11-Methyl-10,10-dioxobenzo[d][1,6,2]benzodithiazocin-12-one

• 分子结构分类: 有机化合物 - 有机硫化合物 - 硫醚类
• 英文名称: 11-Methyl-10,10-dioxobenzo[d][1,6,2]benzodithiazocin-12-one
• 化学式: C₁₄H₁₁NO₃S₂
• 分子量: 305.4
• InChiKey: IIGQXFXJZBHMCS-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  2.7
• 重原子数：
  20
• 可旋转键数：
  0
• 环数：
  3.0
• sp3杂化的碳原子比例：
  0.07
• 拓扑面积：
  88.1
• 氢给体数：
  0
• 氢受体数：
  4

文献信息

• METHOD OF SEARCHING FOR LIGAND
  申请人：Astellas Pharma Inc.

  公开号：EP2065818A1

  公开（公告）日：2009-06-03

  Disclosed is a method of searching for a ligand capable of binding to a target biomacromolecule, comprising the step of: (1) subjecting a number of low-molecular compounds to docking simulation, based on three-dimensional structural data concerning the low-molecular compounds and three-dimensional structural data concerning a ligand-binding region of the target biomacromolecule, to calculate a docking score for each of the low-molecular compounds, and simultaneously acquire three-dimensional positional data which enable each of the low-molecular compounds to stably bind within the ligand-binding region, (2) acquiring, from among the three-dimensional positional data obtained, all three-dimensional positional data concerning one or more molecular fragments, with respect to each of low-molecular compounds belonging to a higher group based on docking scores, (3) counting the three-dimensional positional data concerning each molecular fragment obtained, for each of the molecular fragments, (4) selecting the type and the three-dimensional positional data of a molecular fragment which shows a localization tendency, based on the counting data, and (5) selecting one or more molecular fragments from among characteristic molecular fragments determined, and determining a compound which satisfies the characteristic molecular fragments.

  本发明公开了一种寻找能够与目标生物大分子结合的配体的方法，包括以下步骤： (1) 根据低分子化合物的三维结构数据和目标生物大分子配体结合区域的三维结构数据，对若干低分子化合物进行对接模拟，计算出每种低分子化合物的对接得分，同时获取使每种低分子化合物能够在配体结合区域内稳定结合的三维位置数据、 (2) 从获得的三维位置数据中，根据对接得分，获取与属于较高分组的每个低分子化合物有关的一个或多个分子片段的所有三维位置数据、 (3) 针对每个分子片段，对所获得的每个分子片段的三维位置数据进行统计、 (4) 根据计数数据，选择有定位趋势的分子片段的类型和三维位置数据，以及 (5) 从确定的特征分子片段中选择一个或多个分子片段，并确定符合特征分子片段的化合物。