A Computational Framework for Evaluating the Antidiabetic Potential of Medicinal Plant‐Derived Natural Products as Glucokinase Activators ( <scp>GCKAs</scp> ) for Type 2 Diabetes Mellitus ( <scp>T2DM</scp> )

ABSTRACT Diabetes mellitus continues to be a significant global health burden due to its increasing prevalence, high cost of treatment expenditures, and limitations with current therapies. Glucokinase (GCK), a key regulator of glucose homeostasis in hepatocytes and pancreatic β‐cells, functions as a glucose sensor. Focusing on GCK over glucokinase activators (GCKAs) characterizes a promising therapeutic approach for type 2 diabetes mellitus. This study used multi‐scale computational techniques to identify potential natural GCKAs from a library of 2111 bioactive compounds derived from antidiabetic medicinal plants, retrieved from the IMPPAT database. Structure‐based virtual screening against GCK revealed that the control molecule, Dorzagliatin, exhibited a GLIDE XP docking score of −6.25 kcal/mol, while the bioactive compounds IMPHY002045, IMPHY002715, and IMPHY001453 demonstrated higher GLIDE XP docking scores of −9.95, −8.27, and −7.71 kcal/mol, respectively. These bioactive compounds exhibited strong binding affinity and favorable interactions, further supported by MM/GBSA binding free energy (≥ −89 kcal/mol). In silico pharmacokinetic and toxicity profiling using QikProp and ProTox indicated acceptable drug‐like properties. Density functional theory (DFT) analysis revealed favorable quantum chemical properties. Furthermore, 300 ns molecular dynamics simulations confirmed stable binding behavior. Principal component analysis (PCA) and free energy landscape (FEL) analysis showed restricted conformational dynamics and well‐defined energy minima, indicating stable conformational states. The integrated computational findings provide a strong rationale for progressing these compounds toward experimental validation and preclinical evaluation as potential antidiabetic agents.