Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

Amino acid transporters (AATs) are essential membrane proteins that transfer amino acids across cells. They are necessary for plant growth and development. The lysine histidine transporter (LHT) gene family in maize (Zea mays) has not yet been characterized. According to sequence composition and phylogenetic placement, this study found 15 LHT genes in the maize genome. The ZmLHT genes are scattered across the plasma membrane. The study also analyzed the evolutionary relationships, gene structures, conserved motifs, 3D protein structure, a transmembrane domain, and gene expression of the 15 LHT genes in maize. Comprehensive analyses of ZmLHT gene expression profiles revealed distinct expression patterns in maize LHT genes in various tissues. This studys extensive data will serve as a foundation for future ZmLHT gene family research. This study might make easier to understand how LHT genes work in maize and other crops.

In humans, FOXP gene family is involved in embryonic development and cancer progression. The FOXP4 (Forkhead box protein P4) gene belongs to this FOXP gene family. FOXP4 gene plays a crucial role in oncogenesis. Single nucleotide polymorphisms are biological markers and common determinants of human diseases. Mutations can largely affect the function of the corresponding protein. Therefore, the molecular mechanism of nsSNPs in the FOXP4 gene needs to be elucidated. Initially, the SNPs of the FOXP4 gene were extracted from the dbSNP database and a total of 23124 SNPs was found, where 555 nonsynonymous, 20525 intronic, 1114 noncoding transcript, 334 synonymous were obtained and the rest were unspecified. Then, a series of bioinformatics tools (SIFT, PolyPhen2, SNAP2, PhD SNP, PANTHER, I-Mutant2.0, MUpro, GOR IV, ConSurf, NetSurfP 2.0, HOPE, DynaMut2, GeneMANIA, STRING and Schrodinger) were used to explore the effect of nsSNPs on FOXP4 protein function and structural stability. First, 555 nsSNPs were analyzed using SIFT, of which 57 were found as deleterious. Following, PolyPhen2, SNAP2, PhD SNP and PANTHER analyses, 10 nsSNPs (rs372762294, rs141899153, rs142575732, rs376938850, rs367607523, rs112517943, rs140387832, rs373949416, rs373949416 and rs376160648) were common and observed as deleterious, damaging and diseases associated. Following that, using I-Mutant2.0 and MUpro servers, 7 nsSNPs were found to be the most unstable. GOR IV predicted that these seven nsSNPs affect protein structure by altering the protein contents of alpha helixes, extended strands, and random coils. Following DynaMut2, 5 nsSNPs showed a decrease in the ΔΔG value compared with the wild-type and were found to be responsible for destabilizing the corresponding protein. GeneMANIA and STRING network revealed interaction of FOXP4 with other genes. Finally, molecular dynamics simulation analysis revealed consistent fluctuation in RMSD and RMSF values, Rg and hydrogen bonds in the mutant proteins compared with WT, which might alter the functional and structural stability of the corresponding protein. As a result, the aforementioned integrated comprehensive bioinformatic analyses provide insight into how various nsSNPs of the FOXP4 gene change the structural and functional properties of the corresponding protein, potentially proceeding with the pathophysiology of human diseases.

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9–43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.

The biodiversity has experienced a significant increase in heavy metal contamination, which has a direct impact on aquatic environments. Industrial wastewater, municipal waste, burning fossil fuels, mining, and pesticides are the main sources of pollution. Due to its ability to produce a significant amount of biomass and its high level of stress tolerance, Spirodela polyrhiza (S. polyrhiza) is known as a phytoremediation aquatic plant. Because of their rapid development, simplicity in harvesting, and potential to remove heavy metals from wastewater S. polyrhiza could be an important tool for the treatment of industrial wastewater. This research analyzes how incorporating S. polyrhiza into industrial effluent can improve its physiochemical characteristics, like pH, Chemical oxygen demand (COD), Chlorides, total hardness, sulphates, total dissolved solids (TDS), Cu, Ni, Fe, Zn, Pb, and Ca. In this experiment industrial wastewater was treated using S. polyrhiza for 45 days on the basis of the depth of water (6", 12", and 18"). From the experimental study after D45 color changed brownish to light brownish. After D45 Chlorides level (mg/l) decreased 295.50±17.73 to 251.20±16.007. The initial COD value (mg/l) of the wastewater was 252.330±6.78 and after 45 days of treatment, the value reduced to 93.87±1. The total hardness (mg/ l) of the wastewater was reduced from 1862.8±43.9 to 1223.9±50.93 after treatment. On the other hand TDS value (mg/l) increased from 583.6±3.9 to 815.3±15.7 after the treatment. After 45 days of treatment with S. polyrhiza the copper level (mg/l) was reduced from 0.170±0.020 to 0.098±0.032. Similarly, the levels (mg/l) of Pb, Fe, Zn, and Ni were reduced from 0.222±0.029 to 0.061±0.035, 10.306±1.429 to 0.596±0.110, 0.168±0.055 to 0.084±0.023 and 0.150±0.029 to 0.078±0.018 respectively. The findings indicate that S. polyrhiza might with stand heavy metals and could be a feasible option for the phytoremediation of physiochemical contaminants and heavy metals derived from industrial wastewater

The cytotoxic T-lymphocyte antigen-4 (CTLA4) is essential in controlling T cell activity within the immune system. Thus, uncovering the molecular dynamics of single nucleotide polymorphisms (SNPs) within the CTLA4 gene is critical. We identified the non-synonymous SNPs (nsSNPs), examined their impact on protein stability, and identified the protein sequences associated with them in the human CTLA4 gene. There were 3134 SNPs (rsIDs) in our study. Out of these, 186 missense variants (5.93%), 1491 intron variants (47.57%), and 91 synonymous variants (2.90%), while the remaining SNPs were unspecified. We utilized SIFT, PolyPhen-2, PROVEAN, and SNAP for identifying deleterious nsSNPs, and SNPs&GO, PhD SNP, and PANTHER for verifying risk nsSNPs in the CTLA4 gene. Following SIFT analysis, six nsSNPs were identified as deleterious and reporting second and third nsSNPs as probably damaging and one as benign, respectively. From upstream analysis, rs138279736, rs201778935, rs369567630, and rs376038796 were found to be deleterious, probably damaging, and disease associated. ConSurf predicted conservation scores for four nsSNPs, and Project Hope suggested that all mutations could disrupt protein interactions. Furthermore, mCSM and DynaMut2 analyses indicated a decrease in ΔΔG stability for the mutants. GeneMANIA and STRING networks highlighted correlations with CD86 and CD80 genes. Finally, MD simulation revealed consistent fluctuation in RMSD and RMSF, consequently Rg, hydrogen bonds, and PCA in the mutant proteins compared with wild-type, which might alter the functional and structural stability of CTLA4 protein. The current comprehensive study shows how various nsSNPs in the CTLA4 gene can modify the structural and functional characteristics of the protein, potentially influencing the pathogenesis of diseases in humans. Further, experimental studies are needed to analyze the effect of these nsSNPs on the susceptibility of pathological phenotype populations.