Optimising the EVA descriptor for prediction of biological activity.
EVA is a multivariate molecular descriptor for use in QSAR studies. It is constructed from vibrational eigenvalues derived from either a quantum theoretical or molecular mechanical treatment of molecular structure. This paper applies the method to biological-activity data using measures of the inotropic potential of a range of Calcium channel agonists. The performance of the descriptor, as both an explanatory and a predictive tool, is analysed in relation to the way in which it is constructed using a rigorous statistical treatment. Its capabilities are examined in relation to those of previously published methodology which used a composite descriptor. It is shown to have improved performance and several procedural advantages, such as ease of calculation and operation. It is a 3-D structural descriptor which does not require prior co-alignment of structures for a QSAR study.
Ford
Martyn
M
Centre for Molecular Design, IBBS, University of Portsmouth, King Henry Building, King Henry I Street, Portsmouth, Hampshire PO1 2DY, UK. martyn.ford@port.ac.uk
Phillips
Laurie
L
Stevens
Adrian
A
D001498:3-Pyridinecarboxylic acid, 1,4-dihydro-2,6-dimethyl-5-nitro-4-(2-(trifluoromethyl)phenyl)-, Methyl ester / Q000737:chemistry / Q000494:pharmacology; D000465:Algorithms; D002120:Calcium Channel Agonists / Q000737:chemistry* / Q000494:pharmacology*; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D015999:Multivariate Analysis; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
D002120:Calcium Channel Agonists; D001498:3-Pyridinecarboxylic acid, 1,4-dihydro-2,6-dimethyl-5-nitro-4-(2-(trifluoromethyl)phenyl)-, Methyl ester