Pharmacophore Modeling and Virtual Screening
Studies to Design Potential Protein Tyrosine
Phosphatase 1B Inhibitors as New Leads |
Neelakantan Suresh1* and N. S. Vasanthi2
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1GVK Biosciences Pvt. Ltd., 37, Sterling Road, Nungambakkam, Chennai 600034, T.N., India |
2Head, Department of Biotechnology, Bannari Amman Institute of technology, Erode 638401, T.N., India |
| *Corresponding author: |
Dr. Neelakantan Suresh,
GVK Biosciences Pvt.
Ltd., 37, Sterling Road,
Nungambakkam, Chennai 600034, T.N., India. |
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Received September 27, 2009; Accepted January 12, 2010; Published
January 12, 2010 |
| Citation: Suresh N, Vasanthi NS (2010) Pharmacophore Modeling and Virtual Screening Studies to Design Potential Protein Tyrosine Phosphatase 1B Inhibitors as New Leads. J Proteomics Bioinform 3: 020- 028. doi:10.4172/jpb.1000117 |
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| Copyright: © 2010 Suresh N, et al. This is an open-access article distributed
under the terms of the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are credited. |
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| Abstract |
| Protein Tyrosine Phosphatase 1B (PTP-1B) is one of the
important targets in the treatment of diabetes and obesity.
They play a very important role in cellular signaling within
and between cells. The best pharmacophore hypothesis
(Hypo 1), consisting of four features, namely, one hydrogen-
bond acceptor (HBA), one hydrophobic point (HY),
and two ring aromatics (RA), has a correlation coefficient
of 0.961, a root mean square deviation (RMSD) of 0.885,
and a cost difference of 62.436, suggesting that a highly
predictive pharmacophore model was successfully obtained.
A chemical feature based pharmacophore model
has been generated from known PTP-1B inhibitors (25
training set compounds) by HypoGen module implemented
in CATALYST software. The top ranked hypothesis
(Hypo1) contained four chemical feature types such as
hydrogen-bond acceptor (HA), hydrophobic aromatic
(HY), and two ring aromatic (RA) features. Hypo1 was
further validated by 125 test set molecules giving a correlation
coefficient of 0.905 between experimental and estimated
activity. This was also validated using CatScramble
method. Thus, the Hypo1 was exploited for searching new
lead compounds over chemical compounds in Medichem
database and then the selected compounds were screened
based on restriction estimated activity. Finally, we obtained
30 new lead candidates and the one best highly active compound
structure was selected as a lead compound. The results
demonstrate that hypothesis derived in this study
could be considered to be a useful and reliable tool in identifying
structurally diverse compounds with desired biological
activity. |
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