In silico identification of potential phytochemical inhibitors for mpox virus: molecular docking, MD simulation, and ADMET studies.

The mpox virus (MPXV), a member of the Poxviridae family, which recently appeared outside of the African continent has emerged as a global threat to public health. Given the scarcity of antiviral treatments for mpox disease, there is a pressing need to identify and develop new therapeutics. We investigated 5715 phytochemicals from 266 species available in IMMPAT database as potential inhibitors for six MPXV targets namely thymidylate kinase (A48R), DNA ligase (A50R), rifampicin resistance protein (D13L), palmytilated EEV membrane protein (F13L), viral core cysteine proteinase (I7L), and DNA polymerase (E9L) using molecular docking. The best-performing phytochemicals were also subjected to molecular dynamics (MD) simulations and in silico ADMET analysis. The top phytochemicals were forsythiaside for A48R, ruberythric acid for A50R, theasinensin F for D13L, theasinensin A for F13L, isocinchophyllamine for I7L, and terchebin for E9L. Interestingly, the binding energies of these potential phytochemical inhibitors were far lower than brincidofovir and tecovirimat, the standard drugs used against MPXV, hinting at better binding properties of the former. These findings may pave the way for developing new MPXV inhibitors based on natural product scaffolds. However, they must be further studied to establish their inhibitory efficacy and toxicity in in vitro and in vivo models.

Molecular detection of monkeypox and related viruses: challenges and opportunities.

The recent widespread emergence of monkeypox (mpox), a rare and endemic zoonotic disease by monkeypox virus (MPXV), has made global headlines. While transmissibility (R0 ≈ 0.58) and fatality rate (0-3%) are low, as it causes prolonged morbidity, the World Health Organization has declared monkeypox as a public health emergency of international concern. Thus, effective containment and disease management require quick and efficient detection of MPXV. In this bioinformatic overview, we summarize the numerous molecular tests available for MPXV, and discuss the diversity of genes and primers used in the polymerase chain reaction-based detection. Over 90 primer/probe sets are used for the detection of poxviruses. While hemagglutinin and A-type inclusion protein are the most common target genes, tumor necrosis factor receptor and complement binding protein genes are frequently used for distinguishing Clade I and Clade II of MPXV. Problems and possibilities in the detection of MPXV have been discussed.

Biobanking for Translational Diabetes Research in India.

India is declared as the diabetic capital of the world. Clinically well-annotated blood samples will advance diabetes research for better diagnostic and treatment methods. Building a disease-specific biobank with high-quality peripheral blood mononuclear cells (PBMCs) and clinical follow-up data system will serve as a good platform for clinical research in diabetes. Processing and storage of high-quality biospecimen for translational research in diabetes demand the implementation of good clinical laboratory practices. "Certification or accreditation programs" that improve biorepository processes and frameworks are lacking in Indian context. To sustain and translate the research into clinical practice, good governance of the biobank and financial resources is required. For ethical issues related to health needs of the people and participants in the research, issues related to research process, translational research, and commercialization, data sharing should be addressed. For India to be an innovation and sustainable country Indian government is supporting translational research facilities, including biobanks. India has developed biobanks for various diseases; however, diabetes-specific research biorepository is lacking. Given the dangers of diabetic burden, India should set up a diabetes disease-specific repository learning from the global organizations and customize to the needs of Indian context. It is important to have private agencies get involved to develop biobanks and future research as there are commercial goals to translate research into practice. New technologies of specimen storing and preservation, data management, and data sharing should be adopted for developing cost-effective long-standing disease-specific population biobank in India.

Identification of novel predictive factors for post surgical corneal haze.

Molecular factors altered in corneas that develop haze post refractive surgery have been described, but pre-existing factors that predispose clinically normal corneas to aberrant fibrosis post surgery and the role of the corneal epithelium remains unknown. We analyzed the global gene expression in epithelium collected intraoperatively from subjects undergoing photorefractive keratectomy. Subjects were grouped into those that developed haze 12 months post surgery (n = 6 eyes; haze predisposed) and those that did not develop haze in a similar follow up duration (n = 11 eyes; controls). Ontological analysis of 1100 upregulated and 1780 downregulated genes in the haze predisposed group revealed alterations in pathways associated with inflammation, wnt signaling, oxidative stress, nerve functions and extra cellular matrix remodeling. Novel factors such as PREX1, WNT3A, SOX17, GABRA1and PXDN were found to be significantly altered in haze predisposed subjects and those with active haze(n = 3), indicating their pro-fibrotic role. PREX1 was significantly upregulated in haze predisposed subjects. Ectopic expression of PREX1 in cultured human corneal epithelial cells enhanced their rate of wound healing while its ablation using shRNA reduced healing compared to matched controls. Recombinant TGFß treatment in PREX1 overexpressing corneal cells led to enhanced αSMA expression and Vimentin phosphorylation while the converse was true for shPREX1 expressing cells. Our data identify a few novel factors in the corneal epithelium that may define a patient's risk to developing post refractive corneal haze.

Integrative gene ontology and network analysis of coronary artery disease associated genes suggests potential role of ErbB pathway gene EGFR.

Coronary artery disease (CAD) is a major cause of mortality in India, more importantly the young Indians. Combinatorial and integrative approaches to evaluate pathways and genes to gain an improved understanding and potential biomarkers for risk assessment are required. Therefore, 608 genes from the CADgene database version 2.0, classified into 12 functional classes representing the atherosclerotic disease process, were analyzed. Homology analysis of the unique list of gene ontologies (GO) from each functional class gave 8 GO terms represented in 11 and 10 functional classes. Using disease ontology analysis 80 genes belonging to 8 GO terms, using FunDO suggested that 29 of them were identified to be associated with CAD. Extended network analysis of these genes using STRING version 9.1 gave 328 nodes and 4,525 interactions of which the top 5% had a node degree of ≥75 associated with pathways including the ErbB signaling pathway with epidermal growth factor receptor (EGFR) gene as the central hub. Evaluation of EFGR protein levels in age and gender­matched 342 CAD patients vs. 342 control subjects demonstrated significant differences [controls=149.76±2.47 pg/ml and CAD patients stratified into stable angina (SA)=161.65±3.40 pg/ml and myocardial infarction (MI)=171.51±4.26 pg/ml]. Logistic regression analysis suggested that increased EGFR levels exhibit 3­fold higher risk of CAD [odds ratio (OR) 3.51, 95% confidence interval [CI] 1.96­6.28, P≤0.001], upon adjustment for hypertension, diabetes and smoking. A unit increase in EGFR levels increased the risk by 2­fold for SA (OR 2.58, 95% CI 1.25­5.33, P=0.01) and 3.8­fold for MI (OR 3.82, 95% CI 1.94­7.52, P≤0.001) following adjustment. Thus, the use of ontology mapping and network analysis in an integrative manner aids in the prioritization of biomarkers of complex disease.

In-Cardiome: integrated knowledgebase for coronary artery disease enabling translational research.

Database URL: www.tri-incardiome.org.

Danger-recognizing proteins, ß-defensin-128 and histatin-3, as potential biomarkers of recurrent coronary events.

Conventional risk factors have limited ability to predict recurrent events in subjects with first-time coronary artery disease (CAD). This aim of this study was to identify novel biomarkers using comparative global proteome analysis to improve the risk assessment for recurrent coronary events. We used samples from phase-I of the Indian Atherosclerosis Research Study (IARS), consisting of 2,332 subjects, of whom 772 were CAD-affected subjects, including 152 with recurrent events identified during a 5-year follow-up period. Global proteome analysis was performed on serum samples of 85 subjects with recurrent coronary events and 85 age- and gender-matched subjects with first-time CAD using surface-enhanced laser desorption ionization time-of-flight mass spectrometry with CM10 arrays. TagIdent was used for protein identification followed by validation by western blot analysis and ELISA. Data were analyzed by logistic analysis, Cox-regression, hazards ratio, C-statistics and combined-marker risk score using SPSS version-17 and R-package version-2.13.0 software. We identified 16 significantly differentially expressed protein peaks. Of these, 2 peaks corresponding to m/z 8588 and 1864 were identified as ß-defensin-128 and histatin-3, belonging to the danger-recognizing peptide family, which exhibited a significant independent association with recurrent events (odds ratios of 7.49 and 1.4, respectively). C-statistics improved significantly from 0.677 for conventional risk factors alone to 0.800 (p-value=0.001) in combination with ß-defensin-128 and histatin-3 with a hazards ratio of 1.833. A combined risk score of ß-defensin-128 and histatin-3 could reclassify 112 out of the 170 subjects into intermediate- and high-risk groups. On the whole, our data indicate that ß-defensin-128 and histatin-3 may be potential biomarkers whch may be used to improve risk the stratification for recurrent coronary events.

Understanding the progression of atherosclerosis through gene profiling and co-expression network analysis in Apob(tm2Sgy)Ldlr(tm1Her) double knockout mice.

The objective of the study was to gain molecular insights into the progression of atherosclerosis in Apob(tm2Sgy)Ldlr(tm1Her) mice, using transcriptome profiles. Weighted gene co network analysis (WGCNA) and time course analysis using limma were used to study disease progression from 0 to 20weeks. Five co-expression modules were identified by WGCNA using the expression values of 2153 genes. Genes associated with autophagy, endoplasmic reticulum stress, inflammation and lipid metabolism were differentially expressed at early stages of atherosclerosis. Time course analysis highlighted activation of inflammatory gene signaling at 4weeks, cell proliferation and calcification at 8weeks, amyloid like structures and oxidative stress at 14weeks and enhanced production of inflammatory cytokines at 20weeks. Our results suggest that maximum gene perturbations occur during early atherosclerosis which could be the danger signals associated with subclinical disease. Understanding these genes and associated pathways can help in improvement of diagnostic and therapeutic targets for atherosclerosis.

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation.

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD­gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)­induced genes were identified from the literature and the CAD­associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identified in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ­glutamyl transferase (GGT)­5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV­neutralizing antibody (CMV­NA) titers. The C­statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction.

Association of γ-glutamyl transferase with premature coronary artery disease.

Accumulating evidence from epidemiological studies suggests that higher γ-glutamyl transferase (GGT) levels in the blood are associated with the incident of cardiovascular disease (CVD), including atherosclerosis, and have prognostic importance. However, to the best of our knowledge, the association of the GGT level with premature coronary artery disease (CAD) in an Asian Indian population has not been evaluated. In the present study, 240 (120 unaffected and 120 CAD affected) young subjects (males, ≤45 years and females, ≤50 years) were selected. The markers assayed were GGT, high-sensitivity C-reactive protein, lipids, secretory phospholipase A2, neopterin, myeloperoxidase, interleukin-6, cystatin-C, tumor necrosis factor-like weak inducer of apoptosis and lipoprotein (a). The plasma GGT levels in these subjects showed a positive correlation with quantitative variables, such as waist circumference, triglycerides, neopterin levels and cross-sectional correlation with qualitative variable smoking. The findings suggest that the subjects in the highest tertile of GGT had a 2.1-fold [odds ratio (OR), 2.104; 95% confidence interval (CI), 1.063-4.165; P=0.033] higher risk of developing premature CAD in comparison with the reference tertile. Furthermore, a 1 U/l increase of GGT (on a log scale) increased the OR by 5.2-fold (OR, 5.208; 95% CI, 1.018-24.624; P=0.048) and 7.4-fold (OR, 7.492; 95% CI, 1.221-45.979; P=0.030) on addition of associated risk factors. In conclusion, the elevated plasma GGT levels potentially indicate increased oxidative stress and the risk of developing premature CAD. Therefore, these findings could be potentially used in the risk stratification of premature CAD following further evaluation.

Insights from Chromosome-Centric Mapping of Disease-Associated Genes: Chromosome 12 Perspective.

In line with the aims of the Chromosome-based Human Proteome Project and the Biology/Disease-based Human Proteome Project, we have been studying differentially expressed transcripts and proteins in gliomas­the most prevalent primary brain tumors. Here, we present a perspective on important insights from this analysis in terms of their co-expression, co-regulation/de-regulation, and co-localization on chromosome 12 (Chr. 12). We observe the following: (1) Over-expression of genes mapping onto amplicon regions of chromosomes may be considered as a biological validation of mass spectrometry data. (2) Their co-localization further suggests common determinants of co-expression and co-regulation of these clusters. (3) Co-localization of "missing" protein genes of Chr. 12 in close proximity to functionally related genes may help in predicting their functions. (4) Further, integrating differentially expressed gene-protein sets and their ontologies with medical terms associated with clinical phenotypes in a chromosome-centric manner reveals a network of genes, diseases, and pathways­a diseasome network. Thus, chromosomal mapping of disease data sets can help uncover important regulatory and functional links that may offer new insights for biomarker development.

Novel network biomarkers profile based coronary artery disease risk stratification in Asian Indians.

BACKGROUND: Multi-marker approaches for risk prediction in coronary artery disease (CAD) have been inconsistent due to biased selection of specific know biomarkers. We have assessed the global proteome of CAD-affected and unaffected subjects, and developed a pathway network model for elucidating the mechanism and risk prediction for CAD. MATERIALS AND METHODS: A total of 252 samples (112 CAD-affected without family history and 140 true controls) were analyzed by Surface-Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS) by using CM10 cationic chips and bioinformatics tools. RESULTS: Out of 36 significant peaks in SELDI-TOF MS, nine peaks could do better discrimination of CAD subjects and controls (area under the curve (AUC) of 0.963) based on the Support Vector Machine (SVM) feature selection method. Of the nine peaks used in the model for discrimination of CAD-affected and unaffected, the m/z corresponding to 22,859 was identified as stress-related protein HSP27 and was shown to be highly associated with CAD (odds ratio of 3.47). The 36 biomarker peaks were identified and a network profile was constructed showing the functional association between different pathways in CAD. CONCLUSION: Based on our data, proteome profiling with SELDI-TOF MS and SVM feature selection methods can be used for novel network biomarker discovery and risk stratification in CAD. The functional associations of the identified novel biomarkers suggest that they play an important role in the development of disease.

Integrative bioinformatics analysis of genomic and proteomic approaches to understand the transcriptional regulatory program in coronary artery disease pathways.

Patients with cardiovascular disease show a panel of differentially regulated serum biomarkers indicative of modulation of several pathways from disease onset to progression. Few of these biomarkers have been proposed for multimarker risk prediction methods. However, the underlying mechanism of the expression changes and modulation of the pathways is not yet addressed in entirety. Our present work focuses on understanding the regulatory mechanisms at transcriptional level by identifying the core and specific transcription factors that regulate the coronary artery disease associated pathways. Using the principles of systems biology we integrated the genomics and proteomics data with computational tools. We selected biomarkers from 7 different pathways based on their association with the disease and assayed 24 biomarkers along with gene expression studies and built network modules which are highly regulated by 5 core regulators PPARG, EGR1, ETV1, KLF7 and ESRRA. These network modules in turn comprise of biomarkers from different pathways showing that the core regulatory transcription factors may work together in differential regulation of several pathways potentially leading to the disease. This kind of analysis can enhance the elucidation of mechanisms in the disease and give better strategies of developing multimarker module based risk predictions.

BioParishodhana: A novel graphical interface integrating BLAST, ClustalW, primer3 and restriction digestion tools.

UNLABELLED: Bioinformatics has emerged as an integral part of life sciences and biomedical research. The bioinformatics tools developed so far exist individually and do not cross talk leading biologists to spend more time in formatting the output from one tool as input for another tool. This leads to huge loss of time and cost. We herein have made platform which integrates the tools in a way that the output of one program can be directly used as input of another and does not need any modifications. Tools for similarity search, primer designing, and restriction enzyme digestion are required in almost all biological research; therefore we initially tried to integrate these tools. BioParisodhana platform optimizes the time spend in browsing and downloading applications and is an interactive, effective and user friendly. AVAILABILITY: The database is available for free at http://resource.ibab.ac.in/bioparishodhana.html.

Downregulation of c-Jun expression by transcription factor C/EBPalpha is critical for granulocytic lineage commitment.

The transcription factor C/EBPalpha is crucial for the differentiation of granulocytes. Conditional expression of C/EBPalpha triggers neutrophilic differentiation, and C/EBPalpha can block 12-O-tetradecanoylphorbol-13-acetate-induced monocytic differentiation of bipotential myeloid cells. In C/EBPalpha knockout mice, no mature granulocytes are present. A dramatic increase of c-Jun mRNA in C/EBPalpha knockout mouse fetal liver was observed. c-Jun, a component of the AP-1 transcription factor complex and a coactivator of the transcription factor PU.1, is important for monocytic differentiation. Here we report that C/EBPalpha downregulates c-Jun expression to drive granulocytic differentiation. An ectopic increase of C/EBPalpha expression decreases the c-Jun mRNA level, and the human c-Jun promoter activity is downregulated eightfold in the presence of C/EBPalpha. C/EBPalpha and c-Jun interact through their leucine zipper domains, and this interaction prevents c-Jun from binding to DNA. This results in downregulation of c-Jun's capacity to autoregulate its own promoter through the proximal AP-1 site. Overexpression of c-Jun prevents C/EBPalpha-induced granulocytic differentiation. Thus, we propose a model in which C/EBPalpha needs to downregulate c-Jun expression and transactivation capacity for promoting granulocytic differentiation.