type and mutant’s complexes validated the deleterious effects of proposed nsSNPs. This study successfully identified and verified the possibly damaging nsSNPs in GPx1 enzyme, which may be linked the progression of various types of cancer. Our findings underscore the value of in-silico approaches in mutational analysis and encourage further preclinical and clinical trials.

Cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel protein involved in trans-epithelial transport of salt and the regulation of intracellular ion concentrations. The present study aims to investigate the relationship between CFTR non-synonymous SNPs (nsSNPs) and cancer. The study also seeks to elucidate the structural and functional consequences of the deleterious CFTR variants on the protein. The CFTR nsSNPs were retrieved from the Ensembl genome browser, and the deleterious nsSNPs were filtered out using PredictSNP2, CADD, FunSeq2 and GWAVA. The most pathogenic nsSNPs were shortlisted for further analysis. By employing I-TASSER, ProjectHOPE, I-Mutant, MUpro, DynaMut and MutPred, the influence of SNPs on the function and structure of the protein was assessed. Secondary and tertiary structures were predicted through PSIPRED and AlphaFold. Normal Mode Analysis (NMA) were performed through IMOD software, while the RMSD values of the mutated structures were determined through myPresto. Genotyping analyses were conducted through Tetra-primer ARMS-PCR (Amplification Refractory Mutation System). Fourteen nsSNPs of CFTR were identified as deleterious, significantly decreasing protein stability and potentially contributing to carcinogenesis. The pathogenic variants were mapped onto the ATP-binding cassette domain, indicating a strong association with altered protein function. Structural analyses indicated that the nsSNPs could induce changes in residue interactions with neighboring residues, thereby affecting the protein stability and molecular interactions. Normal Mode Analysis confirmed that these variants could perturb the CFTR’s conformational integrity. The genotyping analysis indicated that the heterozygous (AT) genotype of rs556880586 was highly prevalent in patients (70%) in comparison to controls (19%). Testing through Hardy–Weinberg Equilibrium (HWE) showed significant deviation in both patient and control groups for the nsSNPs, rs556880586 and rs949472192. Outcomes of the current study identified two deleterious nsSNPs in the CFTR gene that can possibly contribute to cancer progression. Moreover, these variants could act as preliminary biomarker candidates for clinical validation. The obtained knowledge gained from the current research could eventually assist in disease diagnosis and therapy design.

Background Polymorphisms in IL1B play a significant role in depression, multiple inflammatory-associated disorders, and susceptibility to infection. Functional non-synonymous SNPs (nsSNPs) result in changes in the encoded amino acids, potentially leading to structural and functional alterations in the mutant proteins. So far, most genetic studies have concentrated on SNPs located in the IL1B promoter region, without addressing nsSNPs and their association with multifactorial diseases. Therefore, this study aimed to explore the impact of deleterious nsSNPs retrieved from the dbSNP database on the structure and functions of the IL1B protein. Results Six web servers (SIFT, PolyPhen-2, PROVEAN, SNPs&GO, PHD-SNP, PANTHER) were used to analyze the impact of 222 missense SNPs on the function and structure of IL1B protein. Five novel nsSNPs (E100K, T240I, S53Y, D128Y, and F228S) were found to be deleterious and had a mutational impact on the structure and function of the IL1B protein. The I-mutant v2.0 and MUPro servers predicted that these mutations decreased the stability of the IL1B protein. Additionally, these five mutations were found to be conserved, underscoring their significance in protein structure and function. Three of them (T240I, D128Y, and F228S) were predicted to be cancer-causing nsSNPs. To analyze the behavior of the mutant structures under physiological conditions, we conducted a 50 ns molecular dynamics simulation using the WebGro online tool. Our findings indicate that the mutant values differ from those of the IL1B wild type in terms of RMSD, RMSF, Rg , SASA, and the number of hydrogen bonds. Conclusions This study provides valuable insights into nsSNPs located in the coding regions of IL1B , which lead to direct deleterious effects on the functional and structural aspects of the IL1B protein. Thus, these nsSNPs could be considered significant candidates in the pathogenesis of disorders caused by IL1B dysfunction, contributing to effective drug discovery and the development of precision medications. Thorough research and wet lab experiments are required to verify our findings. Moreover, bioinformatic tools were found valuable in the prediction of deleterious nsSNPs.

Fucosyltransferase 2 ( FUT2 ) gene has been extensively reported to play its role in potential gut microbiota changes and norovirus susceptibility. The normal activity of FUT2 has been found to be disrupted by non-synonymous single nucleotide polymorphisms (nsSNPs) in its gene. To explore the possible mutational changes and their deleterious effects, we employed state-of-the-art computational strategies. Firstly, nine widely-used bioinformatics tools were utilized for initial screening of possibly deleterious nsSNPs. Subsequently, the structural and functional effects of screened nsSNPs on FUT2 were evaluated by utilizing relevant computational tools. Following this, the two shortlisted nsSNPs, including G149S (rs200543547) and V196G (rs367923363), were further validated by their molecular docking with norovirus capsid protein, VP1. As compared to wild-type, the higher stability and lower binding energy scores of the both the mutants indicated their stable binding with VP1, which ultimately leads to norovirus implications. These docking results were further verified by a comprehensive computational approach, molecular dynamic simulation, which gave results in the form of lower RMSD, RMSF, RoG, and hydrogen bond values of both the mutants, depicted in relevant graphs. Overall, this research explores and validated the two FUT2 nsSNPs (G146S and V196G), which may possibly linked with the norovirus susceptibility and gut microbiota changes. Moreover, our findings highlights the value of computational strategies in mutational analysis and welcomes any further experimental validation.

Diabetes mellitus (DM) represents a problem for the healthcare system worldwide. DM has very serious complications such as blindness, kidney failure, and cardiovascular disease. In addition to the very bad socioeconomic impacts, it influences patients and their families and communities. The global costs of DM and its complications are huge and expected to rise by the year 2030. DM is caused by genetic and environmental risk factors. Genetic testing will aid in early diagnosis and identification of susceptible individuals or populations using ATP-sensitive potassium (KATP) channels present in different tissues such as the pancreas, myocardium, myocytes, and nervous tissues. The channels respond to different concentrations of blood sugar, stimulation by hormones, or ischemic conditions. In pancreatic cells, they regulate the secretion of insulin and glucagon. Mutations in the KCNJ11 gene that encodes the Kir6.2 protein (a major constituent of KATP channels) were reported to be associated with Type 2 DM, neonatal diabetes mellitus (NDM), and maturity-onset diabetes of the young (MODY). Kir6.2 harbors binding sites for ATP and phosphatidylinositol 4,5-diphosphate (PIP2). The ATP inhibits the KATP channel, while the (PIP2) activates it. A Kir6.2 mutation at tyrosine330 (Y330) was demonstrated to reduce ATP inhibition and predisposes to NDM. In this study, we examined the effect of mutations on the Kir6.2 structure using bioinformatics tools and molecular dynamic simulations (SIFT, PolyPhen, SNAP2, PANTHER, PhD&SNP, SNP&Go, I-Mutant, MuPro, MutPred, ConSurf, HOPE, and GROMACS). Our results indicated that M199R, R201H, R206H, and Y330H mutations influence Kir6.2 structure and function and therefore may cause DM. We conclude that MD simulations are useful techniques to predict the effects of mutations on protein structure. In addition, the M199R, R201H, R206H, and Y330H variant in the Kir6.2 protein may be associated with DM. These results require further verification in protein–protein interactions, Kir6.2 function, and case-control studies.

Spi-1 Proto-Oncogene (SPI1) encodes Purine-rich box 1 Transcription Factor (PU.1), a transcription factor of the ETS family that regulates hematopoietic lineage commitment and immune cell differentiation. Alteration of PU.1 dose or ETS domain integrity may interfere with transcriptional programs, which adds to hematopoietic dysregulation and leukemogenesis. Even though changes in SPI1 expression have been associated with acute myeloid leukemia (AML), the structural and regulatory effects of missense mutations at the PU.1 ETS domain have not been entirely studied, and targeting the PU.1 ETS domain by ligands is an area of computational analysis that should be further pursued. To computationally describe deleterious missense variants of SPI1 in terms of structural stability, evolutionary conservation, post-translational modification (PTM) context and interaction networks, and to measure ADMET-mediated molecular docking of cinnamic acid with the PU.1 ETS domain (8EQG) as a potential modulator. Missense nsSNPs were obtained through Ensembl and narrowed down by consensus prediction of pathogenicity (PredictSNP, combining SIFT, PolyPhen, SNAP and PhD-SNP and other tools). InterPro/UniProt was used for domain mapping. SWISS-MODEL was used to produce wild-type and mutant PU.1 versions, which were analyzed on the structural alignment and Cα–Cα displacement parameters in UCSF Chimera (v1.19). The estimation of stability change was carried out with I-Mutant and MUpro. Prediction of PTM sites was done using MusiteDeep and exploration of functional partners was done using STRING. Human, mouse and zebrafish orthologue conservation was measured by means of MAFFT alignment. GEPIA2 was used to compare the expression of SPI1 in AML (TCGA-LAML) and normal tissues (GTEx). AutoDock Vina (grid center 6, −2, −9 A; 20 × 20 × 20 A; 16 exhaustiveness) was used to prepare cinnamic acid and dock it into the PU.1 ETS domain (8EQG), with SwissDock being used for consistency checks. SwissADME and ADMETlab 2.0 were used to predict drug-likeness, pharmacokinetics, and toxicity. Nine missense mutations were routinely considered as deleterious with the majority of them being located in or near the ETS DNA-binding domain. Structural comparisons showed local perturbations of the structure and I189F and H211P yielded the greatest conformational changes between prioritized variants whereas other forms had minimal movements. A predominantly destabilizing trend was supported by stability prediction whereby V241G had the strongest destabilization signal with further destabilizations being predicted in I189F and R259C. PTM mapping revealed several potential regulatory residues (phosphorylation, acetylation, ubiquitination, and methylation), which indicated that there could be crosstalk between the sequence variation and the transcriptional regulation. The SPI1 was placed in a central hematopoietic transcriptional module (containing RUNX1, CEBP members, GATA1 and IRF factors) by the STRING network. The cross-species alignment showed that there was high conservation of a number of the mutation sites, which would support functional constraint at the ETS region. The expression analysis revealed that the level of SPI1 mRNA in AML was significantly elevated compared to normal tissues. Docking also indicated a slight and reproducible interaction of cinnamic acid with the ETS domain (top affinity −4.27 kcal/mol), with a solitary leading polar anchor and supportive hydrophobic interactions, which is akin to interaction between fragments. The ADMET profiling revealed the likelihood of success in the oral drug-likeness and low CYP inhibition liability, as well as signifying the presence of a possible hepatotoxicity signal that needs further confirmation through experiments. Comprehensive computational studies suggest that certain pathogenic variants of SPI1 missense defects, especially in the ETS domain, can result in loss of PU.1 structural stability and regulatory environment, which are in line with the disturbed hematopoietic regulation and AML-related dysregulation. Cinnamic acid demonstrates moderate yet reproducible binding to the PU.1 ETS domain and has an overall favorable developability profile, which indicates that it is better considered as a starting scaffold, as opposed to an active inhibitor. The results give a logical basis of focused biochemical validation and structure-directed optimization of ETS domain modulators in hematologic disease settings.