Search Results (73)

The extended application of pesticides has intensified the resistance problem in Liriomyza trifolii within Hainan Province. This study aimed to elucidate the underlying mechanisms contributing to the elevated resistance observed in this pest by employing Whole-Genome Re-sequencing (WGR) technology. Through the analysis and comparison of WGR data focusing on voltage-gated sodium channel (VGSC) from diverse regions and LT-S of L. trifolii in Hainan Province, we identified a total of six nonsynonymous single nucleotide polymorphisms (nsSNPs) and thirty-one synonymous single nucleotide polymorphisms (sSNPs) in five wild populations MY, TS, DA, TY, and JY. Among the six nsSNPs, three (PyR1: M918T, L1014F, and PyR2: T933I) have been confirmed as linked to pyrethroid resistance, while one (D IVS6: V1845I) was associated with resistance to indoxacarb. Moreover, the frequency of these four mutations generally increases with decreasing latitude. Additionally, under sustained pesticide selection pressure, L. trifolii exhibits an evolutionary pattern characterized by a dN/dS ratio (nsSNP/sSNP = 6/31 ≈ 0.19) of less than 1. Among the 31 sSNPs that held an absolute quantitative advantage, the highest occurrence frequency reached 94.44% (G2033: JY), and this sSNP occurred in all populations. In contrast, among a limited number of 6 nsSNPs, the highest occurrence frequency attained 100% (L1014F: all populations). This study substantiates that the elevated resistance observed in L. trifolii within Hainan Province can be ascribed to the presence of four nsSNPs-M922T, T933I, L1018F, and V1845I in their VGSC. Furthermore, the emergence of cross-resistance between pyrethroids and indoxacarb has been identified. This research offers a novel theoretical foundation for future investigations into the resistance mechanisms of L. trifolii. Full article

Backgrounds: Objective of this study is to conduct a genome-wide association study (GWAS) of first-parity reproductive traits in Suzi pigs to identify significant single-nucleotide polymorphisms (SNPs) or candidate genes influencing these traits. Methods: This research employed technologies including the Zhongxin 50K SNP chip, simplified genome sequencing, resequencing, and the 100K SNP liquid chip to perform genome-wide SNP detection on 898 Suzi sows. Genotype data and phenotypic data were combined to do GWAS, gene annotation, and enrichment analysis. Results: Results showed that this study obtained phenotypes of 33 first-parity reproductive traits from 574 sows. GWAS results indicated there were 10 first-parity reproductive traits significantly associated with SNPs, and these traits were AFS, AFF, NNB, NH, NW, NS, NM, ND, PB, and CCN. These 10 traits were significantly associated with 60 SNPs, with 15 (25%) located on chromosome 2-the highest proportion. The SNPs significantly associated with AFS and AFF were largely identical. Genome-wide variance component analysis revealed that among the 10 traits with significantly associated SNPs in GWAS, there were 5 traits that exhibited genome-wide heritability ≥ 0.01. Trait of NM showed the highest heritability (0.65–0.7). These significantly associated SNPs annotated 20 candidate genes, including ADAMTS19, PROP1, ZNF354B, PCARE, LUZP2, VIRMA, EPHA5, AAAS, SLCO3A1-SV2B, KIF18A-BDNF, SERGEF, DYNLRB2, HNF4G, CATSPERD, HSD11B1L, DICER1, RARG, PCDHAC2, KRT79, and HSD17B2. GO analysis of candidate genes revealed that the top three biological processes were cell adhesion, positive regulation of cell projection organization, and positive regulation of neuron projection development. KEGG results showed the top three pathways were inositol phosphate metabolism, glutamatergic synapse, and phosphatidylinositol signaling system. Conclusions: These findings provide a foundation for the reproductive breeding of Suzi pigs and offer new insights into biological breeding in pigs. Full article

Background: The ESR2 gene encodes Estrogen Receptor-β1 (ERβ1), a putative tumor suppressor in hormone-dependent malignancies. Although ERβ biology has been studied extensively at the expression level, the functional impact of nonsynonymous SNPs (nsSNPs) and untranslated-region (UTR) variants in ESR2 remains underexplored. Methods: We retrieved variants from Ensembl and performed an integrative in silico assessment using PredictSNP, I-Mutant, MUpro, HOPE, MutPred2, and CScape for pathogenicity, oncogenicity and structural stability; STRING/KEGG/GO for pathway context; RegulomeDB and polymiRTS for regulatory effects; and cBioPortal for pan-cancer clinical outcomes (breast (BRCA), endometrial (UCEC), and ovarian (OV)). We evaluated effects of nsSNPs on ERβ1 stability, ligand-binding/DNA-binding domains, co-factor recruitment, and post-transcriptional regulation. Results: Across tools, 93 missense nsSNPs were consistently predicted to be deleterious. Notably, several variants were found to destabilize ERβ1, particularly within the ligand-binding domains (LBD) and DNA-binding domains (DBD). Putative oncogenic drivers R198P and D154N showed high CScape scores and very low population frequencies, consistent with pathogenicity. Several substitutions were predicted to impair coactivator binding and disrupt interactions with key transcriptional partners, including JUN, NCOA1, and SP1. At the post-transcriptional level, rs139004885 was predicted to disrupt miRNA binding, while 3′UTR rs4986938 showed strong regulatory potential and comparatively high population frequency; by contrast, most other identified SNPs were rare. Clinically, pan-cancer survival analyses indicated worse overall survival (OS) in BRCA for ESR2-Altered cases (HR ≈ 2.25; q < 0.001), but better OS in UCEC (HR ≈ 0.24; q ≈ 0.014) and OV (HR ≈ 0.29; q < 0.001), highlighting a tumor-type-specific association. Conclusions: This integrative analysis prioritizes high-impact ESR2 variants that likely impair ERβ1 structure and shows context-dependent clinical effects. Despite their generally low frequency (except for rs4986938), prospective validation linking variant class to ERβ expression and survival outcomes is needed to support biomarker development and therapeutic applications. Full article

Background: RNF114 gene encodes an E3 ubiquitin ligase involved in immune signaling and regulation of inflammation. Genetic variants, particularly nonsynonymous single-nucleotide polymorphisms (nsSNPs), may interfere with protein function and cause immune diseases such as psoriasis. Although significant, the structural and functional impact of RNF114 nsSNPs is not well understood. Methods: We used comprehensive bioinformatics analyses to predict the functional impact of RNF114 nsSNPs. Deleterious variants were predicted by SIFT, PolyPhen-2, PROVEAN, META-SNP, ESNP&GO, PANTHER, and Alpha-Missense. Protein stability was examined by I-Mutant2.0, and MUpro further contextualized variant effects. Structural modeling was performed by AlphaFold and visualized using UCSF ChimeraX 1.10.1. Additionally, we studied the Conservation using ConSurf and protein-protein interaction by STRING tools. Results: Among 252 available nsSNPs, three mutations—C49R (rs1600868749), R68C (rs745318334), and R68H (rs758000156)—were predicted to have a deleterious and destabilizing effects on the protein structure by all the tools. All three variants were located in extremely conserved residues and were predicted to significantly destabilize the protein structure. Structural modeling demonstrated disruptions in the RNF114 domain structure. STRING analysis revealed interactions of RNF114 with key immune regulators, and pathway enrichment pointed to roles in NF-κB signaling, ubiquitin-mediated proteolysis, and autoimmune disease pathways. Conclusions: In the current study, we predicted three novel, potentially pathogenic RNF114 variants with protein-destabilizing effect that could lead to immune dysregulation. Full article

Psathyrostachys huashanica (2n = 2x = 14, NsNs) and Leymus mollis (2n = 4x = 28, NsNsXmXm) are important wild relatives of common wheat. The Ns chromosomes from two species have been successfully introgressed into wheat through distant hybridization. To compare the genetic effects and evolutionary relationship of Ns chromosomes from different genera in a wheat background, wheat-P. huashanica derivative WH15 and wheat-L. mollis derivative WM14-2 were selected. Sequential FISH-GISH showed that both WH15 and WM14-2 contained 40 wheat chromosomes (with 2D deletion) and two Ns chromosomes with different FISH karyotypes. Molecular markers and SNP array analysis revealed that the two lines both introduced 2Ns chromosomes. However, the P. huashanica 2Ns and L. mollis 2Ns had distinct sequence compositions, and the different SNPs between the two species 2Ns chromosomes were primarily clustered on the short arm. WH15 and WM14-2 exhibited significant differences in spike-related morphologies but shared leaf rust resistance and susceptibility to powdery mildew and Fusarium head blight. Cytogenetic analysis confirmed stable meiotic inheritance of the introduced 2Ns chromosomes. We further developed universal diagnostic markers for 2Ns chromosomes based on SLAF-seq. Therefore, substantial divergence likely exists between the Ns genomes of P. huashanica and L. mollis, and P. huashanica is probably not the direct Ns genome donor for Leymus. Our research-developed derivatives provide unique resources for comparative studies of the structural and functional evolution of homoeologous Ns chromosomes across genera, while offering valuable alleles for wheat improvement. Full article

Nitrogen is an essential nutrient for the growth and development of maize (Zea mays L.), and soil nitrogen deficiency is an important factor limiting maize yield. Although excessive application of nitrogen fertilizer can increase yield, it can also cause environmental problems. Therefore, screening low-nitrogen-tolerant (LNT) germplasm resources and analyzing their genetic mechanisms are of great significance for the development of efficient and environmentally friendly agriculture. In this study, 201 maize inbred lines were used as materials. Two levels of low nitrogen (LN) (0.05 mmol/L, N1) and normal nitrogen (4 mmol/L, N2) were set up. Phenotypic indicators such as seedling length, root length and biomass were measured, and they were classified into LNT type (18 samples), nitrogen-sensitive (NS) type (27 samples) and intermediate type (156 samples). A total of 47 significant SNP loci were detected through a genome-wide association study (GWAS), and 36 candidate genes were predicted. Transcriptome sequencing (RNA-seq) analysis revealed that the differentially expressed genes (753 upregulated and 620 downregulated) in LNT materials under low nitrogen stress (LNS) were significantly fewer than those in NS materials (2436 upregulated and 2228 downregulated). Further analysis using WGCNA identified a total of eight co-expression modules. Among them, the red module was significantly correlated with root length and underground fresh weight under LN conditions (r = 0.75), and three key genes for stress response (Zm00001d005264, Zm00001d053931, Zm00001d044292) were screened out. Combined with GWAS, RNA-seq and qRT-PCR verification, eight candidate genes closely related to LNT at the seedling stage of maize were finally determined, involving biological processes such as stress response, nitrogen metabolism and substance formation. This study initially revealed the molecular mechanism of maize tolerance to LN through multi-omics analysis, providing a theoretical basis and genetic resources for breeding new nitrogen-efficient maize varieties. Full article

Background: Malaria remains a significant global health burden, particularly in sub-Saharan Africa, accounting for high rates of illness and death. The growing resistance to frontline antimalarial therapies underscores the urgent need for novel drug targets and therapeutics. Bromodomain-containing proteins, which regulate gene expression through chromatin remodeling, have gained attention as potential targets. Plasmodium falciparum bromodomain protein 1 (PfBDP1), a 55 kDa nuclear protein, plays a key role in recognizing acetylated lysine residues and facilitating transcription during parasite development. Methods: This study investigated ex vivo PfBDP1 gene mutations and identified potential small molecule inhibitors using computational approaches. Malaria-positive blood samples were collected. Genomic DNA was extracted, assessed for quality, and amplified using PfBDP1-specific primers. DNA sequencing and alignment were performed to determine single-nucleotide polymorphism (SNP). Structural modeling used the PfBDP1 crystal structure (PDB ID: 7M97), and active site identification was conducted using CASTp 3.0. Virtual screening and pharmacophore modeling were performed using Pharmit and AutoDock Vina, followed by ADME/toxicity evaluations with SwissADME, OSIRIS, and Discovery Studio. GROMACS was used for 100 ns molecular dynamics simulations. Results: The malaria prevalence rate stood at 12.24%, and the sample size was 165. Sequencing results revealed conserved PfBDP1 gene sequences compared to the 3D7 reference strain. Virtual screening identified nine lead compounds with binding affinities ranging from −9.8 to −10.7 kcal/mol. Of these, CHEMBL2216838 had a binding affinity of −9.9 kcal/mol, with post-screening predictions of favorable drug-likeness (8.60), a high drug score (0.78), superior pharmacokinetics, and a low toxicity profile compared to chloroquine. Molecular dynamics simulations confirmed its stable interaction within the PfBDP1 active site. Conclusions: Overall, this study makes a significant contribution to the ongoing search for novel antimalarial drug targets by providing both molecular and computational evidence for PfBDP1 as a promising therapeutic target. The prediction of CHEMBL2216838 as a lead compound with favorable binding affinity, drug-likeness, and safety profile, surpassing those of existing drugs like chloroquine, sets the stage for preclinical validation and further structure-based drug design efforts. These findings are supported by prior experimental evidence showing significant parasite inhibition and gene suppression capability of predicted hits. Full article

Background: In Staphylococcus aureus, antimicrobial resistance (AMR) imposes significant fitness costs (FCs), including reduced growth rate, interbacterial competitiveness, and virulence. However, the FC molecular basis remains poorly understood. This study investigated the FC omic basis and compensatory adaptations in high-risk HA-, LA-, and CA-MRSA, acquiring mono- or cross-resistance to second-line daptomycin (DAP) and dalbavancin (DAL), as well as reduced susceptibility (RS) to first-line glycopeptides, i.e., vancomycin and teicoplanin (GLYs, i.e., VAN, TEC), related to the specific mechanism of action (MOA)-related AMR-mechanisms and genomic backgrounds, paying increasing FCs. Methods: The FC omic basis associated with mono- or cross- DAP-/DAL-R and GLY-RS were investigated by integrated omics. This study focused on core-genome essential (EG) and accessory virulence gene (VG) SNPomics and transcriptomics by Illumina MiSeq whole-genome sequencing, RNA-seq, and bioinformatic analysis. Results: Moderate impact nsSNPs were identified in EGs related to vital cellular functions and VGs. Comparative EG transcriptomics revealed differential expressions and key dysregulations—via asRNAs—prevalently affecting the protein synthesis and cell-envelope EG clusters, as well as the VG cluster. Conclusions: Our data, firstly, underlined the EG and VG mutation- and transcription-driven omic-based FC burden and the compensatory adaptations associated with the emergence of mono-DAP-R, cross-DAP-R/hGISA, and DAP-R/DAL-R/GISA, linked to specific MOA-related AMR-mechanisms and genomic backgrounds in high-risk HA-, LA-, and CA-MRSA. Full article

Background: The Jinwu pig is a novel breed created by crossbreeding Jinhua and Duroc pigs, displaying superior meat quality, strong adaptability to coarse feed, high production performance, and a rapid growth rate. However, research on its reproductive traits and genomic characteristics has not been systematically reported. Methods: In this study, we investigated the genetic basis of reproductive traits in Jinwu pigs us-ing a genome-wide association study. We analyzed 2831 breeding records from 516 Jinwu sows to evaluate the effects of fixed factors (farrowing season, parity, and mated boar) on six reproductive traits: the total number of births (TNB), number born alive (NBA), number of healthy offspring produced (NHOP), weak litter size (WLS), number of stillbirths (NS), and number of mummies (NM). Results: A total of 771 genome-wide significant single-nucleotide polymorphisms (SNPs) and ten potential candidate genes associated with pig reproductive traits were identified: VOPP1, PGAM2, TNS3, LRFN5, ORC1, CC2D1B, ZFYYE9, TUT4, DCN, and FEZF1. TT-genotype-carrier individuals of the pleiotropic SNP rs326174997 exhibited significantly higher TNB, NBA, and NHOP trait-related phenotypic values. Conclusions: These findings provide a foundation for the reproductive breeding of Jinwu pigs and offer new insights into molecular genetic breeding in pigs. Full article

Background: Insecticide resistance challenges the vector control efforts towards malaria elimination and proving the development of complementary tools. Targeting the genes that are involved in mosquito fertility and susceptibility to Plasmodium with small molecule inhibitors has been a promising alternative to curb the vector population and drive the transmission down. However, such an approach would require a comprehensive knowledge of the genetic diversity of the targeted genes to ensure the broad efficacy of new tools across the natural vector populations. Methods: Four fertility and parasite susceptibility genes were identified from a systematic review of the literature. The Single Nucleotide Polymorphisms (SNPs) found within the regions spanned by these four genes, genotyped across 2784 wild-caught Anopheles gambiae s.l. from 19 sub-Saharan African (SSA) countries, were extracted from the whole genome SNP data of the Ag1000G project (Ag3.0). The population genetic analysis on gene-specific data included the determination of the population structure, estimation of the differentiation level between the populations, evaluation of the linkage between the non-synonymous SNPs (nsSNPs), and a few statistical tests. Results: As potential targets for small molecule inhibitors to reduce malaria transmission, our set of four genes associated with Anopheles fertility and their susceptibility to Plasmodium comprises the mating-induced stimulator of oogenesis protein (MISO, AGAP002620), Vitellogenin (Vg, AGAP004203), Lipophorin (Lp, AGAP001826), and Haem-peroxidase 15 (HPX15, AGAP013327). The analyses performed on these potential targets of small inhibitor molecules revealed that the genes are conserved within SSA populations of An. gambiae s.l. The overall low Fst values and low clustering of principal component analysis between species indicated low genetic differentiation at all the genes (MISO, Vg, Lp and HPX15). The low nucleotide diversity (>0.10), negative Tajima’s D values, and heterozygosity analysis provided ecological insights into the purifying selection that acts to remove deleterious mutations, maintaining genetic diversity at low levels within the populations. None of MISO nsSNPs were identified in linkage disequilibrium, whereas a few weakly linked nsSNPs with ambiguous haplotyping were detected at other genes. Conclusions: This integrated finding on the genetic features of major malaria vectors’ biological factors across natural populations offer new insights for developing sustainable malaria control tools. These loci were reasonably conserved, allowing for the design of effective targeting with small molecule inhibitors towards controlling vector populations and lowering global malaria transmission. Full article

Background: Programmed cell death protein 1 (PD-1), encoded by the PDCD1 gene, is critical in immune checkpoint regulation and cancer immune evasion. Variants in PDCD1 may alter its function, impacting cancer susceptibility and disease progression. Objectives: This study evaluates the structural, functional, and regulatory impacts of non-synonymous single-nucleotide polymorphisms (nsSNPs) in the PDCD1 gene, focusing on their pathogenic and oncogenic roles. Methods: Computational tools, including PredictSNP1.0, I-Mutant2.0, MUpro, HOPE, MutPred2, Cscape, Cscape-Somatic, GEPIA2, cBioPortal, and STRING, were used to analyze 695 nsSNPs in the PD1 protein. The analysis covered structural impacts, stability changes, regulatory effects, and oncogenic potential, focusing on conserved domains and protein–ligand interactions. Results: The analysis identified 84 deleterious variants, with 45 mapped to conserved regions like the Ig V-set domain essential for ligand-binding interactions. Stability analyses identified 78 destabilizing variants with significant protein instability (ΔΔG values). Ten nsSNPs were identified as potential cancer drivers. Expression profiling showed differential PDCD1 expression in tumor versus normal tissues, correlating with improved survival in skin melanoma but limited value in ovarian cancer. Regulatory SNPs disrupted miRNA-binding sites and transcriptional regulation, affecting PDCD1 expression. STRING analysis revealed key PD-1 protein partners within immune pathways, including PD-L1 and PD-L2. Conclusions: This study highlights the significance of PDCD1 nsSNPs as potential biomarkers for cancer susceptibility, advancing the understanding of PD-1 regulation. Experimental validation and multi-omics integration are crucial to refine these findings and enhance theraputic strategies. Full article

Background: The Signal Transducer and Activator of Transcription 1 (STAT1) gene is an essential component of the JAK-STAT signaling pathway. This pathway plays a pivotal role in the regulation of different cellular processes, including immune responses, cell growth, and apoptosis. Mutations in the STAT1 gene contribute to a variety of immune system dysfunctions. Objectives: We aim to identify disease-susceptible single-nucleotide polymorphisms (SNPs) in STAT1 gene and predict structural changes associated with the mutations that disrupt normal protein–protein interactions using different computational algorithms. Methods: Several in silico tools, such as SIFT, Polyphen v2, PROVEAN, SNAP2, PhD-SNP, SNPs&GO, Pmut, and PANTHER, were used to determine the deleterious nsSNPs of the STAT1. Further, we evaluated the potentially deleterious SNPs for their effect on protein stability using I-Mutant, MUpro, and DDMUT. Additionally, we predicted the functional and structural effects of the nsSNPs using MutPred. We used Alpha-Missense to predict missense variant pathogenicity. Moreover, we predicted the 3D structure of STAT1 using an artificial intelligence system, alphafold, and the visualization of the 3D structures of the wild-type amino acids and the mutant residues was performed using ChimeraX 1.9 software. Furthermore, we analyzed the structural and conformational variations that have resulted from SNPs using Project Hope, while changes in the biological interactions between wild type, mutant amino acids, and neighborhood residues was studied using DDMUT. Conservational analysis and surface accessibility prediction of STAT1 was performed using ConSurf. We predicted the protein–protein interaction using STRING database. Results: In the current study, we identified six deleterious nsSNPs (R602W, I648T, V642D, L600P, I578N, and W504C) and their effect on protein structure, function, and stability. Conclusions: These findings highlight the potential of approaches to pinpoint pathogenic SNPs, providing a time- and cost-effective alternative to experimental approaches. To the best of our knowledge, this is the first comprehensive study in which we analyze STAT1 gene variants using both bioinformatics and artificial-intelligence-based model tools. Full article

Background: Mutations in the EPOR gene can disrupt its normal signaling pathways, leading to hematological disorders such as polycythemia vera and other myeloproliferative diseases. Methodology: In this study, a range of bioinformatics tools, including SIFT, PolyPhen-2, SNAP2, SNPs & Go, PhD-SNP, I-Mutant2.0, MuPro, MutPred, ConSurf, HOPE, and Interpro were used to assess the deleterious effects of missense nonsynonymous single nucleotide polymorphisms (nsSNPs) on protein structure and function. Furthermore, molecular dynamics simulations (MDS) were conducted to assess the structural deviations of the identified mutant variants in comparison to the wild type. Results: The results identified two nsSNPs, R223P and G302S, as deleterious, significantly affecting protein structure and function. Both substitutions occur in functionally conserved regions and are predicted to be pathogenic, associated with altered molecular mechanisms. The MDSs indicated that while the wild-type EPOR maintained optimal stability, the G302S and R223P variants exhibited substantial deviations, adversely affecting overall protein stability and compactness. Conclusions: The computational analysis of missense nsSNPs in the EPOR gene identified two missense SNPs, R223P and G302S, as deleterious, occurring at highly conserved regions, and having substantial effects on erythropoietin receptor (EPO-R) protein structure and function, suggesting their potential pathogenic consequences. Full article

Drug-resistant Morganella morganii, a rod-shaped, Gram-negative, facultatively anaerobic bacillus belonging to the Enterobacteriaceae family, is a growing worldwide health concern due to its association with high morbidity and mortality rates. Recent advancements in machine learning, particularly Alphafold 2’s protein structure prediction using local physics and pattern recognition, have aided research efforts. This study focuses on the enzymatic activity of aminoglycoside N6′-acetyltransferase (aacA7), a critical transferase enzyme in bacteria that confers resistance to aminoglycosides. AacA7 modifies aminoglycoside molecules by catalyzing the acetylation of their 6′-amino group using acetyl-CoA, rendering antibiotics like kanamycin, neomycin, tobramycin, and amikacin inactive. We propose that Doripenem and OncoglabrinolC can interact with aacA7, potentially modifying its enzymatic activity. Molecular docking analysis of aacA7 with 22 drug targets revealed OncoglabrinolC as the most promising candidate, exhibiting a binding energy of −12.82 kcal/mol. These two top candidates, OncoglabrinolC and Doripenem, were then subjected to 100 ns of molecular dynamic simulations to assess their dynamic conformational features. Furthermore, the PredictSNP consensus classifier was used to predict the impact of mutations on aacA7 protein functionality. The study also investigated the interaction of wild-type and mutant aacA7 proteins with both Doripenem and OncoglabrinolC. These findings provide valuable insights into the binding behavior of OncoglabrinolC and Doripenem as potential lead molecules for repurposing against aacA7, potentially reducing the pathogenicity of Morganella morganii. Full article

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 (K_ATP) 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 K_ATP 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 K_ATP 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. Full article