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    • 10. 发明申请
    • Method for generating a hierarchical topological tree of 2D or 3D-structural formulas of chemical compounds for property optimisation of chemical compounds
    • 用于生成用于化学化合物性质优化的化合物的2D或3D结构式的分层拓扑树的方法
    • US20070043511A1
    • 2007-02-22
    • US11588894
    • 2006-10-27
    • Axel JensenStefan Seidler
    • Axel JensenStefan Seidler
    • G06F19/00
    • G16C20/80
    • The invention concerns a new method for automatically and dynamically generating hierarchical topological trees of 2D- or 3D-structural formulas for structurally characterized chemical compounds, especially drug-like molecules, wherein the molecular graph of each 2D- or 3D-structure for a chemical compound is analyzed in terms of topological key features, the Largest Topological Substructure (LTS) and the proper Topological Cluster Centre (TCC) are created for each molecular graph, the ranking of the classes of topological key features and/or the ranking within each class of topological key features present in the TCC is used to generate a connected hierarchical Topological Sequence Path (TSP) of sentinel molecules from each molecular graph, and different molecular graphs and their Topological Sequence Paths (TSPs) share common vertices for common topological key features thus growing a Topological Structure Tree (TST), each chemical compound from the input stream is attached as a leaf node to the appropriate Largest Topological Substructure (LTS) node in the tree.
    • 本发明涉及用于自动和动态地生成用于结构特征化学化合物,特别是药物样分子的2D或3D结构式的分层拓扑树的新方法,其中化学化合物的每个2D或3D结构的分子图 根据拓扑关键特征进行分析,为每个分子图创建最大拓扑结构(LTS)和适当的拓扑聚类中心(TCC),拓扑关键特征类别和/或每类分类中的排名 TCC中存在的拓扑关键特征用于从每个分子图生成前哨分子的连接分层拓扑序列路径(TSP),并且不同的分子图及其拓扑序列路径(TSP)共享常见的拓扑关键特征的常见顶点,从而增长 拓扑结构树(TST),来自输入流的每种化合物作为叶子附着 节点到树中适当的最大拓扑子结构(LTS)节点。