After the identification of a biological target, drug design is to analyze the relationships between the structure of potential ligands and their biological activity. A hierarchy of structure representation is presented here considering either the constitution of a molecule, its 3D structure, or the molecular surface. At each level, a variety of physicochemical effects can be accounted for. Furthermore, the special requirements of learning algorithm, such as neural networks, are taken into consideration. Application to problems from combinatorial chemistry, lead identification, high-throughput screening, and prediction of ADME-Tox properties are given.
Keywords: constitution, 3d structure, conformational flexibility, molecular surfaces, charge distribution, neural networks, lead discovery, high-throughput screening
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