Computational ADME Modeling of Selected Terpenoids Using Swiss ADME

Terpenoids, a large and diverse class of naturally occurring organic compounds, have shown significant therapeutic potential, including antimicrobial, anticancer, and anti-inflammatory properties. However, the pharmacokinetic behavior of terpenoids, particularly their absorption, distribution, metabolism, and excretion (ADME) profiles, remains a critical factor in their drug development process. Computational ADME modeling has emerged as a powerful tool for earlystage screening of bioactive compounds, enabling the efficient prediction of pharmacokinetic properties and drug-likeness. This review focuses on the application of SwissADME, a widely used web-based platform, for evaluating the ADME characteristics of selected terpenoids. The tool offers various predictive modules including Lipinski's rule of five, bioavailability radar, gastrointestinal absorption, blood-brain barrier permeability, and cytochrome P450 interactions. By analyzing computational ADME data, this review highlights key pharmacokinetic attributes of terpenoids that influence their drug-likeness and therapeutic potential. Overall, the use of SwissADME in evaluating natural compounds streamlines the selection of promising terpenoid candidates for further experimental and clinical validation, thus accelerating natural product-based drug discovery.