Bauknecht H, Zell A, Bayer H, Levi P, Wagener M, Sadowski J, Gasteiger J
Institut für Parallele und Verteilte Höchstleistungsrechner (IPVR), Universität Stuttgart, Germany.
J Chem Inf Comput Sci. 1996 Nov-Dec;36(6):1205-13. doi: 10.1021/ci960346m.
Electronic properties located on the atoms of a molecule such as partial atomic charges as well as electronegativity and polarizability values are encoded by an autocorrelation vector accounting for the constitution of a molecule. This encoding procedure is able to distinguish between compounds being dopamine agonists and those being benzodiazepine receptor agonists even after projection into a two-dimensional self-organizing network. The two types of compounds can still be distinguished if they are buried in a dataset of 8323 compounds of a chemical supplier catalog comprising a wide structural variety. The maps obtained by this sequence of events, calculation of empirical physicochemical effects, encoding in a topological autocorrelation vector, and projection by a self-organizing neural network, can thus be used for searching for structural similarity, and, in particular, for finding new lead structures with biological activity.
位于分子原子上的电子性质，如部分原子电荷以及电负性和极化率值，由考虑分子组成的自相关向量进行编码。即使投影到二维自组织网络中，这种编码过程也能够区分多巴胺激动剂化合物和苯二氮䓬受体激动剂化合物。如果将这两类化合物埋没于包含广泛结构种类的化学供应商目录的8323种化合物的数据集中，它们仍然可以被区分。通过这一系列事件获得的图谱，即经验物理化学效应的计算、拓扑自相关向量中的编码以及自组织神经网络的投影，因此可用于搜索结构相似性，特别是用于寻找具有生物活性的新先导结构。
