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In Silico Study of Beluntas Leaves (Pluchea indica) on DPP-4, α-Glucosidase, SGLT-2, and PPAR-γ as Antidiabetic Targets

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Background: Diabetes mellitus (DM) is a chronic metabolic disease with a steadily increasing prevalence globally. Long-term use of synthetic antidiabetic drugs is often associated with side effects, making exploration of alternative therapies from natural ingredients important. Pluchea indica L. leaves have been reported as a traditional Indonesian plant empirically used to lower blood sugar levels. Objective: This study aims to explore the potential of active compounds from Pluchea indica L. leaves as candidate multi-target antidiabetic agents through an in silico approach. Methods: An in silico study was conducted using molecular docking with Molegro Virtual Docker (MVD) to evaluate the interaction of four active compounds from beluntas leaves [(+)-Lirioresinol B, β Stigmasterol, (+)-Pinoresinol, and Plucheoside A against diabetes target proteins DPP-4 (PDB: 4FFW), α-glucosidase (PDB: 3L4W), SGLT-2 (PDB: 7VSI), and PPAR-γ (PDB: 5UGM)]. Method validation was performed by re-docking the original ligands (RMSD < 2.0 Å). Lipinski's 5 Rule analysis and ADMET prediction were performed to evaluate the drug-likeness and pharmacokinetic profiles of the compounds. Results: Method validation showed RMSD of 0.31-1.71 Å for all target proteins. Docking results showed that (+)-Pinoresinol had the best affinity as a DPP-4 inhibitor (Rerank score -103.452), (+)-Lirioresinol B as an α-glucosidase inhibitor (-100.173), Plucheoside A as an SGLT-2 inhibitor (-126.555), and β Stigmasterol as a PPAR-γ agonist (-131.023). Lipinski's 5 Rules analysis showed that all compounds most often violated 1 criterion (PSA). ADMET predictions showed an acceptable pharmacokinetic profile with low toxicity. Conclusion: The active compounds from beluntas leaves show potential as multi-target antidiabetic agents with good binding affinity to diabetes target proteins. These findings are still predictive and require further validation through in vitro and in vivo studies to confirm their biological activity, selectivity, safety, and pharmacological relevance as effective antidiabetic candidates in the future.
Title: In Silico Study of Beluntas Leaves (Pluchea indica) on DPP-4, α-Glucosidase, SGLT-2, and PPAR-γ as Antidiabetic Targets
Description:
Background: Diabetes mellitus (DM) is a chronic metabolic disease with a steadily increasing prevalence globally.
Long-term use of synthetic antidiabetic drugs is often associated with side effects, making exploration of alternative therapies from natural ingredients important.
Pluchea indica L.
leaves have been reported as a traditional Indonesian plant empirically used to lower blood sugar levels.
Objective: This study aims to explore the potential of active compounds from Pluchea indica L.
leaves as candidate multi-target antidiabetic agents through an in silico approach.
Methods: An in silico study was conducted using molecular docking with Molegro Virtual Docker (MVD) to evaluate the interaction of four active compounds from beluntas leaves [(+)-Lirioresinol B, β Stigmasterol, (+)-Pinoresinol, and Plucheoside A against diabetes target proteins DPP-4 (PDB: 4FFW), α-glucosidase (PDB: 3L4W), SGLT-2 (PDB: 7VSI), and PPAR-γ (PDB: 5UGM)].
Method validation was performed by re-docking the original ligands (RMSD < 2.
0 Å).
Lipinski's 5 Rule analysis and ADMET prediction were performed to evaluate the drug-likeness and pharmacokinetic profiles of the compounds.
Results: Method validation showed RMSD of 0.
31-1.
71 Å for all target proteins.
Docking results showed that (+)-Pinoresinol had the best affinity as a DPP-4 inhibitor (Rerank score -103.
452), (+)-Lirioresinol B as an α-glucosidase inhibitor (-100.
173), Plucheoside A as an SGLT-2 inhibitor (-126.
555), and β Stigmasterol as a PPAR-γ agonist (-131.
023).
Lipinski's 5 Rules analysis showed that all compounds most often violated 1 criterion (PSA).
ADMET predictions showed an acceptable pharmacokinetic profile with low toxicity.
Conclusion: The active compounds from beluntas leaves show potential as multi-target antidiabetic agents with good binding affinity to diabetes target proteins.
These findings are still predictive and require further validation through in vitro and in vivo studies to confirm their biological activity, selectivity, safety, and pharmacological relevance as effective antidiabetic candidates in the future.

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