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 Pow, 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.

Using a data set for 39 base oils, formulated oil products and pure compounds it was demonstrated that there was a good positive relationship between biodegradation in CEC L-33-T-82 and mineralisation to CO2 in the modified Sturm test. A mathematical model was developed which described this correlation for most of the materials tested. One outlier from the model was di-iso tridecyl adipate (DITA), the well-degradable calibration oil for the CEC test. The measured mineralisation of DITA was much lower than that predicted by the model based on the compound's high biodegradability in the CEC test. A possible reason for this is given and the implications of this result discussed.