Pendekatan In Silico dalam Penemuan Senyawa Bioaktif Tanaman sebagai Kandidat Obat Antidiabetes

Abstract

This paper presents a narrative review focusing on the significance of in silico methodologies in identifying and evaluating natural bioactive compounds as promising antidiabetic agents. By examining scientific publications from 2020 to 2025, the review highlights substantial evidence that various plant-derived metabolites such as flavonoids, phenolic acids, terpenoids, and glycosides from Orthosiphon stamineus, Moringa oleifera, Syzygium polyanthum, Tinospora crispa, and Albizia saman demonstrate notable affinity toward several crucial enzymes implicated in type 2 diabetes, including DPP-4, SGLT-2, α-glucosidase, and PTP1B. Findings from molecular docking analyses and ADMET simulations indicate that many of these compounds exhibit favorable pharmacokinetic behavior, strong receptor interactions, and minimal toxicity, suggesting their potential as multitarget natural therapeutics with synergistic modes of action. Utilizing in silico screening as an initial step effectively predicts biological activity and pharmacological profiles prior to experimental validation through in vitro and in vivo testing, thus reducing both time and research expenditure. The synergy between computational modeling, medicinal chemistry, and phytochemical exploration establishes a scientific framework that supports the advancement of rational, safe, and sustainable herbal-based antidiabetic drug development derived from Indonesia’s vast biodiversity and encourages self-reliance within the national pharmaceutical sector.