Gasteiger Johann
Computer-Chemie-Centrum and Institute of Organic Chemistry, University of Erlangen-Nuremberg, Nägelsbachstrasse 25, 91052 Erlangen, Germany.
Mini Rev Med Chem. 2003 Dec;3(8):789-96. doi: 10.2174/1389557033487656.
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.
在确定生物学靶点后,药物设计旨在分析潜在配体的结构与其生物活性之间的关系。本文提出了一种结构表示层次体系,该体系考虑了分子的组成、其三维结构或分子表面。在每个层次上,都可以考虑各种物理化学效应。此外,还考虑了学习算法(如神经网络)的特殊要求。文中给出了其在组合化学、先导物识别、高通量筛选以及ADME-Tox性质预测等问题中的应用。