In silico evaluation of drug-likeness and toxicity profi ling of selected organic compounds

Abstract

In silico approaches have become essential tools in modern drug discovery for the therapeutic and cost-effective evaluation of chemical compounds. This study focuses on the assessment of drug-likeness and toxicity profiles of five selected organic compounds: aspirin, caffeine, ibuprofen, metformin, and benzene. The compounds were analyzed using computational tools to evaluate their pharmacokinetic properties based on established criteria such as Lipinski's rule of five, along with toxicity prediction models. The drug likeness analysis revealed that aspirin, caffeine, ibuprofen, and metformin exhibit favorable physicochemical properties, indicating good oral bioavailability and suitability as potential drug candidates. Benzene showed significant toxicity concerns, including predicted carcinogenicity and neurotoxicity. These findings highlight that compliance with drug-likeness rules alone does not guarantee safety and underscore the importance of complementary toxicity assessment during early-stage screening. Toxicity profiling indicated that most compounds possess acceptable safety profiles, whereas benzene demonstrated higher toxicity risks, including possible carcinogenic and mutagenic effects. Overall, this study demonstrates that in silico methods are effective tools for early-stage screening of drug candidates, helping to reduce time, cost, and experimental effort in pharmaceutical research.