Tandem 3D-QSARs approach as a valuable tool to predict binding affinity data: design of new Gly/NMDA receptor antagonists as a key study.
Quantitative structure-activity relationships (QSARs) represent a very well consolidated computational approach to correlate structural or property descriptors of chemical compounds with their chemical or biological activities. We have recently reported that autocorrelation Molecular Electrostatic Potential (autoMEP) vectors in combination to Partial Least-Square (PLS) analysis or to Response Surface Analysis (RSA) can represent an interesting alternative 3D-QSAR strategy. In the present paper, we would like to present how the applicability of in tandem linear and nonlinear 3D-QSAR methods (autoMEP/PLS&RSA) can help to predict binding affinity data of a new set of N-methyl-d-aspartate (Gly/NMDA) receptor antagonists.
Bacilieri
M
M
Molecular Modeling Section, Department of Pharmaceutical Sciences, University of Padova, via Marzolo 5, I-35131 Padova, Italy.
Varano
F
F
Deflorian
F
F
Marini
M
M
Catarzi
D
D
Colotta
V
V
Filacchioni
G
G
Galli
A
A
Costagli
C
C
Kaseda
C
C
Moro
S
S
D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology; D003198:Computer Simulation; D015195:Drug Design; D004563:Electrochemistry; D018691:Excitatory Amino Acid Antagonists / Q000737:chemistry / Q000494:pharmacology*; D007202:Indicators and Reagents; D016018:Least-Squares Analysis; D016014:Linear Models; D009682:Magnetic Resonance Spectroscopy; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D021281:Quantitative Structure-Activity Relationship; D016194:Receptors, N-Methyl-D-Aspartate / Q000037:antagonists & inhibitors*
D018691:Excitatory Amino Acid Antagonists; D007202:Indicators and Reagents; D016194:Receptors, N-Methyl-D-Aspartate