Network pharmacology-based approach to investigate the molecular targets and molecular mechanisms of Rosmarinus officinalis L. for treating aging-related disorders.

Aging, a natural biological process, presents challenges in maintaining physiological well-being and is associated with increased vulnerability to diseases. Addressing aging mechanisms is crucial for developing effective preventive and therapeutic strategies against age-related ailments. Rosmarinus officinalis L. is a medicinal herb widely used in traditional medicine, containing diverse bioactive compounds that have been studied for their antioxidant and anti-inflammatory properties, which are associated with potential health benefits. Using network pharmacology, this study investigates the anti-aging function and underlying mechanisms of R. officinalis. Through network pharmacology analysis, the top 10 hub genes were identified, including TNF, CTNNB1, JUN, MTOR, SIRT1, and others associated with the anti-aging effects. This analysis revealed a comprehensive network of interactions, providing a holistic perspective on the multi-target mechanism underlying Rosemary's anti-aging properties. GO and KEGG pathway enrichment analysis revealed the relevant biological processes, molecular functions, and cellular components involved in treating aging-related conditions. KEGG pathway analysis shows that anti-aging targets of R. officinalis involved endocrine resistance, pathways in cancer, and relaxin signaling pathways, among others, indicating multifaceted mechanisms. Genes like MAPK1, MMP9, and JUN emerged as significant players. These findings enhance our understanding of R. officinalis's potential in mitigating aging-related disorders through multi-target effects on various biological processes and pathways. Such approaches may reduce the risk of failure in single-target and symptom-based drug discovery and therapy.

Screening of potential inhibitors of Leishmania major N-myristoyltransferase from Azadirachta indica phytochemicals for leishmaniasis drug discovery by molecular docking, molecular dynamics simulation and density functional theory methods.

Leishmaniasis is one of the most neglected parasitic diseases worldwide. The toxicity of current drugs used for its treatment is a major obstacle to their effectiveness, necessitating the discovery and development of new therapeutic agents for better disease control. In Leishmania parasites, N-Myristoyltransferase (NMT) has been identified as a promising target for drug development. Thus, exploring well-known medicinal plants such as Azadirachta indica and their phytochemicals can offer a diverse range of treatment options, potentially leading to disease prevention and control. To assess the therapeutic potential of these compounds, their ADMET prediction and drug-likeness properties were analyzed. The top 4 compounds were selected which had better and significantly low binding energy than the reference molecule QMI. Based on the binding energy score of the top compounds, the results show that Isonimocinolide has the highest binding affinity (-9.8 kcal/mol). In addition, a 100 ns MD simulation of the four best compounds showed that Isonimocinolide and Nimbolide have good stability with LmNMT. These compounds were then subjected to MMPBSA (last 30 ns) calculation to analyze protein-ligand stability and dynamic behavior. Nimbolide and Meldenin showed lowest binding free energy i.e. -84.301 kJ/mol and -91.937 kJ/mol respectively. DFT was employed to calculate the HOMO-LUMO energy gap, global reactivity parameters, and molecular electrostatic potential of all hit molecules. The promising results obtained from MD simulations and MMPBSA analyses provide compelling evidence for the potential use of these compounds in future drug development efforts for the treatment of leishmaniasis.Communicated by Ramaswamy H. Sarma.

Network pharmacology, molecular docking, and molecular dynamics simulation to elucidate the mechanism of anti-aging action of Tinospora cordifolia.

Scientific research has demonstrated that Tinospora cordifolia acts as an anti-aging agent in several experimental models, generating global interest in its underlying molecular mechanisms of this activity. The aim of the study was to identify the possible phytochemical compounds of T. cordifolia that might combat age-related illness through integrating network pharmacology, molecular docking techniques, and molecular dynamics (MD) study to explore their potential mechanisms of action. To carry out this study, several databases were used, including PubChem, KNApSAcK family database, PubMed, SwissADME, Molsoft, SwissTargetPrediction, GeneCards, and OMIM database. For network development and GO enrichment analysis KEGG, ShinyGo 0.77, and the STRING database were used. For better analysis, the networks were also constructed using Cytoscape 3.9.1. The Cytoscape network analyzer tool was used for data analysis, and molecular docking was done via Vina-GPU-2.0. The best compounds and AKT1 were finally subjected to MD simulation for 100 ns. The CytoHubba plugin of Cytoscape identified ten key targets, commonly called hub genes, including AKT1, GAPDH, and TP53, and so on. GO and KEGG pathway enrichment analysis revealed the relevant biological processes, cellular components, and molecular functions involved in treating aging-related disorders. KEGG pathway analysis involved neuroactive ligand-receptor interactions, lipid and atherosclerosis, and cAMP signaling. The docking of 100 T. cordifolia compounds with AKT1 demonstrated good binding affinity, particularly for Amritoside, Sitagliptin, Berberine, and Piperine. Finally, the relative stability of four-hit phytochemicals was validated by MD simulation, which may be the most crucial compound for anti-aging activity. In conclusion, this study used network pharmacology, molecular docking, and MD simulation to identify the compounds in T. cordifolia and proposed a potential mechanism for anti-aging activity. These results suggest future directions for the prevention and treatment of age-related diseases.