Network pharmacology and bioinformatics approach reveals the therapeutic mechanism of action of curcumin in Alzheimer disease.

Curcumin is a natural anti-inflammatory and antioxidant substance which plays a major role in reducing the amyloid plaques formation, which is the major cause of Alzheimer's disease (AD). Consequently, a methodical approach was used to select the potential protein targets of curcumin in AD through network pharmacology. In this study, through integrative methods, AD targets of curcumin through SwissTargetPrediction database, STITCH database, BindingDB, PharmMapper, Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM) database were predicted followed by gene enrichment analysis, network construction, network topology, and docking studies. Gene ontology analysis facilitated identification of a list of possible AD targets of curcumin (74 targets genes). The correlation of the obtained targets with AD was analysed by using gene ontology (GO) pathway enrichment analyses and Kyoto Encyclopaedia of Genes and Genomes (KEGG). We have incorporated the applied network pharmacological approach to identify key genes. Furthermore, we have performed molecular docking for analysing the mechanism of curcumin. In order to validate the temporospatial expression of key genes in human central nervous system (CNS), we searched the Human Brain Transcriptome (HBT) dataset. We identified top five key genes namely, PPARγ, MAPK1, STAT3, KDR and APP. Further validated the expression profiling of these key genes in publicly available brain data expression profile databases. In context to a valuable addition in the treatment of AD, this study is concluded with novel insights into the therapeutic mechanisms of curcumin, will ease the treatment of AD with the clinical application of curcumin.

Potential Efficacy of ß-Amyrin Targeting Mycobacterial Universal Stress Protein by In Vitro and In Silico Approach.

The emergence of drug resistance and the limited number of approved antitubercular drugs prompted identification and development of new antitubercular compounds to cure Tuberculosis (TB). In this work, an attempt was made to identify potential natural compounds that target mycobacterial proteins. Three plant extracts (A. aspera, C. gigantea and C. procera) were investigated. The ethyl acetate fraction of the aerial part of A. aspera and the flower ash of C. gigantea were found to be effective against M. tuberculosis H37Rv. Furthermore, the GC-MS analysis of the plant fractions confirmed the presence of active compounds in the extracts. The Mycobacterium target proteins, i.e., available PDB dataset proteins and proteins classified in virulence, detoxification, and adaptation, were investigated. A total of ten target proteins were shortlisted for further study, identified as follows: BpoC, RipA, MazF4, RipD, TB15.3, VapC15, VapC20, VapC21, TB31.7, and MazF9. Molecular docking studies showed that ß-amyrin interacted with most of these proteins and its highest binding affinity was observed with Mycobacterium Rv1636 (TB15.3) protein. The stability of the protein-ligand complex was assessed by molecular dynamic simulation, which confirmed that ß-amyrin most firmly interacted with Rv1636 protein. Rv1636 is a universal stress protein, which regulates Mycobacterium growth in different stress conditions and, thus, targeting Rv1636 makes M. tuberculosis vulnerable to host-derived stress conditions.

Glossary of phytoconstituents: Can these be repurposed against SARS CoV-2? A quick in silico screening of various phytoconstituents from plant Glycyrrhiza glabra with SARS CoV-2 main protease.

World is familiar with the viral pathogen Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2). The principle working enzymes of SARS CoV-2 have been identified as main proteases 3Cl pro which act as main regulators for SARS infection. The need for therapy is required immediately pertaining to the vulnerable conditions. Protein-ligand studies are imperative for understanding the functioning of biological interactions as they are crucial in providing a hypothetical origin for the design and unearthing of novel drug targets. Phytoconstituents from Glycyrrhiza glabra, earlier reported to be anticancerous in nature were used as repurposed drugs against SARS CoV-2 main protease 3Clpro. We analyzed the molecular interactions of protein-phytocompounds, by AutoDock Vina 4.2 tools. The best interactions of each algorithm were subjected to molecular dynamic (MD) simulations to have an insight of the molecular dynamic mechanisms involved. Selected phytoconstituents gave a good score for binding affinity with the main protease 6LU7 of SARS CoV-2 as compared to the antiviral drugs already being used in the disease therapy. DehydroglyasperinC(-8.7,-8.1,-6.7,-7.1)kcal/mol, Licochalcone D(-8.4,-8.2,-7.1,-7.9) kcal/mol, Liquiritin(-8.6,-9.0,-7.2,-7.8) kcal/mol have showed energy interactions with 3Clpro better than many FDA approved repurposed drugs; Remdesvir, Favipiravir, and Hydroxychloroquine. MD Simulation also corelates our findings for molecular docking studies.