Novel and Potent NPY5 Receptor Antagonists Derived from Virtual Screening and Iterative Parallel Chemistry Design.

ChemInform ◽  
2005 ◽  
Vol 36 (29) ◽  
Author(s):  
Wolfgang Guba ◽  
Werner Neidhart ◽  
Matthias Nettekoven
Keyword(s):  
Virtual Screening ◽  
Receptor Antagonists ◽  
Npy5 Receptor

Ligand-Based Virtual Screening Using Tailored Ensembles: A Prioritization Tool for Dual A2A Adenosine Receptor Antagonists / Monoamine Oxidase B Inhibitors

2016 ◽  
Vol 22 (21) ◽  
pp. 3082-3096 ◽  
Author(s):  
Aliuska Morales Helguera ◽  
Yunierkis Perez-Castillo ◽  
M. Natália D.S. Cordeiro ◽  
Eduardo Tejera ◽  
César Paz-y-Miño ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Monoamine Oxidase ◽  
Adenosine Receptor ◽  
Monoamine Oxidase B ◽  
Receptor Antagonists ◽  
A2a Adenosine Receptor

Structure–activity relationship studies on 2-heteroaryl-4-arylimidazoles NPY5 receptor antagonists

2003 ◽  
Vol 13 (20) ◽  
pp. 3593-3596 ◽  
Author(s):  
Richard L. Elliott ◽  
Robert M. Oliver ◽  
Janet A. LaFlamme ◽  
Melissa L. Gillaspy ◽  
Marlys Hammond ◽  
...  
Keyword(s):  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Receptor Antagonists ◽  
Structure Activity ◽  
Npy5 Receptor

Discovery of cannabinoid-1 receptor antagonists by virtual screening

2010 ◽  
Vol 20 (17) ◽  
pp. 5130-5132 ◽  
Author(s):  
Gil Nam Lee ◽  
Kwang Rok Kim ◽  
Sung-Hoon Ahn ◽  
Myung Ae Bae ◽  
Nam Sook Kang
Keyword(s):  
Virtual Screening ◽  
Receptor Antagonists ◽  
Cannabinoid 1 Receptor

Identifying the structural features and diversifying the chemical domain of peripherally acting CB1 receptor antagonists using molecular modeling techniques

RSC Advances ◽  
2016 ◽  
Vol 6 (2) ◽  
pp. 1466-1483 ◽  
Author(s):  
Mayank Kumar Sharma ◽  
Prashant R. Murumkar ◽  
Guanglin Kuang ◽  
Yun Tang ◽  
Mange Ram Yadav
Keyword(s):  
Molecular Modeling ◽  
Virtual Screening ◽  
3D Qsar ◽  
Structural Features ◽  
Cb1 Receptor ◽  
Receptor Antagonists ◽  
Modeling Techniques ◽  
Qsar Models ◽  
Cb1 Receptor Antagonists

A four featured pharmacophore and predictive 3D-QSAR models were developed which were used for virtual screening of the Asinex database to get chemically diverse hits of peripherally active CB1 receptor antagonists.

First Pharmacophore Model of CCR3 Receptor Antagonists and its Homology Model-Assisted, Stepwise Virtual Screening

2011 ◽  
Vol 77 (5) ◽  
pp. 373-387 ◽  
Author(s):  
Vaibhav Jain ◽  
Parameswaran Saravanan ◽  
Akanksha Arvind ◽  
Chethampadi Gopi Mohan
Keyword(s):  
Virtual Screening ◽  
Pharmacophore Model ◽  
Homology Model ◽  
Receptor Antagonists

scholarly journals Virtual screening tailored ensembles of QSAR models for the discovery of dual A2A Adenosine Receptor Antagonists / Monoamine Oxidase B Inhibitors

2015 ◽  
Author(s):  
Fernanda Borges ◽  
Maykel Cruz-Monteagudo ◽  
Aliuska Morales-Helguera ◽  
Yunierkis Pérez-Castillo ◽  
M. Natália D. S. Cordeiro ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Monoamine Oxidase ◽  
Adenosine Receptor ◽  
Monoamine Oxidase B ◽  
Receptor Antagonists ◽  
Qsar Models

scholarly journals Identification of novel and structurally diverse N-Methyl-D-Aspartate Receptor Antagonists: Successful Application of Pharmacophore Modeling, Virtual Screening and Molecular Docking

2018 ◽  
Author(s):  
Mukta Sharma ◽  
Anupama Mittal ◽  
Aarti Singh ◽  
Ashwin K. Jainarayanan ◽  
Sarvesh Kumar Paliwal
Keyword(s):  
Hydrogen Bond ◽  
Molecular Docking ◽  
Nmda Receptor ◽  
Virtual Screening ◽  
Alzheimer Disease ◽  
Receptor Antagonist ◽  
In Silico ◽  
Nmda Receptor Antagonist ◽  
Receptor Antagonists ◽  
Hydrogen Bond Acceptor

ABSTRACTIn view of “excitotoxic” effects of glutamate, wherein excessive excitatory input causes increase in intracellular Ca2+ and ultimately cell death, NMDA receptor has emerged as an important target for treatment and prevention of several neurological disorders, like Alzheimer disease. Prompted by the successful application of in-silico pharmacophore-based virtual screening in lead identification, we have made an effort to implement in-silico protocols to identify novel NMDA receptor antagonist. A series of novel benzo[b]quinolizinium cations as NMDA receptor antagonists have been used as a starting point to develop prognostic pharmacophore models. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, one hydrogen bond acceptor, one hydrophobic and two ring aromatic, showed a correlation (r) of 0.89, root mean square of 0.259, and the cost difference of 43.01 bits between null and fixed cost. The model was thoroughly validated and subjected to a chemical database search, which lead to the identification of 400 hits from NCI and Maybridge databases which were checked for Lipinski’s violation and predictive potency.This reduced the list to 10 compounds, out of which, two most potent compounds were subjected to molecular docking using Libdock software and interestingly, all the docked conformations showed hydrogen bond interactions with important amino acids Tyr214, His88, Thr174, Val169 and Arg121. In summary, through our validated pharmacophore-based virtual screening protocol, we have identified two potent, structurally diverse, druggable and novel NMDA receptor antagonist which might be of great help to address the unmet medical need of Alzheimer disease.

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