A new descriptor of molecular structure, EVA, for use in the derivation of robustly predictive QSAR relationships is described. It is based on theoretically derived normal coordinate frequencies, and has been used extensively and successfully in proprietary chemical discovery programmes within Shell Research. As a result of informal dissemination of the methodology, it is now being used successfully in related areas such as pharmaceutical drug discovery. Much of the experimental data used in development remain proprietary, and are not available for publication. This paper describes the method and illustrates its application to the calculation of nonproprietary data, log P(ow), in both explanatory and predictive modes. It will be followed by other publications illustrating its application to a range of data derived from biological systems.

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.