Applying Network Pharmacology and Molecular Docking in the Screening for Molecular Mechanisms of Ampalaya (Momordica charantia L.) and Banaba (Lagerstroemia speciosa L.) against Type 2 Diabetes Mellitus

Abstract

Background and Objectives Type 2 diabetes mellitus (T2DM) is a global health concern affecting more than 400 million people worldwide. Diabetic neuropathy, nephropathy, retinopathy, and cardiovascular complications lead to debilitating effects to patients. To prevent these, the treatment goal is to lower the blood sugar levels and maintain at a normal range which is achieved through conventional treatments like insulin and oral hypoglycemic agents. However, the high cost of these medications implicates patient treatment outcomes. Hence, alternatives are sought for including the use of herbal medicines. Momordica charantia (MC) and Lagerstroemia speciosa (LS) are common herbal medicines used to manage T2DM. In the Philippines, these herbal preparations are validated for their glucose lowering effects and are commonly found in combination in food supplements. The study aims to screen the possible mechanisms of compounds present in these herbal medicines which can offer possible explanations for their synergistic effects and rationalization of their combination in preparations. Methods Network pharmacology was employed to determine pivotal proteins that are targeted by MC and LS compounds. Molecular docking was then done to evaluate the favorability of the binding of these compounds toward their target proteins. Results Our results showed that TNF, HSP90AA1, MAPK3, ALDH2, GCK, AKR1B1, TTR and RBP4 are the possible pivotal targets of MC and LS compounds in T2DM. Conclusion Terpenoids from MC and decanoic acid from LS are the compounds which showed favorable binding towards pivotal protein targets in T2DM. By binding towards the different key proteins in T2DM, they may exhibit their synergistic effects. However, the results of this study are bound to the limitations of computational methods and experimental validation are needed to verify our findings.