Exploring the therapeutic mechanism of potential phytocompounds from Kalanchoe pinnata in the treatment of diabetes mellitus by integrating network pharmacology, molecular docking and simulation approach.

Since ancient times, bioactive phytocompounds from different parts of medicinal plants have been used to heal various disease ailments and they are now regarded as a valuable source of disease prevention globally. Kalanchoe pinnata is a member of the Crassulaceae family; it has a long history of usage in traditional ayurvedic treatment. Analysis of bioactive compounds for their potential anti-type-2 diabetes mellitus (T2DM) mechanism along with in-vitro and in-silico approaches was studied in the present research. The alpha-amylase and alpha-glucosidase inhibitory activity of methanolic extract of Kalanchoe pinnata (α-amylase: IC50 29.50 ± 0.04 µg/ml; α-glucosidase IC50 32.04 ± 0.35 µg/ml) exhibit a high degree of similarity to the standard drug acarbose (IC50 35.82 ± 0.14 µg/ml). Different biological databases were used to list phytocompounds from the plant, and ADME analysis using swissADME was carried out to screen compounds that obeyed the Lipinski rule of 5 and were employed further. STRING and KEGG pathway analysis was performed for gene enrichment analysis followed by network pharmacology to identify key target proteins involved in DM. AMY2A, NOX4, RPS6KA3, ADRA2A, CHRM5, and IL2 were identified as core targets for luteolin, kaempferol, alpha amyrin, stigmasterol compounds by modulating neuroactive ligand interaction, P13-AKT, MAPK, and PPAR signaling pathways. Molecular docking was performed to study the binding affinity among bioactive compounds of K. pinnata against aldose reductase, alpha-amylase, alpha-glucosidase, and dipeptidyl peptidase IV. Alpha-amylase-friedelin [FRI] and alpha-amylase-acarbose [STD] complexes were subjected to molecular simulation for a 200 ns duration that depicted the stability of the compounds and proteins. In the current study, employing dual approach in-silico and in-vitro enzyme assays has yielded a comprehensive and strong understanding of its potential therapeutic properties, making a significant step towards the development of novel anti-diabetic treatment.

Network pharmacology based anti-diabetic attributes of bioactive compounds from Ocimum gratissimum L. through computational approach.

The present research was framed to determine the key compounds present in the plant Ocimum gratissimum L. targeting protein molecules of Diabetes Mellitus (DM) by employing In-silico approaches. Phytochemicals previously reported to be present in this herb were collated through literature survey and public phytochemical databases, and their probable targets were anticipated using BindingDB (p ≥ 0.7). STRING and KEGG pathway databases were employed for pathway enrichment analysis. Homology modelling was executed to elucidate the structures of therapeutic targets. Further, Phytocompounds from O. gratissimum were subjected for docking with four therapeutic targets of DM by using AutoDock vina through POAP pipeline implementation. 30 compounds were predicted to target 136 protein molecules including aldose reductase, DPP4, alpha-amylase, and alpha-glucosidase. Neuroactive ligand-receptor interaction, MAPK, PI3K-Akt, starch and insulin resistance were predicted to have potentially modulation by phytocompounds. Based on the phytocompound's binding score with the four targets of DM, Rutin scored the lowest binding energy (-11 kcal/mol) with Aldose reductase by forming 17 intermolecular interactions. In conclusion, based on the network and binding score, phytocompounds from O. gratissimum have a synergistic and considerable effect in the management of DM via multi-compound, multi-target, and multi-pathway mechanisms.