Prediction of Health and Environmental Hazards of Chemicals: A Hierarchical Approach using QMSA and QSAR (1997-2000)

Abstract

During the past few years we have been involved in the development of new computational methods for quantifying similarity/dissimilarity of chemicals and applications of quantitative molecular similarity analysis (QMSA) techniques in analog selection and property estimation for use in the hazard assessment of chemicals. We have also explored the mathematical nature of the molecular similarity space in order to better understand the basis of analog selection by QMSA methods. The parameter spaces used for QMSA and analog selection were constructed from nonempirical parameters derived from computational chemical graph theory. Occasionally, graph invariants were supplemented with geometrical parameters and quantum chemical indices to study the relative effectiveness of graph invariants vis-a-vis geometrical and quantum chemical parameters in analog selection and property estimation. We carried out comparative studies of nonempirical descriptor spaces and physicochemical property spaces (n selecting analogs. Molecular similarity methods were applied in predicting modes of toxic action (MOA) of chemicals. Our similarity/dissimilarity methods have also found successful applications in the discovery of new drug leads by US drug companies.