Quantitative Structure−Activity Relationship Modeling of Dopamine D1Antagonists Using Comparative Molecular Field Analysis, Genetic Algorithms−Partial Least-Squares, and K Nearest Neighbor Methods

1999 ◽  
Vol 42 (17) ◽  
pp. 3217-3226 ◽  
Author(s):  
Brian Hoffman ◽  
Sung Jin Cho ◽  
Weifan Zheng ◽  
Steven Wyrick ◽  
David E. Nichols ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Least Squares ◽  
Partial Least Squares ◽  
Nearest Neighbor ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Comparative Molecular Field Analysis ◽  
Quantitative Structure ◽  
K Nearest Neighbor ◽  
Structure Activity

QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP MODELING FOR PREDICTION OF PYRIDINE SUBSTITUTED ANALOGUES WITH K-NEAREST NEIGHBOR STUDIES

INDIAN DRUGS ◽  
2017 ◽  
Vol 54 (10) ◽  
pp. 16-22
Author(s):  
M. C. Sharma ◽  
◽  
D.V. Kohli
Keyword(s):  
Correlation Coefficient ◽  
Quantitative Relationship ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Field Analysis ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Angiotensin Ii Receptor ◽  
K Nearest Neighbor ◽  
Structure Activity

A quantitative structure activity relationship study was performed on a series of imidazo[4,5-b]pyridine substituted compounds as angiotensin II receptor antagonists for establishing quantitative relationship between activity and their physicochemical properties. The best quantitative structure activity relationship model was generated with correlation coefficient of 0.8318, cross validated correlation coefficient of 0.7142 and r2 for external test set 0.7965. Molecular field analysis was used to construct the best 3D-QSAR model using PLS method, showing good correlative and predictive capabilities in terms of q2 = 0.7264 and pred_r2 = 0.8164. These results will be useful for the design of new antihypertensive molecules.

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