In silico evaluation of pharmacokinetic properties and molecular docking for the identification of potential anticancer compounds

The integration of ADME(T) profiling, machine learning, and molecular docking provides a comprehensive and reproducible computational strategy for drug discovery. The approach enabled the identification of compounds with favorable pharmacokinetic properties and selective inhibitory potential, supporting compound CC-43 as a promising candidate for further exploration in breast cancer therapeutics.