Identification of novel selective antagonists for cyclin C by homology modeling and virtual screening
P Sarita Rajender1, M Vasavi, Uma Vuruputuri
1Department of Chemistry, Nizam College, Basheerbagh, Hyderabad 500001, Andhra Pradesh, India.
Abstract:
Cancer is a global multidrug resistant calamity, demanding an urgent need to design a novel/potent anti cancer agent. CDK8, 3/cyclin C biosynthetic pathway plays a specific role in G(0)/G(1)/S phases of cell cycle. Cyclin C is identified as a potential anti cancer target candidate. In order to understand the mechanism of ligand binding and interaction between ligand and cyclin C, a 3D homology model for cyclin C is generated. The cyclin C binding groove can be checked by small ligand molecules leading to inhibition. Virtual screening of molecules from an online data base of ChemBank library throws light to arrive at possible inhibitors for cyclin C inhibition. The molecules with better docking scores and acceptable ADME properties were prioritised to obtain potential lead molecules as cyclin C inhibitors.
Insights
Researchers identified potential new anti-cancer drugs by modeling cyclin C, a key cell cycle protein. Virtual screening of compounds revealed promising inhibitors for further development against cancer.
Area of Science:
- Biochemistry
- Molecular Biology
- Drug Discovery
Background:
- Cancer presents a global challenge due to multidrug resistance, necessitating novel therapeutic agents.
- The CDK8/cyclin C pathway is crucial in regulating cell cycle progression (G0/G1/S phases).
- Cyclin C is recognized as a promising molecular target for anti-cancer drug development.
Purpose of the Study:
- To investigate the ligand binding mechanisms and interactions with cyclin C.
- To identify potential inhibitors of cyclin C through virtual screening.
- To discover novel lead molecules for anti-cancer drug development.
Main Methods:
- Generation of a 3D homology model for cyclin C.
- Analysis of the cyclin C binding groove for potential inhibitor interactions.
- Virtual screening of the ChemBank library for candidate molecules.
- Prioritization based on docking scores and ADMET properties.
Main Results:
- A 3D model of cyclin C was successfully generated, enabling binding site analysis.
- Virtual screening identified several molecules with potential to inhibit cyclin C.
- Selected compounds exhibited favorable docking scores and predicted ADMET properties.
Conclusions:
- Cyclin C is a viable anti-cancer target.
- Virtual screening and computational modeling are effective in identifying potential cyclin C inhibitors.
- Prioritized lead molecules warrant further investigation as novel anti-cancer therapeutics.
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