Comparative modeling and in silico identification of drug target sites in RASSF3

RASSF3 is a gene that encodes a protein with tumor-suppressive properties, primarily by promoting apoptosis and regulating the cell cycle. It plays a significant role in inhibiting cancer progression. In this study, the 3D structure of RASSF3 was predicted using homology modeling. MODELLER (v10.4) and online tools such as I-TASSER, Swiss-Model, and MODWEB were employed for model generation. The structural models were evaluated for accuracy using tools including ERRAT, PROCHECK, and Rampage. The most reliable model, based on validation, was selected for molecular docking studies. Binding pockets of RASSF3 were identified using the CASTp server. Molecular docking was carried out using AutoDock Vina and AutoDock4 to investigate the interaction between RASSF3 and two selected ligands: ANP and GNP. These compounds demonstrated the lowest binding energies of -5.7 and -5.3 Kcal/mol respectively and the highest binding affinities within the top-ranked binding site. Identification of these binding domains and ligand interactions is critical for understanding the functional behavior of RASSF3 and its role in cancer inhibition. The predicted binding pockets and docking results suggest that RASSF3 could serve as a promising target in anticancer drug discovery.