Unveiling the antidiabetic potential of kemuning leaves (murraya paniculata l. Jack): an in-silico exploration of dpp-4 inhibitory activity. Explore the antidiabetic potential of Kemuning leaves (Murraya paniculata L. Jack) as natural DPP-4 inhibitors via an in-silico study, identifying promising compounds for type 2 diabetes.
Type 2 diabetes mellitus is a global health issue associated with insulin resistance and impaired glucose metabolism. Murraya paniculata L. Jack (kemuning) has shown antidiabetic potential, yet its role as a DPP-4 inhibitor remains underexplored. This study aimed to investigate the potential of kemuning leaf bioactive compounds as natural DPP-4 inhibitors through an in-silico approach. Compound structures were obtained from the PubChem database and analyzed using AutoDock Vina for molecular docking against the DPP-4 protein. Pharmacokinetic properties, toxicity, and drug-likeness were evaluated using pkCSM and SwissADME, while complex stability was assessed through molecular dynamics simulation (RMSF). The results showed that most compounds demonstrated favorable binding affinities (−6.8 to −7.9 kcal/mol), along with acceptable pharmacokinetic and toxicity profiles. Among the tested compounds, 1-aminoindan-1,5-dicarboxylic acid emerged as the most promising candidate for natural DPP-4 inhibition.
This study presents a timely and well-structured in-silico investigation into the antidiabetic potential of *Murraya paniculata L. Jack* (kemuning) leaves, specifically focusing on their ability to inhibit dipeptidyl peptidase-4 (DPP-4), a crucial target in Type 2 diabetes management. The global health challenge posed by Type 2 diabetes underscores the continuous need for novel therapeutic agents, with natural products offering a rich source for such discoveries. While kemuning has been traditionally recognized for its antidiabetic properties, its precise mechanism via DPP-4 inhibition has remained largely unexplored. This research effectively addresses this knowledge gap by computationally identifying promising compounds from kemuning leaves that could act as natural DPP-4 inhibitors. The authors employed a comprehensive and rigorous in-silico methodology, utilizing state-of-the-art computational tools to screen bioactive compounds. The pipeline included sourcing compound structures from the PubChem database, performing molecular docking simulations with AutoDock Vina against the DPP-4 protein, and critically, assessing pharmacokinetic properties, toxicity, and drug-likeness via pkCSM and SwissADME. A notable strength of this work is the inclusion of molecular dynamics simulations (RMSF) to evaluate the stability of the compound-protein complexes, adding a robust layer of validation to the predicted interactions. The results are compelling, revealing that most tested compounds demonstrated favorable binding affinities (ranging from −6.8 to −7.9 kcal/mol) alongside acceptable pharmacokinetic and toxicity profiles, with 1-aminoindan-1,5-dicarboxylic acid emerging as the most promising candidate. This in-silico exploration makes a significant contribution by providing a strong computational foundation for further drug discovery efforts from *Murraya paniculata*. The identification of 1-aminoindan-1,5-dicarboxylic acid as a lead compound with potential DPP-4 inhibitory characteristics, supported by favorable ADMET profiles and complex stability, is a valuable outcome. However, as an in-silico study, its inherent limitations necessitate immediate experimental validation. Future research should prioritize in-vitro assays to confirm the predicted DPP-4 inhibitory activity and cytotoxicity, followed by in-vivo studies to ascertain efficacy and safety. Overall, this work serves as an excellent preliminary screening, effectively narrowing down potential candidates and providing clear directions for subsequent wet-lab investigations into novel antidiabetic agents from natural sources.
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