Finding Novel Anti-carcinomas Compounds by Targeting SFRP4 Through Molecular Modeling, Docking and Dynamic Simulation Studies

Author(s): M. Hassan, M. Azhar, Q. Abbas, H. Raza, A.A. Moustafa, S. Shahzadi, Z. Ashraf*, S.Y. Seo*.

Journal Name: Current Computer-Aided Drug Design

Volume 14 , Issue 2 , 2018

Graphical Abstract:


Background: Secreted Frizzled-Related Protein 4 (SFRP4) is a glycoprotein that acts as a competitor of both canonical and non-canonical Wnt pathways. SFRP4 is mostly expressed in ovary and plays a significant role as a target molecule to cure ovarian carcinoma.

Objective: Multiple chemical agonists are being used to cure ovary melanoma. We are interested in theoretically analyzing the compounds through computational approaches for their potential inhibitory effects against SFRP4.

Methods: Compounds were sketched in Chemsketch drawing tool and minimized through chimera tool. Because the crystal structure of SFRP4 is not available in Protein Data Bank, homology modeling approach was used to predict Three-Dimensional (3D) crystal structure of SFRP4. Moreover, multiple computational approaches such as molecular docking and Molecular Dynamic (MD) simulations along with various online tools were employed to screen the best inhibitor against ovary melanoma.

Results: The docking results showed that 1d and 1e compounds revealed significant binding energy values (-9.10 and -9.00 kcal/mol, respectively) compared with the standard drugs such as cis-platin and docetaxel (-3.30, -10.80 kcal/mol), respectively. Moreover, MD simulation results showed that 1d has little fluctuations throughout the simulation period as depicted by the root mean square deviation and root mean square fluctuation graphs.

Conclusion: The present in-silico study provides a deeper insight into the structural attributes of 1d compound and its overall molecular interactions against SFRP4 and gives a hypothetical gateway to use this compound as a potential inhibitor against ovarian carcinoma.

Keywords: SFRP4, cancer, computational modeling, molecular docking, dynamic simulation.

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Article Details

Year: 2018
Page: [160 - 173]
Pages: 14
DOI: 10.2174/1573409914666180112100122
Price: $58

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