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Ever since Rachel Carson's Silent Spring, we have generally become aware of environmental contaminants and their effects on the ecosystem. The findin~ of PCB's in fish by Soren Jensen in Sweden, the recognition of mirex as contaminant in fish from Lake Ontario, and the discoveries of contaminant laden leachates from dumpsites such as the Love Canal have become milestones in the search for and charac terization of contaminants in our environment. At this time, the problem no longer is so much the identifi cation of contaminants and their sources. Rather, we are now faced with solving questions on the fates and effects of such compounds. This includes the search for mechanisms to deal effectively with the large number of chemicals already found in water, air and biota. One of such time and cost saving scientific avenues is the field of quantitative structure-activity correlations for the prediction of the environmental behavior and effects of compounds.
This book discusses the different aspects and fields of application of QSAR, such as: # Statistical techniques and estimation of physico-chemical properties # Environmental fate processes # Toxicokinetic behaviour # Environmental toxicity and mechanism of action # Application of QSAR in practice Moreover, presentations are included which deal with the mechanistic aspects of environmental fate and toxicity. Experts from these different fields ensure the exchange of information which will stimulate the development of QSAR. Another objective is to bring together the expertise of people working in the fields of drug design and the environmental sciences, since the underlying processes that lead to the beneficial effects of drugs are the same as those that cause the adverse effects of environmental pollutants. This excellent volume reflects developments at the cutting edge of a rapidly developing field.
Over the past few years, research in the field of quantitative structure-activity relationships (QSAR) in chemistry, biology, pharmacology, toxicology, and environmental sciences has seen strong growth. New journals and books have appeared in each of these fields, however, the combination of QSAR and environmental sciences is still in its infancy. After the success of the Workshop on Quantitative Structure-Activity Relationships (QSAR) in Environmental Toxicology, held at McMaster University, Aug ust 16-18, 1983, with the proceedings publ ished in 1984 [QSA R in Environmental Toxicology, Kaiser, K. L. E. (Ed. ), D. Reidel Pub!. Co. , Dordrecht, 406 p. , ISBN 90-277 -1776-1], it was time to hold another workshop in 1986. Indeed, the response by the scientific community was excellent with over 50 participants from Canada, Germany, Great Britain, Hungary, India, Japan, The Netherlands, United States, and Yugoslavia. Moreover, both breadth and depth of papers given were significantly improved and the workshop discussions were intense and frank. Regrettably, the number of participants, number of papers given and submitted for these proceedings made it impossible to include the workshop discussions of these papers. However, several manuscripts were revised on the basis of these discussions and, therefore, do reflect this very interactive workshop. This volume presents the majority of papers given at the 2nd International Workshop on QSAR in Environmental Toxicology, held at McMaster University, June 9-13, 1986. Many of these papers contain primary, new scientific data, equations and results which will not appear elsewhere.
With numerous examples and more than 1,000 references, this book presents the most recent QSAR methods and illustrates their scope, advantages, and limitations. It offers extended comparisons of 2.5D methods in which the 3D information is masked by data preprocessing and emphasizes the synergy of various aspects of chemoinformatics, including neural networks, genetic algorithms, support vector machines, data mining, and pharmacophore detection. The authors include actual calculations of the thermodynamic cycle and free energy perturbations. They also present the basic principles of molecular modeling methods and recent statistical/mathematical approaches.