Details

Autor(en) / Beteiligte

• Hoffman, Brian
• Cho, Sung Jin
• Zheng, Weifan
• Wyrick, Steven
• Nichols, David E
• Mailman, Richard B
• Tropsha, Alexander

Titel

Quantitative Structure−Activity Relationship Modeling of Dopamine D1 Antagonists Using Comparative Molecular Field Analysis, Genetic Algorithms−Partial Least-Squares, and K Nearest Neighbor Methods

Ist Teil von

• Journal of medicinal chemistry, 1999-08, Vol.42 (17), p.3217-3226

Ort / Verlag

Washington, DC: American Chemical Society

Erscheinungsjahr

1999

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Several quantitative structure−activity relationship (QSAR) methods were applied to 29 chemically diverse D1 dopamine antagonists. In addition to conventional 3D comparative molecular field analysis (CoMFA), cross-validated R 2 guided region selection (q 2-GRS) CoMFA (see ref ) was employed, as were two novel variable selection QSAR methods recently developed in one of our laboratories. These latter methods included genetic algorithm−partial least squares (GA−PLS) and K nearest neighbor (KNN) procedures (see refs −4), which utilize 2D topological descriptors of chemical structures. Each QSAR approach resulted in a highly predictive model, with cross-validated R 2 (q 2) values of 0.57 for CoMFA, 0.54 for q 2-GRS, 0.73 for GA−PLS, and 0.79 for KNN. The success of all of the QSAR methods indicates the presence of an intrinsic structure−activity relationship in this group of compounds and affords more robust design and prediction of biological activities of novel D1 ligands.