Computational Identification of Potential RET Inhibitors for Targeted Lung Cancer Therapy through Molecular Docking and ADMET Profiling

Lung cancer, a leading cause of cancer-related mortality, often involves aberrations in the RET (Rearranged during Transfection) gene, making it a critical target for therapeutic intervention. This study aims to identify potential small molecule inhibitors for the RET protein through molecular docking, to enhance treatment options for RET-associated lung cancer. The 3D structure of the RET protein was obtained from the PDB database, and a library of 901 ligand molecules was sourced from SelleckChem. Refinement of this library using FAF-Drugs4 resulted in 266 molecules suitable for further analysis based on drug-like properties and ADMET profiles. Molecular docking simulations revealed that seven out of ten ligands formed at least one hydrogen bond with the RET protein, with Pyracarbolid exhibiting the highest number. Fenuron heptanoate, Bis(phenylthioureido)carbamoyl-ethanediyl, Fluorolintane, and Sulfanilamide-4-chlorobenzoyl chloride showed moderate interactions, while Phthalimide and Thalidomide formed the fewest hydrogen bonds. This study's docking analysis identified potential lead compounds with favorable binding characteristics, contributing to our understanding of ligand-receptor interactions and offering insights into the design of new drugs targeting the RET protein receptor.