Structure-based classification of chemical reactions without assignment of reaction centers
Structure-based classification of chemical reactions without assignment of reaction centers
复制标题
基于结构的化学反应分类，无需指定反应中心
DOI：
10.1021/ci0502707
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发表时间：
2005-11-01
影响因子：
5.6
通讯作者：
Aires-de-Sousa, J
中科院分区：
文献类型：
--
作者：
Zhang, QY;Aires-de-Sousa, J
化学反应的自动分类对于反应数据库分析、反应检索、反应预测或合成规划非常重要。在这项工作中，研究了光化学反应的分类，但没有明确指定反应中心。使用不同级别的信息，在三种不同的情况下使用随机森林或 Kohonen 神经网络探索分类：（a）根据反应物产生的反应类型对反应物进行分类，（b）根据合成反应物的反应类型对产物进行分类，（c）根据产物描述符和反应物描述符之间的差异对反应进行分类。适合所有情况原子级属性的分子图（MOLMAP）被用作描述符。它们由自组织图生成，并编码分子中可用键的物理化学性质。所有独立测试集中的 78 个动作中，大约 90% 可以实现正确分类。
The automatic classification of chemical reactions is of high importance for the analysis of reaction databases, reaction retrieval, reaction prediction, or synthesis planning. In this work, the classification of photochemical reactions was investigated with no explicit assignment of the reacting centers. Classifications were explored with Random Forests or Kohonen neural networks in three different situations, using different levels of information: (a) pairs of reactants were classified according to the type of reaction they produce, (b) products, were classified according to the type of reaction from which they can be synthesized, and (c) reactions were classified from the difference between the descriptors of the product and the descriptors of the reactants. fit all cases Molecular maps of atom-level properties (MOLMAPs) were Used as descriptors. They are generated by a self-organizing map and encode physicochemical properties of the bonds available in a molecule. Correct classification could be achieved for approximately 90% of the 78 actions in all independent test set.