Network pharmacology of Withania somnifera against stress associated neurodegenerative diseases

Transcriptome analysis reveals the anti-Parkinson's activity of Mangiferin in zebrafish

As the global population ages, the incidence of Parkinson's Disease (PD) continues to rise, imposing significant social and economic burdens. Mangiferin (MGF), a polyphenolic, bioactive compound has been shown to play a role in the prevention and treatment of PD. This study investigates the neuroprotective effects of MGF in an MPTP-induced zebrafish model of PD through transcriptome analysis. Initially, optimal concentrations for modeling were determined using various MPTP and MGF combinations. The zebrafish were then divided into control, MPTP-treated, and MGF co-treated groups. Subsequent evaluations included hatching rates, mortality rates, growth and development conditions, spontaneous motor abilities, as well as measurements of enzymatic activities of SOD, CAT, and levels of GSH. Ultimately, the therapeutic efficacy of MGF on the PD model in zebrafish was assessed through transcriptome sequencing. The results demonstrated that MPTP treatment induced PD-associated symptoms in zebrafish, while MGF treatment significantly improved the motor abilities and survival rates of the PD model zebrafish, effectively reducing oxidative stress and ameliorating PD symptoms. Transcriptome sequencing further revealed that MGF may mitigate mitochondrial-related oxidative stress in PD zebrafish by modulating the expression of critical genes including lrrk2, vps35, atp13a, dnajc6, and uchl1. Differential gene expression analysis indicated that these genes are primarily involved in vital signaling pathways, such as neuroactive ligand-receptor interaction, and the calcium signaling pathway. In summary, our study provides robust scientific evidence supporting MGF as a potential therapeutic candidate for PD by preserving mitochondrial homeostasis and elucidating its mechanisms of action.

Network pharmacology and molecular modelling study of Enhydra fluctuans for the prediction of the molecular mechanisms involved in the amelioration of nephrolithiasis

In view of the ethno medicinal use of Enhydra fluctuans for the treatment of kidney stones; the present study aimed to elucidate the molecular mechanisms involved in the amelioration of nephrolithiasis through a network pharmacology approach. The phytoconstituents were queried in DIGEP-Pred to identify the regulated proteins. The modulated proteins were then enriched in the STRING to predict the protein-protein interactions and the probably regulated pathways were traced in the Kyoto Encyclopedia of Genes and Genomes. Further, the network was constructed using Cytoscape ver 3.5.1. Results showed that β-carotene was found to be regulating maximum targets i.e. 26. In addition, 63 proteins were triggered by the components in which the vitamin D receptor was targeted by the maximum phytoconstituents i.e. 16. The enrichment analysis identified the regulation of 67 pathways in which fluid shear stress and atherosclerosis-associated pathways (KEGG entry hsa05418) regulated ten genes. Further, protein kinase C-α was traced in 23 different pathways. In addition, the majority of the regulated genes were identified from the extracellular space via the modulation of 43 genes. Also, nuclear receptor activity had the maximum molecular function via the regulation of 7 genes. Likewise, the response to organic substance was predicted to trigger the top genes i.e. 43. In contrast, Stigmasterol, Baicalein-7-o-glucoside, and Kauran-16-ol were found to have a high affinity to bind with the VDR receptor confirmed by the molecular modelling and the dynamics. Hence, the study elucidated the probable molecular mechanisms of E. fluctuans in managing nephrolithiasis and identified the lead molecules, their targets, and possible pathways.Communicated by Ramaswamy H. Sarma.

The Abundant Phytocannabinoids in Rheumatoid Arthritis: Therapeutic Targets and Molecular Processes Identified Using Integrated Bioinformatics and Network Pharmacology

The endocannabinoid system consists of several phytocannabinoids, cannabinoid receptors, and enzymes that aid in numerous steps necessary to manifest any pharmacological activity. It is well known that the endocannabinoid system inhibits the pathogenesis of the inflammatory and autoimmune disease rheumatoid arthritis (RA). To the best of our knowledge, no research has been done that explains the network-pharmacology-based anti-rheumatic processes by focusing on the endocannabinoid system. Therefore, the purpose of this study is to further our understanding of the signaling pathways, associated proteins, and genes underlying RA based on the abundant natural endocannabinoids. The knowledge on how the phytocannabinoids in Cannabis sativa affect the endocannabinoid system was gathered from the literature. SwissTarget prediction and BindingDB databases were used to anticipate the targets for the phytocannabinoids. The genes related to RA were retrieved from the DisGeNET and GeneCards databases. Protein–protein interactions (high confidence > 0.7) were carried out with the aid of the string web server and displayed using Cytoscape. The Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis was used to perform enrichment analyses on the endocannabinoid–RA common targets. ShinyGO 0.76 was used to predict the biological processes listed in the Gene Ontology (GO) classification system. The binding affinity between the ligand and the receptors was precisely understood using molecular docking, induced-fit docking, and a molecular dynamics simulation. The network pharmacology analyses predicted that processes like response to oxygen-containing compounds and peptodyl-amino acid modification are related to the potential mechanisms of treatment for RA. These biological actions are coordinated by cancer, neuroactive ligand–receptor interaction, lipids and atherosclerosis, the calcium signaling pathway, and the Rap1 signaling pathway. According to the results of molecular docking, in the context of RA, phytocannabinoids may bind to important target proteins such PIK3CA, AKT1, MAPK9, PRKCD, BRAF, IGF1R, and NOS3. This entire study predicted the phytocannabinoids’ systemic biological characteristics. Future experimental research is needed, however, to confirm the results so far.

Identification of Potential Leishmania N-Myristoyltransferase Inhibitors from Withania somnifera (L.) Dunal: A Molecular Docking and Molecular Dynamics Investigation

Leishmaniasis is a group of infectious diseases caused by Leishmania protozoa. The ineffectiveness, high toxicity, and/or parasite resistance of the currently available antileishmanial drugs has created an urgent need for safe and effective leishmaniasis treatment. Currently, the molecular-docking technique is used to predict the proper conformations of small-molecule ligands and the strength of the contact between a protein and a ligand, and the majority of research for the development of new drugs is centered on this type of prediction. Leishmania N-myristoyltransferase (NMT) has been shown to be a reliable therapeutic target for investigating new anti-leishmanial molecules through this kind of virtual screening. Natural products provide an incredible source of affordable chemical scaffolds that serve in the development of effective drugs. Withania somnifera leaves, roots, and fruits have been shown to contain withanolide and other phytomolecules that are efficient anti-protozoal agents against Malaria, Trypanosoma, and Leishmania spp. Through a review of previously reported compounds from W. somnifera-afforded 35 alkaloid, phenolic, and steroid compounds and 132 withanolides/derivatives, typical of the Withania genus. These compounds were subjected to molecular docking screening and molecular dynamics against L. major NMT. Calycopteretin-3-rutinoside and withanoside IX showed the highest affinity and binding stability to L. major NMT, implying that these compounds could be used as antileishmanial drugs and/or as a scaffold for the design of related parasite NMT inhibitors with markedly enhanced binding affinity.

Integration of System Biology Tools to Investigate Huperzine A as an Anti-Alzheimer Agent

Aim: The present study aimed to investigate huperzine A as an anti-Alzheimer agent based on the principle that a single compound can regulate multiple proteins and associated pathways, using system biology tools. Methodology: The simplified molecular-input line-entry system of huperzine A was retrieved from the PubChem database, and its targets were predicted using SwissTargetPrediction. These targets were matched with the proteins deposited in DisGeNET for Alzheimer disease and enriched in STRING to identify the probably regulated pathways, cellular components, biological processes, and molecular function. Furthermore, huperzine A was docked against acetylcholinesterase using AutoDock Vina, and simulations were performed with the Gromacs package to take into account the dynamics of the system and its effect on the stability and function of the ligands. Results: A total of 100 targets were predicted to be targeted by huperzine A, of which 42 were regulated at a minimum probability of 0.05. Similarly, 101 Kyoto Encyclopedia of Genes and Genomes pathways were triggered, in which neuroactive ligand-receptor interactions scored the least false discovery rate. Also, huperzine A was predicted to modulate 54 cellular components, 120 molecular functions, and 873 biological processes. Furthermore, huperzine A possessed a binding affinity of -8.7 kcal/mol with AChE and interacted within the active site of AChE via H-bonds and hydrophobic interactions.

Gene ontology enrichment analysis of PPAR-γ modulators from Cassia glauca in diabetes mellitus

BACKGROUND

PPAR-γ has an integrative role in the management of insulin resistance; ligands of this receptor have emerged as potent insulin sensitizers and may modulate proteins involved in the pathogenesis of diabetes mellitus. Hence the present study is aimed to identify PPAR-γ modulators from the plant Cassia glauca and predict the ontology enrichment analysis utilizing various in-silico tools.

METHODS

ChEBI database was used to mine the phytoconstituents present in the plant C. glauca, SwissTargetPrediction database was used to identify the targets, and scrutinizing of phytoconstituents modulating PPAR-γ was performed. Autodock4.0 was used to dock phytoconstituent ligands with the target PPAR-γ. Multiple open-source databases and in-silico tools were utilized to predict the drug-likeness characters and predict side effects of the phytoconstituents modulating PPAR-γ and STRING database was used to construct a network between the modulated genes.

RESULTS

Twenty-four phytoconstituents were identified from the plant Cassia glauca from which four were found to modulate PPAR-γ, sennoside was predicted to have the greatest drug-likeness score and a significantly less side effect whereas diphenyl sulfone was predicted to show hepatotoxicity with the greatest pharmacological activity of 0.815. [epicatechin-(4beta- > 8)]5-epicatechin showed the lowest binding affinity with target PPAR-γ i.e. -8.6 kcal/mol and possessing a positive drug-likeness score with no side effect data.

CONCLUSION

Bioctives were found free from probable side effects leaving out diphenyl sulfone having a prediction of hepatotoxicity, the anti-diabetic property of the plant may be due to the presence of [epicatechin-(4beta- > 8)]5-epicatechin which needs further validation by in-vitro and in-vivo protocols.