Comparative modeling and structure-based identification of drug target sites in RASSF4 using molecular docking approaches

Research article | https://doi.org/10.47262/BL/11.2.20250511

Misha Tanveer 1, Zunaira Saif Ullah 2, Huma Nawaz 3, Muhammad Jahangir Shafi 3*

1 Department of Biotechnology, University of Okara, Okara, Pakistan

2 Department of Bioinformatics, University of Okara, Okara, Pakistan

3 Department of Biotechnology, Institute of Biochemistry, Biotechnology and Bioinformatics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan

Abstract

RASSF4, a potential tumor suppressor gene, functions as a KRAS-specific effector protein that may induce apoptosis and cell cycle arrest, playing a significant role in cancer inhibition. In human tumor cells, RASSF4 expression is often suppressed due to promoter methylation. In this study, homology modeling was performed using online servers (I-TASSER, SwissModel, and ModWeb) to generate 3D structures of RASSF4. Models predicted by these web servers were compared with those generated using MODELLER 10.4, and their quality was assessed using standard evaluation tools. The most potent RASSF4 model was selected for molecular docking studies. The structure was visualized and further refined. Binding pockets were identified. Two chemically designed ligands, ANP and GNP, were selected to enhance the activity of the anticancer target protein RASSF4. Molecular docking was conducted to identify potential binding sites. The predicted structure showed high precision, particularly at the active site, indicating that it is suitable for structural and functional analyses. These predicted binding pockets may serve as starting points for further drug discovery in cancer research.