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Trends in Bioinformatics
  Year: 2013 | Volume: 6 | Issue: 2 | Page No.: 25-44
DOI: 10.3923/tb.2013.25.44
 
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Breast Cancer Specific Histone Deacetylase Inhibitors and Lead Discovery using Molecular Docking and Descriptor Study
S. Sangeetha, S. Ranjitha, K. Murugan and G. Ramesh Kumar

Abstract:
Histone deacetylases 1 and 3 (HDAC1 and HDAC3) enzyme chromatin remodeling and gene transcription altering activities are implicated in tumor behavior and progression. Their inhibitors promising pre-clinical model therapeutic efficacy makes them likely anti-cancer targets for breast cancer therapeutic intervention. In this study, both natural and synthetic Histone Deacetylase Inhibitors (HDACi) were screened using in silico docking, molecular descriptors and pharmacophore models to design new molecules with potential HDAC1 and HDAC3 selectivity and inhibitory activity. Three dimensional (3D) homology models of HDAC1 and HDAC3 were built based on the crystal structure of human Histone deacetylase 2 (HDAC2). Lead optimization by docking several natural and synthetic compounds were carried out and compared. There are several natural HDACi available and curcumin was found to be best docked to HDAC1 and HDAC3. Through Virtual Screening (VS) top-scored compound curcumin was identified but it shows poor drug likeness property. To overcome this problem pharmacophore modeling of the curcumin based on virtual screening of (1E, 4E)-1,5-bis (3, 4-dimethoxyphenyl) penta-1, 4- dien-3-one was studied. This study was found to be best docked to HDAC1 and HDAC3 with highest binding energies -10.20 and -10.27 kcal/mol, respectively and interacts with active site of catalytic Zn2+ trihedrally coordinates to the side chains of amino acids. Curcumin analogue was predicted as a potential lead drug-like molecule that selectively inhibits HDAC1 and HDAC3 that may prevent the progression and pathogenesis of breast cancer.
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How to cite this article:

S. Sangeetha, S. Ranjitha, K. Murugan and G. Ramesh Kumar, 2013. Breast Cancer Specific Histone Deacetylase Inhibitors and Lead Discovery using Molecular Docking and Descriptor Study. Trends in Bioinformatics, 6: 25-44.

DOI: 10.3923/tb.2013.25.44

URL: https://scialert.net/abstract/?doi=tb.2013.25.44

 
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