Investigating the potential of Juglans regia phytoconstituents for the treatment of cervical cancer utilizing network biology and molecular docking approach.

The fourth most frequent type of cancer in women and the leading cause of mortality for females worldwide is cervical cancer. Traditionally, medicinal plants have been utilized to treat various illnesses and ailments. The molecular docking method is used in the current study to look into the phytoconstituents of Juglans regia's possible anticancer effects on cervical cancer target proteins. This work uses the microarray dataset analysis of GSE63678 from the NCBI Gene Expression Omnibus database to find differentially expressed genes. Furthermore, protein-protein interactions of differentially expressed genes were constructed using network biology techniques. The top five hub genes (IGF1, FGF2, ESR1, MYL9, and MYH11) are then determined by computing topological parameters with Cytohubba. In addition, molecular docking research was performed on Juglans regia phytocompounds that were extracted from the IMPPAT database versus hub genes that had been identified. Utilizing molecular dynamics, simulation confirmed that prioritized docked complexes with low binding energies were stable.

A Comprehensive Metagenome Study Identifies Distinct Biological Pathways in Asthma Patients: An In-Silico Approach.

Asthma is a multifactorial disease with phenotypes and several clinical and pathophysiological characteristics. Besides innate and adaptive immune responses, the gut microbiome generates Treg cells, mediating the allergic response to environmental factors and exposure to allergens. Because of the complexity of asthma, microbiome analysis and other precision medicine methods are now widely regarded as essential elements of efficient disease therapy. An in-silico pipeline enables the comparative taxonomic profiling of 16S rRNA metagenomic profiles of 20 asthmatic patients and 15 healthy controls utilizing QIIME2. Further, PICRUSt supports downstream gene enrichment and pathway analysis, inferring the enriched pathways in a diseased state. A significant abundance of the phylum Proteobacteria, Sutterella, and Megamonas is identified in asthma patients and a diminished genus Akkermansia. Nasal samples reveal a high relative abundance of Mycoplasma in the nasal samples. Further, differential functional profiling identifies the metabolic pathways related to cofactors and amino acids, secondary metabolism, and signaling pathways. These findings support that a combination of bacterial communities is involved in mediating the responses involved in chronic respiratory conditions like asthma by exerting their influence on various metabolic pathways.

Anti Mtb Medicinal Plants Database (AMMPDB): A curated database of Indian anti-tubercular medicinal plants.

The utilization of medicinal plants for their therapeutic properties has long been a key component of Indian culture. Unique medicinal characteristics can be found in the phytochemicals that are extracted from these plants. Globally, tuberculosis (TB) burden and management are challenged due to the emergence of new resistant strains of Mycobacterium tuberculosis (Mtb). This highlights the importance of new drug molecules from diverse sources as well as their innovative management options. In this context, the present study formulated an Anti Mtb medicinal plant database (AMMPDB Ver. 1.1), a manually curated database of native Indian medicinal plants that reported anti-tubercular (anti-TB) activities and their potential therapeutic phytochemicals. This is the first-ever freely accessible digital repository. The current version of the database provides users, with information regarding 118 native Indian anti-tubercular medicinal plants and their 3374 phytochemicals. The database provides the following information: Taxonomical ID, botanical description, vernacular names, conservation status, geographical distribution maps, IC-50 value, phytochemical details which include - name, Compound ID, Synonyms, location in plant part, 2D, 3D structures (as per the availability), and their medicinal uses reported in the literature. The tools section of the database is equipped with sequentially catalogued and hyperlinked open-access tools utilized for computational drug designing. A case study has been incorporated under the contributors section to validate the tools section and the phytochemicals of the database. AMMPDB Ver 1.1 will be serviceable to research in computational drug designing and discovery with effectiveness and ease. Database URL: https://www.ammpdb.com/.

Systematic analysis to identify novel disease indications and plausible potential chemical leads of glutamate ionotropic receptor NMDA type subunit 1, GRIN1.

Schizophrenia is a mental illness affecting the normal lifestyle of adults and early adolescents incurring major symptoms as jumbled speech, involvement in everyday activities eventually got reduced, patients always struggle with attention and memory, reason being both the genetic and environmental factors responsible for altered brain chemistry and structure, resulting in schizophrenia and associated orphan diseases. The network biology describes the interactions among genes/proteins encoding molecular mechanisms of biological processes, development, and diseases. Besides, all the molecular networks, protein-protein Interaction Networks have been significant in distinguishing the pathogenesis of diseases and thereby drug discovery. The present meta-analysis prioritizes novel disease indications viz. rare and orphan diseases associated with target Glutamate Ionotropic Receptor NMDA Type Subunit 1, GRIN1 using text mining knowledge-based tools. Furthermore, ZINC database was virtually screened, and binding conformation of selected compounds was performed and resulted in the identification of Narciclasine (ZINC04097652) and Alvespimycin (ZINC73138787) as potential inhibitors. Furthermore, docked complexes were subjected to MD simulation studies which suggests that the identified leads could be a better potential drug to recuperate schizophrenia.

Drug repurposing against galectin-3 using simulation-based studies.

The protein galectin, which binds to carbohydrates and is involved in a number of therapeutic processes including cell proliferation, inflammatory responses, apoptosis, etc., has been discovered as a potential therapeutic target. Galectin-3 is a stable biomarker that exhibits both increased and decreased expression in a variety of illnesses and infections, regardless of sex, age, or body mass index. The goal of the current study is to apply bioinformatics techniques to examine the possibility of cardiovascular medications to inhibit Galectin-3-related biological activities. Unsupervised clustering techniques, molecular docking, and guided molecular dynamics (MD) simulation were used to create a computational pipeline that was used to screen potential chemical compounds from a library of chemical compounds with related molecular fingerprints. Utilizing input factors such as gene expression, mode of action, and chemical descriptors, clustering enables prioritization of medicinal molecules. Twenty-four compounds were screened and repurposed against Galectin-3 utilizing molecular docking as part of the cluster-facilitated virtual screening technique. The polar interactions that Arg144, Glu184, Arg162, His158, and Asn174 have with Bufalin, Cymarin, and Ouabalin have the highest binding affinities, according to docking studies. Studies using MD simulations confirm the tested compounds' ability to inhibit Galectin-3. Galactin-3 targeted experimental and in vivo animal model-based validation studies using Bufalin, Cymarin, and Ouabalin are also necessary.Communicated by Ramaswamy H. Sarma.

Oxidative Products of Curcumin Rather Than Curcumin Bind to Helicobacter Pylori Virulence Factor VacA and Are Required to Inhibit Its Vacuolation Activity.

Curcumin is a hydrophobic polyphenol derived from turmeric with potent anti-oxidant, anti-microbial, anti-inflammatory and anti-carcinogenic effects. Curcumin is degraded into various derivatives under in vitro and in vivo conditions, and it appears that its degradation may be responsible for the pharmacological effects of curcumin. The primary risk factor for the cause of gastric cancer is Helicobacter pylori (H. pylori). A virulence factor vacuolating cytotoxic A (VacA) is secreted by H. pylori as a 88 kDa monomer (p88), which can be fragmented into a 33 kDa N-terminal domain (p33) and a 55 kDa C-terminal domain (p55). Recently it has been reported that curcumin oxidation is required to inhibit the activity of another major H.pylori toxin CagA. We performed molecular docking of curcumin and its oxidative derivatives with p33 and p55 domains of VacA. Further, we have examined the effect of the oxidation of curcumin on the vacuolation activity of VacA protein. We observed the binding of curcumin to the p55 domain of VacA at five different sites with moderate binding affinities. Curcumin did not bind to p33 domain of VacA. Remarkably, cyclobutyl cyclopentadione and dihydroxy cyclopentadione, which are oxidized products of curcumin, showed a higher binding affinity with VacA protein at all sites except one as compared to parent curcumin itself. However, cyclobutyl cyclopentadione showed a significant binding affinity for the active site 5 of the p55 protein. Active site five (312-422) of p55 domain of VacA plays a crucial role in VacA-mediated vacuole formation. Invitro experiments showed that curcumin inhibited the vacuolation activity of H. pylori in human gastric cell line AGS cells whereas acetyl and diacetyl curcumin, which cannot be oxidized, failed to inhibit the vacuolation in AGS cells after H. pylori infection. Here our data showed that oxidation is essential for the activity of curcumin in inhibiting the vacuolation activity of H. pylori. Synthesis of these oxidized curcumin derivatives could potentially provide new therapeutic drug molecules for inhibiting H. pylori-mediated pathogenesis.

Network medicine in ovarian cancer: topological properties to drug discovery.

Network medicine provides network theoretical tools, methods and properties to study underlying laws governing human interactome to identify disease states and disease complexity leading to drug discovery. Within this framework, we investigated the topological properties of ovarian cancer network (OCN) and the roles of hubs to understand OCN organization to address disease states and complexity. The OCN constructed from the experimentally verified genes exhibits fractal nature in the topological properties with deeply rooted functional communities indicating self-organizing behavior. The network properties at all levels of organization obey one parameter scaling law which lacks centrality lethality rule. We showed that $\langle k\rangle $ can be taken as a scaling parameter, where, power law exponent can be estimated from the ratio of network diameters. The betweenness centrality $C_B$ shows two distinct behaviors one shown by high degree hubs and the other by segregated low degree nodes. The $C_B$ power law exponent is found to connect the exponents of distributions of high and low degree nodes. OCN showed the absence of rich-club formation which leads to the missing of a number of attractors in the network causing formation of weakly tied diverse functional modules to keep optimal network efficiency. In OCN, provincial and connector hubs, which includes identified key regulators, take major responsibility to keep the OCN integrity and organization. Further, most of the key regulators are found to be over expressed and positively correlated with immune infiltrates. Finally, few potential drugs are identified related to the key regulators.

Proteomic Characterization and Target Identification Against Streptococcus mutans Under Bacitracin Stress Conditions Using LC-MS and Subtractive Proteomics.

The aim of the present study, is to identify potential targets against the highly pathogenic bacteria Streptococcus mutans that causes dental caries as well as the deadly infection of endocarditis. The powerful and highly sensitive technique of liquid chromatography-mass spectrometry (LC-MS/MS) identified 321 proteins of S. mutans when grown under stressful conditions induced by the antibiotic bacitracin. These 321 proteins were subjected to the insilico method of subtractive proteomics to screen out potential targets by utilizing different analyses like CD-HIT, non-homologous sequence screening, KEGG pathway, essentiality screening, gut-flora non-homology, and codon usage analysis. A database of essential proteins was employed to find sequence homology of non-paralogous proteins to determine proteins which are essential for bacterial survival. Cellular localization analysis of the selected proteins was done to localize them inside the cell along with physico-chemical characterization and druggability analysis. Using computational tools, 22 proteins out of 321, that are functionally distinguishable from their human counterparts and passed the criterion of a potential therapeutic candidate were identified. The selected proteins comprise central energy metabolic proteins, virulence factors, proteins of the sortase family, and essentiality factors. The presented analyses identified proteins of the sortase family, which appear as key therapeutic targets against caries infection. These proteins regulate a number of virulence factors, thus can be simultaneously inhibited to obstruct multiple virulence pathways.

Multiple epitope-based vaccine prediction against SARS-CoV-2 spike glycoprotein.

The global emergence of novel coronavirus disease and its rapid global expansion over a short span of time require effective countermeasures to combat it. Development of a specific vaccine can induce an optimal antibody response, thus providing immunity against it. Our study proposes a detailed and comprehensive immunoinformatic approach that can be applied to the currently available coronavirus protein data in the online server for vaccine candidate development. We have identified the receptor binding domain (RBD) of structural spike protein (S1) as a potential target for immunity against COVID- 19 infection. Epitope prediction illustrated cytotoxic T-cell epitopes, helper T-cell epitopes, and B-cell epitopes associated with the target protein. These were joined through specific linkers along with adjuvant beta-defensin located at the N-terminal to create a multi epitope subunit vaccine (MESV). The specificity in the binding of the devised vaccine candidate to the TLR-3 immune cell receptor was evaluated via molecular docking interaction studies. Good docking score combined with robust interactions in the binding cavity certified the stringency of the engineered vaccine. Molecular dynamics simulation data showed minimal variation of the root-mean square deviations (RMSDs) and root-mean-square fluctuations (RMSFs) which confirmed the interaction stability. These results obtained from various in-silico experiments indicate the potency of this vaccine candidate as a probable therapeutic agent against COVID-19. Vaccination strategies targeting conserved epitope-based immune response would be beneficial in providing cross protection across beta-coronaviruses, and such vaccines would be resistant to the ever-evolving viruses.Communicated by Ramaswamy H. Sarma.

Antineoplastic action of sulforaphane on HeLa cells by modulation of signaling pathways and epigenetic pathways.

BACKGROUND: Epigenetic modifications alter signaling and molecular pathways; moreover, they are an important therapeutic target. This study examined the effect of sulforaphane on molecular targets in HeLa cells. METHODS: Quantitative PCR of various molecular targets was performed. Activity of epigenetic enzymes was measured by ELISA and molecular docking analysis was conducted. Promoter methylation of some tumor suppressor genes was quantified using PCR based methylation array. In-silico protein-protein interaction network analysis was performed to understand the effect of transcriptional changes. RESULTS: Quantitative PCR demonstrated the transcriptional modulation of genes involved in proliferation, metastasis, inflammation, signal transduction pathways and chromatin modifiers. Sulforaphane reduced the enzymatic activity of DNA methyl transferases, histone deacetylases and histone methyltransferases. Molecular docking results suggest that sulforaphane competitively inhibited several DNA methyl transferases and histone deacetylases. Promoter 5'CpG methylation levels of selected tumor suppressor genes was found to be reduced which correlated with their transcriptional increase as well modulation of epigenetic enzymes. Further, protein-protein interaction network analysis discerned the participation of genes towards cancer pathways. Functional enrichment and pathway-based analysis represented the modulation of epigenetic and signaling pathways on sulforaphane treatment. CONCLUSIONS: The modulation in transcriptional status of epigenetic regulators, genes involved in tumorigenesis resulting in tumor suppressor genes demethylation and re-expression underscores the mechanism behind the anticancer effect of sulforaphane on HeLa cells.

Prioritization and characterization of validated biofilm blockers targeting glucosyltransferase C of Streptococcus mutans.

To date, several Glucosyltransferase C (GtfC) inhibitors have been identified and experimentally validated. All these inhibitors have been validated at different experimental conditions like degree of purity, animal models, kinetic conditions, experimental environment etc.; and most of these inhibitors (ligands) proved to be quite effective in their respective validation environment. However, due to varied experimental validation conditions, and absence of molecular interaction data, there is no way to prioritize these validated ligands for their inhibition potential against GtfC. The present study is a novel attempt of comparative evaluation of the interaction of the validated ligands on a single platform and under similar conditions with a dual objective, i.e. ligand prioritization for their respective inhibitory potential and elucidation of the involved unknown molecular interactions. Carbohydrate derivatives (6-Deoxy sucrose and Trichloro-galactosucrose) were identified as the most promising GtfC inhibitors. In addition, Asp588, Trp517, and Asn481 amino acid residues of the domain A1 proved vital for the inhibitory effect. The study highlights the importance of the comparative analysis of the validated ligands in order to identify the most promising leads for drug discovery against dental caries.

Inhibitory mechanism of an antifungal drug, caspofungin against amyloid ß peptide aggregation: Repurposing via neuroinformatics and an experimental approach.

The multifactorial neurological condition called Alzheimer's disease (AD) primarily affects elderly individuals. Despite the calamitous consequences of AD, curative strategies for a regimen to apply remain inadequate as several factors contribute to AD etiology. Drug repurposing is an advance strategy prior to drug discovery as various effective drugs perform through alteration of multiple targets, and the present "poly-pharmacology" can be a curative approach to complex disorders. AD's multifactorial behavior actively encourages the hypothesis for a drug design approach focused on drug repurposing. In this study, we discovered that an antifungal drug, Caspofungin (CAS) is a potent Aß aggregation inhibitor that displays significantly reduced toxicity associated with AD. Drug reprofiling and REMD simulations demonstrated that CAS interacts with the ß-sheet section, known as Aß amyloid fibrils hotspot. CAS leads to destabilization of ß-sheet and, conclusively, in its devaluation. Later, in vitro experiments were acquired in which the fibrillar volume was reduced for CAS-treated Aß peptide. For the first time ever, this study has determined an antifungal agent as the Aß amyloid aggregation's potent inhibitor. Several efficient sequence-reliant potent inhibitors can be developed in future against the amyloid aggregation for different amyloid peptide by the processing and conformational optimization of CAS.

Identification of new BACE1 inhibitors for treating Alzheimer's disease.

Alzheimer's disease (AD) is a type of brain disorder, wherein a person experiences gradual memory loss, state of confusion, hallucination, agitation, and personality change. AD is marked by the presence of extracellular amyloid plaques and intracellular neurofibrillary tangles (NFTs) and synaptic losses. Increased cases of AD in recent times created a dire need to discover or identify chemical compounds that can cease the development of AD. This study focuses on finding potential drug molecule(s) active against ß-secretase, also known as ß-site amyloid precursor protein cleaving enzyme 1 (BACE1). Clustering analysis followed by phylogenetic studies on microarray datasets retrieved from GEO browser showed that BACE1 gene has genetic relatedness with the RCAN1 gene. A ligand library comprising 60 natural compounds retrieved from literature and 25 synthetic compounds collected from DrugBank were screened. Further, 350 analogues of potential parent compounds were added to the library for the docking purposes. Molecular docking studies identified 11-oxotigogenin as the best ligand molecule. The compound showed the binding affinity of - 11.1 Kcal/mole and forms three hydrogen bonds with Trp124, Ile174, and Arg176. The protein-ligand complex was subjected to 25 ns molecular dynamics simulation and the potential energy of the complex was found to be - 1.24579e+06 Kcal/mole. In this study, 11-oxotigogenin has shown promising results against BACE1, which is a leading cause of AD, hence warrants for in vitro and in vivo validation of the same. In addition, in silico identification of 11-oxotigogenin as a potential anti-AD compound paves the way for designing of chemical scaffolds to discover more potent BACE1 inhibitors.Graphical abstract.

The polyphenolic phytoalexin polydatin inhibits amyloid aggregation of recombinant human prion protein.

Prion diseases involve misfolded and highly infectious aggregates of prion protein (PrPSc) which forms amyloid plaques leading to fatal neurodegeneration. The absence of clinically proven therapeutics makes the discovery of effective remedial interventions a prime concern. Herein, we report novel prion intervention by the polyphenolic phytoalexin, polydatin which binds with moderate affinity to the recombinant protease resistant core of human prion protein, encompassing the sequence 90-231 (rPrPres) and inhibits its conversion into the highly neurotoxic forms. An extensive evaluation using biophysical techniques revealed that polydatin incubated rPrPres samples generate off-pathway oligomers having reduced cross-ß sheet signature, and relatively smaller in size than the native rPrPres oligomers. The detailed structural analysis using molecular dynamics simulations elucidated the induction of antagonistic mobilities in the ß2-α2 loop, α3 helix and the N-terminal amyloidogenic region of prions. This study puts forward novel prion fibrillogenesis inhibitory potential of polydatin, specifically by stabilizing the N-terminal amyloidogenic region. Collectively our results affirm the importance of polydatin in crippling the prion pathogenesis and may serve as a structural scaffold for designing novel therapeutic agents targeting amyloidogenic transition in prions.

Potency of inhibitors depends upon the accessibility of their aromatic rings within the hydrophobic specificity pocket: a novel avenue for future aldose reductase inhibitor design.

Communicated by Ramaswamy H. Sarma.

Unravelling the interaction of glipizide with human serum albumin using various spectroscopic techniques and molecular dynamics studies.

Glipizide is known to stimulate insulin secretion by ß-cells of the pancreas. It is a second-generation sulfonylurea drug used in the management of type 2 diabetes. The shorter biological half-life makes it a suitable candidate to be designed as a controlled release formulation. Human serum albumin (HSA), a major plasma protein plays a crucial role in the transportation of drugs, hormones, fatty acids, and many other molecules and determines their physiological fate and biodistribution. In this study, the interaction of glipizide with HSA was investigated under physiological conditions using multi-spectroscopic techniques corroborated with molecular docking and dynamics approach. It was found that glipizide integrates to HSA with a binding constant in the order of 105 M-1. The mode of fluorescence quenching by glipizide is static in nature with one binding site. Glipizide preferentially interacts with sub-domain IIA of HSA and their complexion is thermodynamically favorable. This interaction results in the loss of α-helical content of HSA. The energy transfer efficiency from HSA to glipizide was found to be 26.72%. In silico molecular docking and simulation studies ratified in vitro findings and revealed that hydrogen bonds and hydrophobic interactions are accountable for glipizide-HSA complex formation.Communicated by Ramaswamy H. Sarma.

Identifying novel inhibitor of quorum sensing transcriptional regulator (SdiA) of Klebsiella pneumoniae through modelling, docking and molecular dynamics simulation.

In this study, attempts have been made to identify novel inhibitor(s) of SdiA (a homolog of LuxR transcription regulator) of Klebseilla pneumoniae using various computational techniques. 4LFU was used as a template to model the structure of SdiA. ProCheck, Verify3D, Ramachandran plot scores and ProSA-Web confirmed the good quality of the model as the root mean square deviation (RMSD) between SdiA model, and 4LFU template was estimated to be 0.21 Å. The secondary structural contents of SdiA model were predicted using PDBsum. The only binding site of SdiA was identified (area = 523.083 Å2 and volume = 351.044 Å3) using CASTp. Molecular docking at three different levels [high throughput virtual screening, standard-precision (SP) and extra-precision (XP) dockings] with increasingly stringent conditions was performed using Glide on Selleck's express pick library (L3600). A total of 61 ligands were found to bind with high affinities to the active site of SdiA. Further, the effect of solvent on protein-ligand interaction was evaluated by performing molecular mechanics-general born surface area (Prime/MM-GBSA). On the basis of Prime/MM-GBSA score, molecular dynamics simulation (50 ns) was performed on the ligand (WAY-390139-A) showing lowest binding energy to confirm the stability of protein-ligand complex. Docking energy and the corresponding binding affinity of WAY-390139-A towards SdiA were estimated to be -13.005 kcal mol-1 and 3.46 × 109 M-1, respectively. Our results confirm that WAY-390139-A binds at the autoinducer binding site of SdiA with high affinity and stability and can be further exploited as potential drug against K. pneumoniae after experimental validation.Communicated by Ramaswamy H. Sarma.

Reductive metabolites of curcumin and their therapeutic effects.

Curcumin, a secondary metabolite from the turmeric plant is one of the most promising natural products, which has been studied extensively for decades. It has demonstrated several pharmacological activities in vitro and in vivo. Various studies have indicated that the pharmacological activity of curcumin is contributed by its metabolites. The aim of this review is to present an overview of metabolic products of curcumin produced upon its reduction like di, tetra, hexa and octa-hydrocurcumin. In addition, this paper has systematically analyzed the current information regarding medicinal use of reduced metabolites of curcumin and identified the limitations which have hindered its widespread usage in the medical world. Several diverse therapeutic effects have shown to be exhibited by reduced metabolites of curcumin such as antioxidant, anti-cancerous, anti-inflammatory and immunoregulatory activities. The potential underlying molecular mechanisms of the biological activities of reduced metabolites of curcumin have also been highlighted, which may provide insight into the principle of effectiveness of curcumin.

Epigallocatechin gallate inhibits HeLa cells by modulation of epigenetics and signaling pathways.

This study examines the effect of epigallocatechin gallate (EGCG) on signaling pathways, epigenetic modulators and tumour suppressor genes in cervical cancer cells, HeLa. qRT-PCR, ELISA-based enzymatic assays and in silico studies were used to catalogue the modulation of these genes by EGCG treatment. qRT-PCR showed transcriptional modulation of several epigenetic modifiers including DNA methyltransferases and histone modifiers (DNMT1, DNMT3B, DNMT3A, AURKA, AURKC, AURKB, KDM4A, KDM5C, PRMT7, PRMT6, UBE2B, HDAC5, HDAC6, HDAC7 and HDAC11. Furthermore, ELISA-based assays showed that EGCG lowered the activity of DNA methyltransferases, histone deacetylases and histone methyltransferases (H3K9). Molecular docking results suggests that EGCG may competitively inhibit some epigenetic enzymes (DNMT1, DNMT3A, HDAC2, HDAC3, HDAC4, HDAC7 and EZH2). A functional outcome of these epigenetic alterations could be inferred from the reversal of promoter hypermethylation of tumour suppressor genes by quantitative methylation array and transcriptional re-expression of tumour suppressor genes including TP73, PTEN, SOCS1, CDH1, RARß, and DAPK1 by qRT-PCR. Downregulation of key signaling moieties of PI3K, Wnt and MAPK pathways, cell cycle regulators, metastasis regulators and pro-inflammatory moieties including TERT, CCNB1, CCNB2, MMP2, MMP7. PIK3C2B, PIK3CA, MAPK8 and IL6 was also observed. In silico protein-protein interaction network analysis followed by KEGG analysis discerned the active participation of gene sets towards cancer pathways. This study comprehensively explains EGCG's anti-cancer mechanism via the synchronized transcriptional alteration of several molecular targets across different signaling pathways and reversal of tumour suppressor gene silencing through modulation of epigenetic enzymes.

Elucidating potential molecular signatures through host-microbe interactions for reactive arthritis and inflammatory bowel disease using combinatorial approach.

Reactive Arthritis (ReA), a rare seronegative inflammatory arthritis, lacks exquisite classification under rheumatic autoimmunity. ReA is solely established using differential clinical diagnosis of the patient cohorts, where pathogenic triggers linked to enteric and urogenital microorganisms e.g. Salmonella, Shigella, Yersinia, Campylobacter, Chlamydia have been reported. Inflammatory Bowel Disease (IBD), an idiopathic enteric disorder co-evolved and attuned to present gut microbiome dysbiosis, can be correlated to the genesis of enteropathic arthropathies like ReA. Gut microbes symbolically modulate immune system homeostasis and are elementary for varied disease patterns in autoimmune disorders. The gut-microbiota axis structured on the core host-microbe interactions execute an imperative role in discerning the etiopathogenesis of ReA and IBD. This study predicts the molecular signatures for ReA with co-evolved IBD through the enveloped host-microbe interactions and microbe-microbe 'interspecies communication', using synonymous gene expression data for selective microbes. We have utilized a combinatorial approach that have concomitant in-silico work-pipeline and experimental validation to corroborate the findings. In-silico analysis involving text mining, metabolic network reconstruction, simulation, filtering, host-microbe interaction, docking and molecular mimicry studies results in robust drug target/s and biomarker/s for co-evolved IBD and ReA. Cross validation of the target/s or biomarker/s was done by targeted gene expression analysis following a non-probabilistic convenience sampling. Studies were performed to substantiate the host-microbe disease network consisting of protein-marker-symptom/disease-pathway-drug associations resulting in possible identification of vital drug targets, biomarkers, pathways and inhibitors for IBD and ReA.Our study identified Na(+)/H(+) anti-porter (NHAA) and Kynureninase (KYNU) to be robust early and essential host-microbe interacting targets for IBD co-evolved ReA. Other vital host-microbe interacting genes, proteins, pathways and drugs include Adenosine Deaminase (ADA), Superoxide Dismutase 2 (SOD2), Catalase (CAT), Angiotensin I Converting Enzyme (ACE), carbon metabolism (folate biosynthesis) and methotrexate. These can serve as potential prognostic/theranostic biomarkers and signatures that can be extrapolated to stratify ReA and related autoimmunity patient cohorts for further pilot studies.