In silico Pharmacokinetic, Bioactivity and Toxicity Evaluation of Some Selected Anti-Diabetic Agents

Diabetes mellitus is among the most common chronic metabolic disorders worldwide and is characterized by persistently high blood glucose levels resulting from insufficient insulin secretion, insulin resistance, or a combination of both. The primary goals of diabetes management are to maintain optimal glycemic control, reduce symptoms, and prevent long-term complications such as cardiovascular disease, nephropathy, retinopathy, and neuropathy. Although several anti-diabetic therapies are currently available, many are associated with limitations, including hypoglycemia, weight gain, gastrointestinal discomfort, and concerns regarding long-term safety. Therefore, evaluating the drug-likeness, pharmacokinetic behavior, biological activity, and toxicity potential of existing anti-diabetic drugs is crucial to support the development of safer and more effective alternatives. In this study, in silico computational approaches were used to analyse the pharmacokinetic profiles, bioactivity scores, and toxicity risks of six commonly prescribed anti- diabetic agents: metformin, sit gliptin, pioglitazone, empagliflozin, dapagliflozin, and glimepiride. Key physicochemical parameters such as molecular weight, logP, topological polar surface area (TPSA), hydrogen bond donors and acceptors, rotatable bonds, and predicted absorption were calculated using Mo inspiration Cheminformatics tools and assessed according to Lipinski’s rule of five. Bioactivity was evaluated across major biological target classes, including GPCR ligands, ion channel modulators, kinase inhibitors, nuclear receptor ligands, protease inhibitors, and enzyme inhibitors, while toxicity risks such as oncogenicity, mutagenicity, teratogenicity, irritation, sensitivity, immunotoxicity, and neurotoxicity were predicted using Pallas ADMETox software. The results indicated that most of the selected drugs comply well with drug-likeness criteria, exhibit balanced lipophilicity, and show moderate to good absorption based on TPSA values. The majority of compounds demonstrated significant bioactivity, particularly as enzyme inhibitors, aligning with their known mechanisms of action. Toxicity predictions were generally favorable for metformin, empagliflozin, and dapagliflozin, whereas pioglitazone displayed higher risk levels across several toxicity parameters. Overall, these in silico findings provide meaningful insights into the advantages and limitations of current anti-diabetic medications and offer valuable guidance for the rational design of new agents with improved pharmacokinetic properties, enhanced efficacy, better target selectivity, and reduced toxicity, thereby contributing to more effective management of the growing global burden of diabetes.