Multi-omics delineate growth factor network underlying exercise effects in an Alzheimer's mouse model.

Physical exercise represents a primary defense against age-related cognitive decline and neurodegenerative disorders like Alzheimer's disease (AD). To impartially investigate the underlying mechanisms, we conducted single-nucleus transcriptomic and chromatin accessibility analyses (snRNA-seq and ATAC-seq) on the hippocampus of mice carrying AD-linked NL-G-F mutations in the amyloid precursor protein gene (APPNL-G-F) following prolonged voluntary wheel-running exercise. Our study reveals that exercise mitigates amyloid-induced changes in both transcriptomic expression and chromatin accessibility through cell type-specific transcriptional regulatory networks. These networks converge on the activation of growth factor signaling pathways, particularly the epidermal growth factor receptor (EGFR) and insulin signaling, correlating with an increased proportion of immature dentate granule cells and oligodendrocytes. Notably, the beneficial effects of exercise on neurocognitive functions can be blocked by pharmacological inhibition of EGFR and the downstream phosphoinositide 3-kinases (PI3K). Furthermore, exercise leads to elevated levels of heparin-binding EGF (HB-EGF) in the blood, and intranasal administration of HB-EGF enhances memory function in sedentary APPNL-G-F mice. These findings offer a panoramic delineation of cell type-specific hippocampal transcriptional networks activated by exercise and suggest EGF-related growth factor signaling as a druggable contributor to exercise-induced memory enhancement, thereby suggesting therapeutic avenues for combatting AD-related cognitive decline.

Molecular characterization of circadian gene expression and its correlation with survival percentage in colorectal cancer patients.

Colorectal cancer (CRC) is a form of cancer characterized by many symptoms and readily metastasizes to different organs in the body. Circadian rhythm is one of the many processes that is observed to be dysregulated in CRC-affected patients. In this study, we aim to identify the dysregulated physiological processes in CRC-affected patients and correlate the expression profiles of the circadian clock genes with CRC-patients' survival rates. We performed an extensive microarray gene expression pipeline, whereby 471 differentially expressed genes (DEGs) were identified, following which, we streamlined our search to 43 circadian clock affecting DEGs. The Circadian Gene Database was accessed to retrieve the circadian rhythm-specific genes. The DEGs were then subjected to multi-level functional annotation, i.e., preliminary analysis using ClueGO/CluePedia and pathway enrichment using DAVID. The findings of our study were interesting, wherein we observed that the survival percentage of CRC-affected patients dropped significantly around the 100th-month mark. Furthermore, we identified hormonal activity, xenobiotic metabolism, and PI3K-Akt signaling pathway to be frequently dysregulated cellular functions. Additionally, we detected that the ZFYVE family of genes and the two genes, namely MYC and CDK4 were the significant DEGs that are linked to the pathogenesis and progression of CRC. This study sheds light on the importance of bioinformatics to simplify our understanding of the interactions of different genes that control different phenotypes.

SARS-CoV-2 vaccine breakthrough infections (VBI) by Omicron variant (B.1.1.529) and consequences in structural and functional impact.

This study investigated the efficacy of existing vaccines against hospitalization and infection due to the Omicron variant of COVID-19, particularly for those who received two doses of Moderna or Pfizer vaccines and one dose of Johnson & Johnson vaccine or who were vaccinated more than five months before. A total of 36 variants in Omicron's spike protein, targeted by all three vaccinations, have made antibodies less effective at neutralizing the virus. The genotyping of the SARS-CoV-2 viral sequence revealed clinically significant variants such as E484K in three genetic mutations (T95I, D614G, and del142-144). A woman showed two of these mutations, indicating a potential risk of infection after successful immunization, as recently reported by Hacisuleyman (2021). We examine the effects of mutations on domains (NID, RBM, and SD2) found at the interfaces of the spike domains Omicron B.1.1529, Delta/B.1.1529, Alpha/B.1.1.7, VUM B.1.526, B.1.575.2, and B.1.1214 (formerly VOI Iota). We tested the affinity of Omicron for ACE2 and found that the wild- and mutant-spike proteins were using atomistic molecular dynamics simulations. According to the binding free energies calculated during mutagenesis, the ACE2 bound Omicron spikes more strongly than the wild strain SARS-CoV-2. T95I, D614G, and E484K are three substitutions that significantly contribute to RBD, corresponding to ACE2 binding energies and a doubling of the electrostatic potential of Omicron spike proteins. The Omicron appears to bind to ACE2 with greater affinity, increasing its infectivity and transmissibility. The spike virus was designed to strengthen antibody immune evasion through binding while boosting receptor binding by enhancing IgG and IgM antibodies that stimulate human ß-cell, as opposed to the wild strain, which has more vital stimulation of both antibodies.

CDK regulators-Cell cycle progression or apoptosis-Scenarios in normal cells and cancerous cells.

Serine/threonine kinases called cyclin-dependent kinases (CDKs) interact with cyclins and CDK inhibitors (CKIs) to control the catalytic activity. CDKs are essential controllers of RNA transcription and cell cycle advancement. The ubiquitous overactivity of the cell cycle CDKs is caused by a number of genetic and epigenetic processes in human cancer, and their suppression can result in both cell cycle arrest and apoptosis. This review focused on CDKs, describing their kinase activity, their role in phosphorylation inhibition, and CDK inhibitory proteins (CIP/KIP, INK 4, RPIC). We next compared the role of different CDKs, mainly p21, p27, p57, p16, p15, p18, and p19, in the cell cycle and apoptosis in cancer cells with respect to normal cells. The current work also draws attention to the use of CDKIs as therapeutics, overcoming the pharmacokinetic barriers of pan-CDK inhibitors, analyze new chemical classes that are effective at attacking the CDKs that control the cell cycle (cdk4/6 or cdk2). It also discusses CDKI's drawbacks and its combination therapy against cancer patients. These findings collectively demonstrate the complexity of cancer cell cycles and the need for targeted therapeutic intervention. In order to slow the progression of the disease or enhance clinical outcomes, new medicines may be discovered by researching the relationship between cell death and cell proliferation.

Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach.

Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.

Analysis of signaling cascades from myeloma cells treated with pristimerin.

Multiple myeloma (MM) is the 2nd most frequently diagnosed blood cancer after non-Hodgkin's lymphoma. The present study aimed to identify the differentially expressed genes (DEGs) between the control and pristimerin-treated MM cell lines. We examined the GSE14011 microarray dataset and screened DEGs with GEO2R statistical tool using the inbuilt limma package. We used a bioinformatics pipeline to identify the differential networks, signaling cascades, and the survival of the hub genes. We implemented two different enrichment analysis including ClueGO and Metacore™, to get accurate annotation for most significant DEGs. We screened the most significant 408 DEGs from the dataset based on p-values and logFC values. Using protein network analysis, we found the genes UBC, HSP90AB1, HSPH1, HSPA1B, HSPA1L, HSPA6, HSPD1, DNAJB1, HSPE1, DNAJC10, BAG3, and DNAJC7 had higher node degree distribution. In contrast, the functional annotation provided that the DEGs were predominantly enriched in B-cell receptor signaling, unfolded protein response, positive regulation of phagocytosis, HSP70, and HSP40-dependent folding, and ubiquitin-proteasomal proteolysis. Using network algorithms, and comparing enrichment analysis, we found the hub genes enriched were INHBE, UBC, HSPA1A, HSP90AB1, IKBKB, and BAG3. These DEGs were further validated with overall survival and gene expression analysis between the tumor and control groups. Finally, pristimerin effects were validated independently in a cell line model consisting of IM9 and U266 MM cells. Pristimerin induced in vitro cytotoxicity in MM cells in a dose-dependent manner. Pristimerin inhibited NF-κB, induced accumulation of ubiquitinated proteins and inhibited HSP60 in the validation of bioinformatics findings, while pristimerin-induced caspase-3 and PARP cleavage confirmed cell death. Taken together, we found that the identified DEGs were strongly associated with the apoptosis induced in MM cell lines due to pristimerin treatment, and combinatorial therapy derived from pristimerin could act as novel anti-myeloma multifunctional agents.

Identification of dysregulated canonical pathways associated with pathogenesis and progression of Amyotrophic Lateral Sclerosis-An integrated bioinformatics approach.

The mechanisms responsible for the pathogenesis and progression of Amyotrophic Lateral Sclerosis (ALS) remain poorly understood, making the diagnosis of ALS challenging. We aimed to find the novel gene biomarkers via computationally analyzing microarray expression studies, in three different cell lineages, namely myotube cells, astrocyte cells and oligodendrocyte cells. Microarray gene expression profiles were obtained and analyzed for three cell types: myotube cell lineage (GSE122261), astrocyte, and oligodendrocyte cell lineage (GSE87385). A comprehensive computational pipeline, tailored explicitly for microarray gene expression profiling studies, was devised to analyze the sample groups, wherein the myotube sample group comprised of six control (GSM3462697, GSM3462698, GSM3462699, GSM3462700, GSM3462701, GSM3462702) & six diseased (GSM3462691, GSM3462692, GSM3462693, GSM3462694, GSM3462695, GSM3462696) samples were considered. Similarly, for the astrocyte sample group two samples each for the control (GSM2330040, GSM2330042) and the diseased (GSM2330039, GSM2330041), and for the oligodendrocyte sample group, 2 control (GSM2330043, GSM2330045) samples and two diseased (GSM2330044, GSM2330046) samples were considered for the current study. The in-depth interaction of these DEGs was studied using MCODE and subjected to preliminary functional analysis using ClueGO/CluePedia plug-in. Qiagen's IPA software was employed for enrichment analysis, which generated the key canonical pathways and a list of potential biomarker molecules specific to each sample group. The preliminary analysis yielded 512 DEGs across all 3-sample groups, wherein 139 DEGs belonged to the myotube sample group, 216 DEGs for the astrocyte sample group, and 157 DEGs for the oligodendrocytes sample group. The data suggests growth hormone signaling and its activity, ErbB signaling pathway, and JAK/STAT signaling pathway are some of the pathways that are significantly dysregulated and play a crucial role in the development and progression of ALS. KISS1R and CSHL1 are potential genes that could act as diagnostic biomarkers in myotube cell types. Also, KRAS, TGFB2, JUN, and SMAD6 genes may be used as prognostic biomarkers to differentiate between early and late-stage ALS-diseased patients.

Elucidating the mechanism of antimicrobial resistance in Mycobacterium tuberculosis using gene interaction networks.

Antimicrobial resistance (AMR) in microorganisms is an urgent global health threat. AMR of Mycobacterium tuberculosis is associated with significant morbidity and mortality. It is of great importance to underpin the resistance pathways involved in the mechanisms of AMR and identify the genes that are directly involved in AMR. The focus of the current study was the bacteria M. tuberculosis, which carries AMR genes that give resistance that lead to multidrug resistance. We, therefore, built a network of 43 genes and examined for potential gene-gene interactions. Then we performed a clustering analysis and identified three closely related clusters that could be involved in multidrug resistance mechanisms. Through the bioinformatics pipeline, we consistently identified six-hub genes (dnaN, polA, ftsZ, alr, ftsQ, and murC) that demonstrated the highest number of interactions within the clustering analysis. This study sheds light on the multidrug resistance of MTB and provides a protocol for discovering genes that might be involved in multidrug resistance, which will improve the treatment of resistant strains of TB.

Gene network interaction analysis to elucidate the antimicrobial resistance mechanisms in the Clostridiumdifficile.

Antimicrobial resistance has caused chaos worldwide due to the depiction of multidrug-resistant (MDR) infective microorganisms. A thorough examination of antimicrobial resistance (AMR) genes and associated resistant mechanisms is vital to solving this problem. Clostridium difficile (C. difficile) is an opportunistic nosocomial bacterial strain that has acquired exogenous AMR genes that confer resistance to antimicrobials such as erythromycin, azithromycin, clarithromycin, rifampicin, moxifloxacin, fluoroquinolones, vancomycin, and others. A network of interactions, including 20 AMR genes, was created and analyzed. In functional enrichment analysis, Cellular components (CC), Molecular Functions (MF), and Biological Processes (BP) were discovered to have substantial involvement. Mutations in the rpl genes, which encode ribosomal proteins, confer resistance in Gram-positive bacteria. Full erythromycin and azithromycin cross-resistance can be conferred if more than one of the abovementioned genes is present. In the enriched BP, rps genes related to transcriptional regulation and biosynthesis were found. The genes belong to the rpoB gene family, which has previously been related to rifampicin resistance. The genes rpoB, gyrA, gyrB, rpoS, rpl genes, rps genes, and Van genes are thought to be the hub genes implicated in resistance in C. difficile. As a result, new medications could be developed using these genes. Overall, our observations provide a thorough understanding of C. difficile AMR mechanisms.

HPV and molecular mimicry in systemic lupus erythematosus and an impact of compiling B-cell epitopes and MHC-class II binding profiles with in silico evidence.

Epidemiological link between HPV and SLE is evolving. The possibility of HPV infection-induced molecular mimicry and systemic lupus erythematosus (SLE) was elucidated through detailed in silico analyses. Conserved regions in the structural protein sequences of high-risk HPV types were inferred, and sequence homologies between viral and human peptides were identified to delineate proteins implicated in SLE. B-cell epitopes and MHC-class II binding were compiled using Immune Epitope Database and ProPred II analysis tool. Molecular modeling and molecular dynamics/simulation (MDS) were performed using AutoDock Vina and GROMACS, respectively. Sequence alignment revealed 32 conserved regions, and 27/32 viral peptides showed varying similarities to human peptides, rich in B-cell epitopes with superior accessibility, high hydrophilicity, antigenicity and disposition to bind many class-II HLA alleles. Molecular docking of 13 viral peptides homologous (100%) to human peptides implicated in SLE showed that VIR-PEP1 (QLFNKPYWL) and VIR-PEP2 (DTYRFVTS) exhibited higher binding affinities than corresponding human peptides to SLE predisposing HLA-DRB1 allele. MDS of these peptides showed that the viral peptides had superior folding, compactness, and a higher number of hydrogen bonds than human peptides throughout the simulation period. SASA analysis revealed that the VIR-PEP1&2 fluctuated less frequently than corresponding human peptides. MM-PBSA revealed that the VIR-PEP2 complex exhibited higher binding energy than the human peptide complex. This suggests that highly conserved structural peptides of high-risk HPV types homologous to human peptides could compete and bind avidly to the HLA allele associated with SLE and predispose HPV-infected individuals to SLE through molecular mimicry.Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening to identify potential lipase inhibitors to reduce lipid storage in Wolman disorder.

Wolman disorder (WD) was first described in Iranian-Jewish (IJ) children, and it is caused by a deficiency of the lysosomal acid lipase (LAL). Newborns with WD are healthy and active at birth but soon develop severe malnutrition symptoms and often die before 1 year. In particular, spleens, livers, bone marrows, intestines, adrenal glands, and lymph nodes accumulate harmful amounts of lipids. G87V mutation in LIPA is responsible for Wolman disorder. Some reports suggest that δ-tocopherol can reduce lipid accumulation in cholesterol storage disorders. Hence, we used δ-tocopherol for the virtual screening process in this study. Initially, the lead compounds were docked with native and G87V mutant LIPA. Subsequently, the ADME and toxicity parameters for screened compounds were determined to ensure the safety profiles. Finally, the molecular dynamics simulations result indicated that dl-alpha-Tocopherol-13C3, a molecule obtained from the PubChem database, is identified as a potential and stable lead molecule that could be effective against the G87V mutant form of LIPA.

Multispectroscopic, virtual and in vivo insights into the photoaging defense mediated by the natural food colorant bixin.

An upsurge in early onset of photoaging due to repeated skin exposure to environmental stressors such as UV radiation is a challenge for pharmaceutical and cosmeceutical divisions. Current reports indicate severe side effects because of chemical or synthetic inhibitors of matrix metalloproteases (MMPs) in anti-skin aging cosmeceuticals. We evaluated the adequacy of bixin, a well-known FDA certified food additive, as a scavenger of free radicals and its inhibitory mechanism of action on MMP1, collagenase, elastase, and hyaluronidase. The anti-skin aging potential of bixin was evaluated by several biotechnological tools in silico, in vitro and in vivo. Molecular docking and simulation dynamics studies gave a virtual insight into the robust binding interaction between bixin and skin aging-related enzymes. Absorbance and fluorescence studies, enzyme inhibition assays, enzyme kinetics and in vitro bioassays of human dermal fibroblast (HDF) cells highlighted bixin's role as a potent antioxidant and inhibitor of skin aging-related enzymes. Furthermore, in vivo protocols were carried out to study the impact of bixin administration on UVA induced photoaging in C57BL/6 mice skin. Here, we uncover the UVA shielding effect of bixin and its efficacy as a novel anti-photoaging agent. Furthermore, the findings of this study provide a strong foundation to explore the pharmaceutical applications of bixin in several other biochemical pathways linked to MMP1, collagenase, elastase, and hyaluronidase.

SARS-CoV-2 vaccine-breakthrough infections (VBIs) by Omicron (B.1.1.529) variant and consequences in structural and functional impact

This study investigated the efficacy of existing vaccinations against hospitalization and infection due to the Omicron variant of COVID-19, particularly for those who received two doses of Moderna or Pfizer vaccines and one dose of a vaccine by Johnson & Johnson or who were vaccinated more than five months previously. A total of 36 variants in Omicrons spike protein, targeted by all three vaccinations, have made antibodies less effective at neutralizing the virus. Genotyping of SARS-CoV-2 viral sequencing revealed clinically significant variants such as E484K in three genetic mutations (T95I, D614G, and del142-144). One woman displayed two of these mutations, indicating a potential risk of infection following successful immunization, as recently reported by Hacisuleyman (2021). We examined the effects of mutations on domains (NID, RBM, and SD2) found at the interfaces of spike domains Omicron B.1.1529, Delta/B.1.1529, Alpha/B.1.1.7, VUM B.1.526, B.1.575.2, and B.1.1214 (formerly VOI Iota). We tested the affinity of Omicron for hACE2 and found that the wild and mutant spike proteins were using atomistic molecular dynamics simulations. According to binding free energies calculated during mutagenesis, hACE2 bound Omicron spike more strongly than SARS-CoV-2 wild strain. T95I, D614G, and E484K are three substitutions that significantly contribute to the RBD, corresponding to hACE2 binding energies and a doubling of Omicron spike proteins electrostatic potential. Omicron appears to bind hACE2 with greater affinity, increasing its infectivity and transmissibility. The spike virus was designed to strengthen antibody immune evasion through binding while boosting receptor binding by enhancing IgG and IgM antibodies that stimulate human {beta}-cell, as opposed to the wild strain, which has more vital stimulation of both antibodies.

Deciphering the effect of mutations in MMAA protein causing methylmalonic acidemia-A computational approach.

Methylmalonic acidemia (MMA) is a rare genetic disorder affecting multiple body systems. We aimed to investigate the pathogenic mutations in MMAA that are associated with isolated methylmalonic acidemia to identify the structural behavior of MMAA upon mutation. The algorithms such as PredictSNP, iStable, ConSurf, and Align GVGD were employed to analyze the consequence of the mutations. Molecular docking was carried out for the native MMAA, L89P, G274D, and R359G to interpret its interactions with the GDP substrate. The docked complexes were simulated for 200ns aiding GROMACS in apprehending the behavior of MMAA upon mutation and GDP binding. After simulation, cα disruptions were observed using the RMSF plot, which indicated that several regions of mutant MMAAs have highly fluctuated. The gyration and H-bond plots were used to understand the compactness and intermolecular interaction with the GDP molecule. The MDS analysis showed that the mutations L89P, G274D, and R359G are highly unstable even after GDP binding, with the least compactness, fewer H-bonds, and larger conformational cα motions. Our study provided structural and dynamic insights into MMAA protein, which further helps to characterize these mutants and provide potential treatment strategies for MMA patients.

Computational and structural investigation of Palmitoyl-Protein Thioesterase 1 (PPT1) protein causing Neuronal Ceroid Lipofuscinoses (NCL).

The Neuronal Ceroid Lipofuscinoses (NCL) are a group of progressive neurodegenerative disorders, associated with 14 Ceroid Lipofuscinosis Neuronal genes (CLN1-14). The mutations in the Palmitoyl-Protein Thioesterase 1 (PPT1) protein serve as one of the major reasons for the causative of NCL. The PPT1 involves degrading and modifying cysteine residues in proteins or peptides by removing thioester-linked fatty acyl groups like palmitate prefers acyl chains of 14-18 carbons in length. In this study, we have analyzed the impact of PPT1 mutations on the deleteriousness, stability, conservative nature of amino acid, and impact of mutations on the protein structure. We have also used molecular dynamics simulations using GROMACS to perceive the alteration in the dynamic behavior of the PPT1 at the residual level. In this study, we have retrieved 23 PPT1 mutations from the UniProt database, and these were subjected to a series of analyses using varied computer algorithms. From these analyses, out of 23 mutations, 16 mutations were identified as deleterious. Among 16, eight mutations were identified to destabilize the protein structure, and finally, two mutations (W38C and L222P) were found to be positioned in the highly conserved region. The structural impact study observed that the mutant proline could disrupt the alpha helix formed by the leucine at position 222. Finally, from the molecular dynamics simulations, we observed that due to the mutations (W38C and L222P), the protein had experienced higher deviation, fluctuation, and lower compactness. These structural changes elucidate that these mutations can impact the structure and function of the PPT1 protein.

Integrative ontology and pathway-based approach identifies distinct molecular signatures in transcriptomes of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) remains a serious concern globally due to many factors that including late diagnosis, lack of an ideal biomarker for diagnosis and prognosis, and high rate of mortality. In this study, we aimed to identify the essential dysregulated genes and molecular signatures associated with the progression and development of ESCC. The dataset with 15 ESCCs and the 15 adjacent normal tissue samples from the surrounding histopathologically tumor-free mucosa was selected. We applied bioinformatics pipelines including various topological parameters from MCODE, CytoNCA, and cytoHubba to prioritize the most significantly associated DEGs with ESCC. We performed functional enrichment annotation for the identified DEGs using DAVID and MetaCore™ GeneGo platforms. Furthermore, we validated the essential core genes in TCGA and GTEx datasets between the normal mucosa and ESCC for their expression levels. These DEGs were primarily enriched in positive regulation of transferase activity, negative regulation of organelle organization, cell cycle mitosis/S-phase transition, spindle organization/assembly, development, and regulation of angiogenesis. Subsequently, the DEGs were associated with the pathways such as oocyte meiosis, cell cycle, and DNA replication. Our study identified the eight-core genes (AURKA, AURKB, MCM2, CDC20, TPX2, PLK1, FOXM1, and MCM7) that are highly expressed among the ESCC, and TCGA dataset. The multigene comparison and principal component analysis resulted in elevated signals for the AURKA, MCM2, CDC20, TPX2, PLK1, and FOXM1. Overall, our study reported GO profiles and molecular signatures that might help researchers to grasp the pathological mechanisms underlying ESCC development and eventually provide novel therapeutic and diagnostic strategies.

Investigation of differentially expressed genes and dysregulated pathways involved in multiple sclerosis.

Multiple Sclerosis (MS) is a neurodegenerative autoimmune and organ-specific demyelinating disorder, known to affect the central nervous system (CNS). While genetic studies have revealed several critical genes and diagnostic biomarkers associated with MS, the etiology of the disease remains poorly understood. This study is aimed at screening and identifying the key genes and canonical pathways associated with MS. Gene expression profiling of the microarray dataset GSE38010 was used to analyze two control brain samples (control 1; GSM931812, control 2; GSM931813), active inflammation stage samples (CAP1; GSM931815, CAP2; GSM931816) and late subsided stage samples (CP1; GSM931817, CP2; GSM931818) collected from patients ranging between 23 and 54years and both genders. This analysis yielded a list of 58,866 DEGs (29,433 for active-inflammation stage and 29,433 for late-subsided Stage). The interactions between the DEGs were then studied using STRING, Cytoscape software, and MCODE was employed to find the genes that form clusters. Functional enrichment and integrative analysis were performed using ClueGO/CluePedia and MetaCore™. Our data revealed dysregulated key canonical pathways in MS patients. In addition, we identified three hub genes (SCN2A, HTR2A, and HCN1) that may serve as potential biomarkers for the prognosis of MS. Furthermore, the expression patterns of HPCA and PLCB1 provide insights into the progressive stages of MS, indicating that these genes could be used in predicting MS progression. We were able to map potential biomarkers that could be used for the prognosis and diagnosis of MS.

A review of bioinformatics tools and web servers in different microarray platforms used in cancer research.

Over the past decade, conventional lab work strategies have gradually shifted from being limited to a laboratory setting towards a bioinformatics era to help manage and process the vast amounts of data generated by omics technologies. The present work outlines the latest contributions of bioinformatics in analyzing microarray data and their application to cancer. We dissect different microarray platforms and their use in gene expression in cancer models. We highlight how computational advances empowered the microarray technology in gene expression analysis. The study on protein-protein interaction databases classified into primary, derived, meta-database, and prediction databases describes the strategies to curate and predict novel interaction networks in silico. In addition, we summarize the areas of bioinformatics where neural graph networks are currently being used, such as protein functions, protein interaction prediction, and in silico drug discovery and development. We also discuss the role of deep learning as a potential tool in the prognosis, diagnosis, and treatment of cancer. Integrating these resources efficiently, practically, and ethically is likely to be the most challenging task for the healthcare industry over the next decade; however, we believe that it is achievable in the long term.

Computational structural assessment of BReast CAncer type 1 susceptibility protein (BRCA1) and BRCA1-Associated Ring Domain protein 1 (BARD1) mutations on the protein-protein interface.

Breast cancer type 1 susceptibility protein (BRCA1) is closely related to the BRCA2 (breast cancer type 2 susceptibility protein) and BARD1 (BRCA1-associated RING domain-1) proteins. The homodimers were formed through their RING fingers; however they form more compact heterodimers preferentially, influencing BRCA1 residues 1-109 and BARD1 residues 26-119. We implemented an integrative computational pipeline to screen all the mutations in BRCA1 and identify the most significant mutations influencing the Protein-Protein Interactions (PPI) in the BRCA1-BARD1 protein complex. The amino acids involved in the PPI regions were identified from the PDBsum database with the PDB ID: 1JM7. We screened 2118 missense mutations in BRCA1 and none in BARD1 for pathogenicity and stability and analyzed the amino acid sequences for conserved residues. We identified the most significant mutations from these screenings as V11G, M18K, L22S, and T97R positioned in the PPI regions of the BRCA1-BARD1 protein complex. We further performed protein-protein docking using the ZDOCK server. The native protein-protein complex showed the highest binding score of 2118.613, and the V11G mutant protein complex showed the least binding score of 1992.949. The other three mutation protein complexes had binding scores between the native and V11G protein complexes. Finally, a molecular dynamics simulation study using GROMACS was performed to comprehend changes in the BRCA1-BARD1 complex's binding pattern due to the mutation. From the analysis, we observed the highest deviation with lowest compactness and a decrease in the intramolecular h-bonds in the BRCA1-BARD1 protein complex with the V11G mutation compared to the native complex or the complexes with other mutations.

Mutations in G6PC2 gene with increased risk for development of type 2 diabetes: Understanding via computational approach.

An increase in the fast blood glucose (FBG) levels has been linked to an increased risk of developing a chronic condition, type 2 diabetes (T2D). The mutation in the G6PC2 gene was identified to have a lead role in the modulation of FBG levels. The abnormal regulation of this enzyme influences glucose-stimulated insulin secretion (GSIS), which controls the insulin levels corresponding to the system's glucose level. This study focuses on the mutations at the G6PC2 gene, which cause the variation from normal expression levels and increase the risk of T2D. We examined the non-synonymous single nucleotide polymorphisms (nsSNPs) present in the G6PC2 and subjected them to pathogenicity, stability, residue conservation, and membrane simulation. The individual representation of surrounding amino acids in the mutant (I63T) model showed the loss of hydrophobic interactions compared to the native G6PC2. In addition, the trajectory results from the membrane simulation exhibited reduced stability, and the least compactness was identified for the I63T mutant model. Our study shed light on the structural and conformational changes at the transmembrane region due to the I63T mutation in G6PC2. Additionally, the Gibbs free energy landscape analysis against the two principal components showed structural differences and decreased the conformational stability of the I63T mutant model compared to the native. Like those presented in this study, dynamical simulations may indeed be crucial to comprehending the structural insights of G6PC2 mutations in cardiovascular-associated mortality and T2D.