Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein–Protein Interaction Network and Gene–Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger’s GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through “http://www.vitiligoinfores.com/”.
The bioinformatics analysis revealed that more than 400,000 DNA sequences within the human genome have the potential of forming G-quadruplex structures. Specifically, G-quadruplexes have been proved to be involved in the regulation of replication, DNA damage repair, transcription and translation of cancer-related genes and hence a therapeutic target. Targeting G4 with small molecules may regulate its expression. Chemical molecules generally shows more cellular toxicity while natural small molecules are more bioavailable and hence shows high biological activity together with low toxicity. In the present study, we have screened the binding potential of quercetin with parallel, anti-parallel and mixed conformations of telomeric G-quadruplexes, cancer protoncogenes and RNA G-quadruplex using molecular docking approach. Our results suggest that the quercetin mainly binds with grooves of all selected G-quadruplxes and its planer aromatic rings stabilizes the structure by π-π stacking. The binding energies were in a range of − 40.24 to − 17.11 kcal/ mol, − 35.73 to − 18.09 kcal/mol, − 32.68 to − 22.47 kcal/mol for telomeric parallel, anti-parallel and mixed G-quadruplexes respectively. Further, binding energies of quercetin with selected cancer proto-oncogenes are in a range of − 38.67 to − 12.95 kcal/mol and − 14.8 and − 14.6 kcal/mol for selected RNA G-quadruplex. Hence, this study highlights the comparative differences in binding energies of quercetin even with a group of single conformation of G-quadruplex and helpful to evaluate the binding potential of quercetin to inhibit the activity of telomerases and down-regulate the expression of oncogenes and to be used as a potential anti-cancer agent.
Vitiligo is a disease of mysterious origins in the context of its occurrence and pathogenesis. The autoinflammatory theory is perhaps the most widely accepted theory that discusses the occurrence of Vitiligo. The theory elaborates the clinical association of vitiligo with autoimmune disorders such as Psoriasis, Multiple Sclerosis and Rheumatoid Arthritis and Diabetes. In the present work, we discuss the comprehensive set of differentially co-expressed genes involved in the crosstalk events between Vitiligo and associated autoimmune disorders (Psoriasis, Multiple Sclerosis and Rheumatoid Arthritis). We progress our previous tool, Vitiligo Information Resource (VIRdb), and incorporate into it a compendium of Vitiligo-related multi-omics datasets and present it as VIRdb 2.0. It is available as a web-resource consisting of statistically sound and manually curated information. VIRdb 2.0 is an integrative database as its datasets are connected to KEGG, STRING, GeneCards, SwissProt, NPASS. Through the present study, we communicate the major updates and expansions in the VIRdb and deliver the new version as VIRdb 2.0. VIRdb 2.0 offers the maximum user interactivity along with ease of navigation. We envision that VIRdb 2.0 will be pertinent for the researchers and clinicians engaged in drug development for vitiligo.
Cytosolic functions of Long non-coding RNAs including mRNA translation masking and sponging are major regulators of biological pathways. Formation of T cell-bounded hypoxic granuloma is a host immune defense for containing infected Mtb-macrophages. Our study exploits the mechanistic pathway of Mtb-induced HIF1A silencing by the antisense lncRNA-HIF1A-AS2 in T
cells. Computational analysis of in-vitro T-cell stimulation assays in progressors(n=119) versus latent(n=221) tuberculosis patients revealed the role of lncRNA mediated disruption of hypoxia adaptation pathways in progressors.We found 291 upregulated and 227 downregulated lncRNAs that were correlated at mRNA level with HIF1A and HILPDA which are major players in hypoxia response. We also report novel lncRNA-AC010655 (AC010655.4 and AC010655.2) in cis with HILPDA, both of which contain binding sites for the BARX2 transcription factor, thus indicating a mechanistic role. Detailed comparison of infection with antigenic stimulation showed a non-random enrichment of lncRNAs in the cytoplasmic fraction of the cell in progressors. The lack of this pattern in non-progressors indicates the hijacking of the lncRNA dynamics by Mtb. The in-vitro manifestation of this response in the absence of granuloma indicates pre-programmed host-pathogen interaction between T-cells and Mtb regulated through lncRNAs, thus tipping this balance towards progression or containment of Mtb. Finally, we trained multiple machine learning classifiers for reliable prediction of latent to the active progression of patients, yielding a model to guide aggressive treatment.
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