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Exploring CIP2A modulators using multiple molecular modeling approaches
Shovonlal Bhowmick1, Kunal Roy2, Achintya Saha1
1Department of Chemical Technology, University of Calcutta, Kolkata, West Bengal, India.
Abstract:
Like other human oncoproteins, Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) exerts cancer promoting function through interaction with other partner proteins, such as MYC and Protein Phosphatase 2A (PP2A). CIP2A regulates several MYC-independent and/or dependent gene expression programs. Broadly, CIP2A can inhibit PP2A, and especially it has been shown to inhibit MYC-associated PP2A, precisely to increase MYC stability and function. Availability of crystal structure has broached the research focus to develop new therapeutics targeting CIP2A. In the present study, structural information of the protein has been used for identification of modulators for homo-dimer CIP2A using advanced structure-based drug design approaches. The compound library, 'Maybridge Screening Collection' database (∼62,000 compounds) has been virtually screened to find out potent modulators for CIP2A. Identification of hotspot region on CIP2A protein-protein interaction interface has been performed using three different tools (HotPoint, SiteMap and icmPocketFinder). Thereafter, molecular docking (Extra Precision and Induced Fit Docking), and long range molecular dynamics simulation analysis, and ADME profile analysis have been carried out for screening purposes. Calculations of MM-PBSA based binding free energy (ΔG), and Density Functional Theory for quantum chemical simulations have been carried out for the hit compounds obtained through multi-step molecular docking based virtual screening technique. The multi-chemometric studies suggested that hit modulators have formed significant numbers of molecular interactions with hotspot residues in the homo-dimer interface region, which enable to hold CIP2A binding stability. Compounds with average ΔG values (ranging -3.4 x 10-2 to -1.1 x 10-2 KJ/mol) signifying promising CIP2A modulators.Communicated by Ramaswamy H. Sarma.
Insights
Researchers identified potential drug candidates targeting Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A), a protein involved in cancer progression. Structure-based drug design and virtual screening pinpointed compounds that bind to CIP2A
Area of Science:
- Oncology
- Structural Biology
- Drug Discovery
Background:
- Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) is an oncoprotein that promotes cancer by interacting with proteins like MYC and Protein Phosphatase 2A (PP2A).
- CIP2A inhibits PP2A, particularly MYC-associated PP2A, to enhance MYC stability and function, contributing to cancer development.
- The availability of CIP2A's crystal structure has opened avenues for developing targeted therapeutics.
Purpose of the Study:
- To identify modulators of the CIP2A homo-dimer using structure-based drug design approaches.
- To screen a large compound library for potential CIP2A inhibitors.
- To validate the binding stability and interactions of identified hit compounds.
Main Methods:
- Virtual screening of the Maybridge Screening Collection database (approx. 62,000 compounds).
- Identification of hotspot regions on the CIP2A protein-protein interaction interface using HotPoint, SiteMap, and icmPocketFinder.
- Molecular docking, molecular dynamics simulations, ADME profiling, MM-PBSA binding free energy calculations, and Density Functional Theory (DFT) for hit compound analysis.
Main Results:
- A multi-step virtual screening approach identified potent modulators of CIP2A.
- Hit compounds demonstrated significant molecular interactions within the homo-dimer interface hotspot region, ensuring binding stability.
- Calculated average binding free energy (ΔG) values ranged from -3.4 x 10-2 to -1.1 x 10-2 KJ/mol, indicating promising CIP2A modulation.
Conclusions:
- The study successfully identified promising CIP2A modulators using advanced structure-based drug design.
- These identified compounds show potential for further development as targeted cancer therapeutics.
- The findings highlight the utility of computational approaches in discovering novel drug candidates for oncoproteins.
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