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Molecular Modeling and Docking Analysis of Novel Drug like Compounds for NDM-1

IJCA Proceedings on National Seminar on Application of Artificial Intelligence in Life Sciences 2013
© 2013 by IJCA Journal
NSAAILS - Number 1
Year of Publication: 2013
Amrit Jagyasi
Jyotsna Choubey
Ashish Patel
M. K. Verma

Amrit Jagyasi, Jyotsna Choubey, Ashish Patel and M K Verma. Article: Molecular Modeling and Docking Analysis of Novel Drug like Compounds for NDM-1. IJCA Proceedings on National Seminar on Application of Artificial Intelligence in Life Sciences 2013 NSAAILS(1):47-54, February 2013. Full text available. BibTeX

	author = {Amrit Jagyasi and Jyotsna Choubey and Ashish Patel and M. K. Verma},
	title = {Article: Molecular Modeling and Docking Analysis of Novel Drug like Compounds for NDM-1},
	journal = {IJCA Proceedings on National Seminar on Application of Artificial Intelligence in Life Sciences 2013},
	year = {2013},
	volume = {NSAAILS},
	number = {1},
	pages = {47-54},
	month = {February},
	note = {Full text available}


NDM-1 (New Delhi metallo-?-lactamase 1) is an enzyme that is carried in certain gram negative bacteria like E. coli and Klebsiella, and makes the bacterium resistant to the beta lactam antibiotics, including carbapenems, with the exception of the monobactam agent, aztreonam. Beta-lactamase is also known as carbapenemases, due to its resistance towards carbapenem antibiotics. Resistance to ? –lactam antibiotics mediated by metallo-?-lactamases is an increasingly worrying clinical problem. NDM-1 has been found in several clinically important carbapenem-resistant pathogens, there is a need for inhibitors of this enzyme that could protect broad spectrum antibiotics from hydrolysis and thus extend their utility. In the presented research, the 3D structure of NDM-1 protein was modeled using homology modeling by Modeller9v8. Evaluation of the constructed model is done by PROCHECK, PROSA, ERRAT and Verify3d servers. DEPTH server is used to predict active sites of Protein. Pubchem and ChEMBL, Drug Bank, and SuperNatural databases is used to find novel compounds. These compounds were dokced with the modeled structure, and those showing least Binding Energy were selected. These final compounds were then tested among Online Validation Servers (Molinspiration, and OSIRIS) for Drug Likeness. Also they were validated using ADMET descriptors protocol of Accelrys Discovery Studio.


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