Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Yun-De Xiao"'
Autor:
Terry Hauser, Kristen G. Jordan, Yun-De Xiao, Patrick M. Lippiello, Merouane Bencherif, John W. James, Jason Speake, Sharon R. Letchworth, Jiahui Zhang, Mazurov Anatoly A, Phil S. Hammond, Katherine M. Van Dyke
Publikováno v:
European Journal of Pharmaceutical Sciences. 47:813-823
Nicotinic α4β2* agonists are known to be effective in a variety of preclinical pain models, but the underlying mechanisms of analgesic action are not well-understood. In the present study, we characterized activation and desensitization properties
Autor:
Dull Gary Maurice, John Genus, Anatoly A. Mazurov, Serguei S. Sidach, Daniel Yohannes, Yun-De Xiao, Terry Hauser, Fedorov Nikolai, John W. James, Benson Lisa, Philip S. Hammond, Miller Craig H, Lan Miao, David C. Kombo
Publikováno v:
Journal of Medicinal Chemistry. 55:9793-9809
(2S,3R)-N-[2-(Pyridin-3-ylmethyl)-1-azabicyclo[2.2.2]oct-3-yl]benzo[b]furan-2-carboxamide (7a, TC-5619), a novel selective agonist of the α7 neuronal nicotinic acetylcholine receptor, has been identified as a promising drug candidate for the treatme
Autor:
Jason Speake, Lan Miao, Jenny Z. Zhang, Gatto Gregory J, Philip S. Hammond, Srinivasa Rao Akireddy, Daniel Yohannes, Mazurov Anatoly A, Murthy Srinivasa, David C. Kombo, Kristen G. Jordan, Bhatti Balwinder Singh, Jon-Paul Strachan, Terry Hauser, Miller Craig H, Yun-De Xiao
Publikováno v:
Journal of Medicinal Chemistry. 55:9181-9194
Diversification of essential nicotinic cholinergic pharmacophoric elements, i.e., cationic center and hydrogen bond acceptor, resulted in the discovery of novel potent α4β2 nAChR selective agonists comprising a series of N-acyldiazabicycles. Core c
Publikováno v:
Journal of Chemical Information and Modeling. 46:137-144
The modeling of nonlinear descriptor-target relationships is a topic of considerable interest in drug discovery. We, herein, continue reporting the use of the self-organizing map-a nonlinear, topology-preserving pattern recognition technique that exh
Autor:
Aaron Clauset, Jeffrey Daniel Schmitt, Ersin Bayram, Yun-De Xiao, Peter Santago, Rebecca Harris
Publikováno v:
Journal of Chemical Information and Modeling. 45:1749-1758
The utility of the supervised Kohonen self-organizing map was assessed and compared to several statistical methods used in QSAR analysis. The self-organizing map (SOM) describes a family of nonlinear, topology preserving mapping methods with attribut
Publikováno v:
Journal of Molecular Graphics and Modelling. 23:129-138
We have employed in parallel the Catalyst HypoGen pharmacophore modeling approach and the variable selection k -nearest neighbor quantitative structure–activity relationship ( k NN QSAR) method to model a diverse data set of p38 mitogen-activated p
Publikováno v:
Journal of Computer-Aided Molecular Design. 18:483-493
Modeling non-linear descriptor-target activity/property relationships with many dependent descriptors has been a long-standing challenge in the design of biologically active molecules. In an effort to address this problem, we couple the supervised se
Publikováno v:
Journal of Computer-Aided Molecular Design. 17:241-253
Quantitative Structure–Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model valid
Autor:
Grzegorz Chałasiński, Alexei A. Buchachenko, M. M. Szczȩśniak, Larry A. Viehland, Roman V. Krems, Yun-De Xiao
Publikováno v:
The Journal of Chemical Physics. 114:9919-9928
Highly accurate ab initio coupled cluster theory calculations, with single, double and noniterative triple excitations [CCSD(T)], and with the extended basis set augmented by the bond functions, were performed for the interactions of chlorine atom an
Autor:
Alexander, Golbraikh, Min, Shen, Zhiyan, Xiao, Yun-De, Xiao, Kuo-Hsiung, Lee, Alexander, Tropsha
Publikováno v:
Journal of computer-aided molecular design. 17(2-4)
Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validat