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International Journal of Computational Bioinformatics and In Silico Modeling
2014: Volume-3 Issue-5
ISSN: 2320-0634

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ABSTRACT   REFERENCES  
International Journal of Computational Bioinformatics and In Silico Modeling 3(5) 2014: 479-482

Computer-aided Screening of Therapeutic Ligands against KLF8 Protein (Homo sapiens)



Renukesh Verma, Mayank Agarwal and Vinod Kumar Jatav*

Department of Biotechnology Madhav Institute of Technology & Science Gwalior-474005, Madhya Pradesh, India.

* Corresponding Author

ABSTRACT

Kruppel like factors (KLFs) are highly related zinc-finger proteins that are important components of the eukaryotic cellular transcriptional machinery. It is expressed in the nucleus of many cell types and its expression is elevated in several human cancers. KLF8 expression is increased in several types of human cancer cells and tissues, and ectopic expression of KLF8 induces transformation. The encoded protein is thought to play an important role in the regulation of epithelial to mesenchymal transition, a process which occurs normally during development but also during metastasis. In this study previously modelled structure was used for Docking and finding best binding ligand in the protein and that can alter the factions of KLF8 protein. For this purpose, a virtually screened 3D model of KLF8 was explored. The unliganded KLF8 was docked and best five docking solutions complex were selected and analyzed by Ligplot (http://www.ebi.ac.uk/thrnto-srv/software/LIGPLOT/). The analysis showed that Dasatinib, Doxorubicin, Pazopanib, Sorafenib & SU 6656 has maximum potential against unliganded protein. The analysis was done on the basis of scoring and binding ability and Dasatinib indicated minimum energy score and highest number of interactions with active site residue and could be a promising inhibitor for KLF8 as Drug target.

 


Copyright © 2014 | AIZEON publishers | All rights reserved

 

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Citation: Renukesh Verma et al. (2014). Computer-aided Screening of Therapeutic Ligands against KLF8 Protein (Homo sapiens). Int J Comput Bioinfo In Silico Model 3(5): 479-482

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