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This chapter defines computer-aided drug design (CADD), its role in drug discovery, and the personnel and computer resources that it requires. Some mention is made of its role in development as well as in biotechnology. The techniques and science that constitute this field will be only briefly discussed; a more thorough description is left to the references. The references cited here have been chosen to reflect the generality of this volume. Specific references to more detailed, technical literature can be found within these references. |
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Of course, computers are used in all data and instrument related areas of science and chemistry. In this chapter, however, we will not attempt to discuss and critique such wide-spread methods as statistics, curve fitting, and data management, but rather will discuss those areas of computational chemistry and biophysics that are specialties unto themselves and that are now routinely applied by research scientists primarily to the drug discovery phase of pharmaceutical R & D. These methods help medicinal chemists, biochemists, and molecular biologists to understand the atomic-level events involved in drug action and provide guidance in the design of new drugs. The methods are often broadly labeled as structure-activity relationships, molecular modeling, or rational drug design. |
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Computer-aided drug design is difficult to define because, in actuality it encompasses many different fields with the commonality that the experiments and science are done on the computer, not in the laboratory, and the tools are not spectrometers and test tubes but chemical, physical, and biological theory as implemented by computer software. These fields include computer graphics, 3-dimensional models of molecules (molecular modeling), protein structure prediction and analysis, molecular motion (molecular dynamics simulation), molecular shape (conformational analysis), molecular property prediction, quantitative structure/property relationships (QSPR), structure-activity relationships (SAR; applied statistics, pattern recognition, and neural networks), database search, quantum chemistry (for predicting structure, properties, and reactivity), computer-assisted synthesis, protein/drug docking, as well as others. Although many of these fields are related and overlap substantially, their size, scope, and intensity dictate that they embody several distinct specialties. For example, typically an expert in protein structure prediction is not also an expert in quantum chemistry. Also, the field of force field development (for molecular modeling) is so intense that typically an expert in this field will not be expert also in SAR studies. |
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