%0 Journal Article %1 Michielan2008 %A Michielan, L. %A Bacilieri, M. %A Schiesaro, A. %A Bolcato, C. %A Pastorin, G. %A Spalluto, G. %A Cacciari, B. %A Klotz, K. N. %A Kaseda, C. %A Moro, S. %D 2008 %J J Chem Inf Model %K & *Models, *Quantitative *Sequence A2A/antagonists Acid Adenosine Amino Binding Homology, Humans Ligands Molecular Pyrazoles Pyrimidines Relationship Sites Structure-Activity Triazoles inhibitors/*chemistry Receptor %N 2 %P 350-63 %T Linear and nonlinear 3D-QSAR approaches in tandem with ligand-based homology modeling as a computational strategy to depict the pyrazolo-triazolo-pyrimidine antagonists binding site of the human adenosine A2A receptor %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18215030 %V 48 %X The integration of ligand- and structure-based strategies might sensitively increase the success of drug discovery process. We have recently described the application of Molecular Electrostatic Potential autocorrelated vectors (autoMEPs) in generating both linear (Partial Least-Square, PLS) and nonlinear (Response Surface Analysis, RSA) 3D-QSAR models to quantitatively predict the binding affinity of human adenosine A3 receptor antagonists. Moreover, we have also reported a novel GPCR modeling approach, called Ligand-Based Homology Modeling (LBHM), as a tool to simulate the conformational changes of the receptor induced by ligand binding. In the present study, the application of both linear and nonlinear 3D-QSAR methods and LBHM computational techniques has been used to depict the hypothetical antagonist binding site of the human adenosine A2A receptor. In particular, a collection of 127 known human A2A antagonists has been utilized to derive two 3D-QSAR models (autoMEPs/PLS&RSA). In parallel, using a rhodopsin-driven homology modeling approach, we have built a model of the human adenosine A2A receptor. Finally, 3D-QSAR and LBHM strategies have been utilized to predict the binding affinity of five new human A2A pyrazolo-triazolo-pyrimidine antagonists finding a good agreement between the theoretical and the experimental predictions.

@article{Michielan2008, abstract = {The integration of ligand- and structure-based strategies might sensitively increase the success of drug discovery process. We have recently described the application of Molecular Electrostatic Potential autocorrelated vectors (autoMEPs) in generating both linear (Partial Least-Square, PLS) and nonlinear (Response Surface Analysis, RSA) 3D-QSAR models to quantitatively predict the binding affinity of human adenosine A3 receptor antagonists. Moreover, we have also reported a novel GPCR modeling approach, called Ligand-Based Homology Modeling (LBHM), as a tool to simulate the conformational changes of the receptor induced by ligand binding. In the present study, the application of both linear and nonlinear 3D-QSAR methods and LBHM computational techniques has been used to depict the hypothetical antagonist binding site of the human adenosine A2A receptor. In particular, a collection of 127 known human A2A antagonists has been utilized to derive two 3D-QSAR models (autoMEPs/PLS&RSA). In parallel, using a rhodopsin-driven homology modeling approach, we have built a model of the human adenosine A2A receptor. Finally, 3D-QSAR and LBHM strategies have been utilized to predict the binding affinity of five new human A2A pyrazolo-triazolo-pyrimidine antagonists finding a good agreement between the theoretical and the experimental predictions.}, added-at = {2010-12-14T18:12:02.000+0100}, author = {Michielan, L. and Bacilieri, M. and Schiesaro, A. and Bolcato, C. and Pastorin, G. and Spalluto, G. and Cacciari, B. and Klotz, K. N. and Kaseda, C. and Moro, S.}, biburl = {https://www.bibsonomy.org/bibtex/2f064a29f6e54aaa8869a33ecc2b01940/pharmawuerz}, endnotereftype = {Journal Article}, interhash = {2e3864869a4335acb91d24dc0a1208fe}, intrahash = {f064a29f6e54aaa8869a33ecc2b01940}, issn = {1549-9596 (Print)}, journal = {J Chem Inf Model}, keywords = {& *Models, *Quantitative *Sequence A2A/antagonists Acid Adenosine Amino Binding Homology, Humans Ligands Molecular Pyrazoles Pyrimidines Relationship Sites Structure-Activity Triazoles inhibitors/*chemistry Receptor}, month = Feb, note = {Michielan, Lisa Bacilieri, Magdalena Schiesaro, Andrea Bolcato, Chiara Pastorin, Giorgia Spalluto, Giampiero Cacciari, Barbara Klotz, Karl Norbet Kaseda, Chosei Moro, Stefano Research Support, Non-U.S. Gov't United States Journal of chemical information and modeling J Chem Inf Model. 2008 Feb;48(2):350-63. Epub 2008 Jan 24.}, number = 2, pages = {350-63}, shorttitle = {Linear and nonlinear 3D-QSAR approaches in tandem with ligand-based homology modeling as a computational strategy to depict the pyrazolo-triazolo-pyrimidine antagonists binding site of the human adenosine A2A receptor}, timestamp = {2010-12-14T18:20:21.000+0100}, title = {Linear and nonlinear 3D-QSAR approaches in tandem with ligand-based homology modeling as a computational strategy to depict the pyrazolo-triazolo-pyrimidine antagonists binding site of the human adenosine A2A receptor}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18215030}, volume = 48, year = 2008 }