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Molecular Docking Studies on Pyrazolopyrimidine and their Derivatives as Human Phosphoinositide 3-Kinase Inhibitors


 
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1. Title Title of document Molecular Docking Studies on Pyrazolopyrimidine and their Derivatives as Human Phosphoinositide 3-Kinase Inhibitors
 
2. Creator Author's name, affiliation, country Dr. Basundhara Chaudhary; Department of Bioinformatics, Singhania University, Jhunjhunu, Rajasthan; India
 
2. Creator Author's name, affiliation, country Dr. Sumer Singh; Department of Bioinformatics, Singhania University, Jhunjhunu, Rajasthan; India
 
3. Subject Discipline(s) Bioinformatics and drug designing
 
3. Subject Keyword(s) AutoDock, Hyperchem, Ovarian Cancer, PI3K, p110a, Python
 
4. Description Abstract

PI3K (Phosphoinositid-3-Kinase) is the mostly used protein as a target for the ovarian cancer. Ovarian cancer is very deadly disease in mostly women. PI3K have three subunit classes such as p110a, p110 beta, p110g which plays very important role in the development in ovarian cancer. P110a is mostly responsible in sever ovarian cancer among all three classes of PI3K. We worked to find the best possible inhibitors for p110a of PI3K. Crystal structure of p110a subunit PI3K, which has no complex with any other molecule taken from structural database (PDB). In-Silico drug designing approaches follow for molecular docking studies using AutoDock 3.05. The docked complexes were validated and enumerated based on the AutoDock Scoring function to pick out the best inhibitors based on docked Energy. Thus from the entire 70 ligand compounds which were Docked, we got 5 best derivatives of pyrazolopyrimidine with optimal docked Energy (pyrazolo pyrimidine, 5a: -22.64 kcal/mol; pyrazolo pyrimidine, 13: -21.43kcal/mol; pyrazolo pyrimidine, 5e: -21.88kcal/mol; pyrazolo pyrimidine, 10: -18.77kcal/mol, pyrazolo pyrimidine, 25:-16.5kcal/mol). Further the five best-docked complexes were analyzed through Python Molecular Viewer software for their interaction studies.

 
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2012-12-26
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://medical.cloud-journals.com/index.php/IJABCB/article/view/Med-30
11. Source Journal/conference title; vol., no. (year) International Journal of Advanced Bioinformatics and Computational Biology; Published Papers
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
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