Comparative Modeling, Molecular Docking, and Revealing of Potential Binding Pockets of RASSF2; a Candidate Cancer Gene

Abstract

RASSF2, potential tumor suppressor gene, acts as a KRAS-specific effectors protein and may promote apoptosis and cell cycle arrest. It stabilizes STK3/MST2 by protecting it from proteasomal degradation. RASSF2 plays a significant role against the inhibition of cancer. MODELLER (9v15) and online servers (I-Tasser, SwissModel, 3D-JigSaw, ModWeb) were utilized to generate 3D structures of the RASSF2 based on homology modeling. A comparison between models predicted by MODELLER (9v15) and Web servers had been checked through utilized evaluation tools. The most potent model for RASSF2 was analyzed and selected for molecular docking studies. The binding pockets were revealed for binding studies through Site Hound. AutoDock Vina and AutoDock4 were utilized for molecular docking, and the attempt of this experiment was to identify the ligands for RASSF2. The selected compounds may act as regulators and regulate the normal activity of RASSF2. It was also analyzed and observed that the selected compounds showed least binding energy and high-affinity binding in predicted top binding domain. The determination of protein function is based on accurate identification of binding sites in protein structures. The binding site is known, and it may allow the ligand type and protein function to be determined by performing in silico and experimental procedures. The detection, comparison, and analysis of binding pockets are pivotal to drug discovery. It proposed that predicted structure is reliable for the structural insights and functional studies. The predicted binding pockets may lead to further analysis (drug discovery), used against cancer study.

Multiscale analysis of acne connects molecular subnetworks with disease status

“…Isotretinoin, the most effective treatment for severe acne, triggers apoptosis in sebaceous glands (Nelson et al, 2008). Elevated levels of RASSF2 have been shown to increase apoptosis while higher levels of VOPP1 may decrease apoptotic potential (Baras et al, 2011;Kanwal et al, 2017). We observed both genes were upregulated in acne lesion samples.…”

Homology Model and Docking-Based Virtual Screening for Ligands of Human Dyskerin as New Inhibitors of Telomerase for Cancer Treatment

“…Furthermore, the Critical Assessment of protein Structure Prediction (CASP), a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994 [ 23 ], has ranked I-TASSER as the best method for automated protein structure prediction in many CASP experiments [ 24 ]. For example, in the field of cancer research, it has been used to model the RAB38 protein (Ras related protein 38), relevant in melanoma [ 25 ] and RASSF2 (Ras Association Domain Family Member 2), studied in different tumor types [ 26 ]. Similarly, in the study of malaria, a model of M17LAP (M17- Family Leucine Aminopeptidase) was obtained and then used as a target protein in a DBVS assay [ 27 ].…”

Artificial intelligence and big data facilitated targeted drug discovery

“…Traditional X-ray crystallography and nuclear magnetic resonance methods predict large amounts of protein structures that are time-consuming and expensive, but bioinformatics provides different tools to predict the 3D structure of proteins and reveal their binding regions. Its application is very promising, such as the identification of conserved binding pockets in ricin A chain,23 RASSF2 potential binding pocket prediction24 and so on. There are two ways to find a pocket combination: (1) proteins with known 3D structures can be searched from the PDB database,25 and related information can be downloaded directly from the database; and (2) method of homology modelling, using I-TASSER, SwissModel, ModWeb and other online servers based on homologous modelling to generate protein 3D structure, as well as to predict the ligand-binding pocket, for example, prediction of serotonin 1A receptor binding pocket 26…”