Exploring Drug-Likeness and ADMET Profiling in Computational Drug Discovery

As part of my ongoing journey in computational biology and drug discovery, I recently worked on evaluating the pharmacokinetic and drug-likeness properties of selected compounds.

Using SwissADME, I performed detailed analysis of physicochemical properties, lipophilicity, solubility, and assessed compliance with Lipinski’s Rule of Five to determine drug-likeness.

Further, I extended the study to ADMET profiling (Absorption, Distribution, Metabolism, Excretion, and Toxicity) to better understand the biological behavior, safety, and efficacy of these compounds within the human body.

🧪 Key Highlights:
🔹 Drug-likeness screening and pharmacokinetics prediction
🔹 GI absorption and BBB permeability analysis
🔹 Evaluation of metabolic interactions and toxicity risks
🔹 Integration of in silico tools for efficient drug candidate selection

This experience strengthened my understanding of early-stage drug discovery and the importance of combining multiple computational approaches for better prediction accuracy.

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