3-(morpholin-4-yl)-1-(3,4,5-trimethoxyphenyl)propan-1-one hydrochloride | 6269-86-9

• 分子结构分类: 有机化合物 - 有机氧化合物
• 英文名称: 3-(morpholin-4-yl)-1-(3,4,5-trimethoxyphenyl)propan-1-one hydrochloride
• 英文别名: 3-Morpholin-4-yl-1-(3,4,5-trimethoxyphenyl)propan-1-one;hydrochloride
• CAS: 6269-86-9
• 化学式: C₁₆H₂₃NO₅*ClH
• 分子量: 345.823
• InChiKey: KNXACQWTYHFWHI-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  2.04
• 重原子数：
  23
• 可旋转键数：
  7
• 环数：
  2.0
• sp3杂化的碳原子比例：
  0.56
• 拓扑面积：
  57.2
• 氢给体数：
  1
• 氢受体数：
  6

反应信息

• 作为产物：
  描述：

  聚合甲醛 、 3',4',5'-三甲氧基苯乙酮 、 吗啡啉盐酸盐 在 盐酸 作用下， 以 乙醇 为溶剂， 反应 7.0h， 生成 3-(morpholin-4-yl)-1-(3,4,5-trimethoxyphenyl)propan-1-one hydrochloride
  参考文献：
  名称：

  3D QSAR study of hypolipidemic asarones by comparative molecular surface analysis

  摘要：

  Three-dimensional quantitative structure-activity relationship (3D QSAR) modeled for alpha-asarone derivatives using the comparative molecular surface analysis (CoMSA) allowed us to reveal a correlation between the activity of these compounds and the electrostatic potential at the molecular surface. The grid formalism (s-CoMSA) allowed us to indicate a pharmacophore that is of key importance for compound activity. The CoMSA formalism coupled with the iterative variable elimination method gives a highly predictive model. (c) 2005 Elsevier Ltd. All rights reserved.

  DOI：

  10.1016/j.bmc.2005.10.014

文献信息

• 3D QSAR study of hypolipidemic asarones by comparative molecular surface analysis
  作者：Tomasz Magdziarz、Bozena Łozowicka、Rafał Gieleciak、Andrzej Bąk、Jarosław Polański、Zdzisław Chilmonczyk

  DOI：10.1016/j.bmc.2005.10.014

  日期：2006.3

  Three-dimensional quantitative structure-activity relationship (3D QSAR) modeled for alpha-asarone derivatives using the comparative molecular surface analysis (CoMSA) allowed us to reveal a correlation between the activity of these compounds and the electrostatic potential at the molecular surface. The grid formalism (s-CoMSA) allowed us to indicate a pharmacophore that is of key importance for compound activity. The CoMSA formalism coupled with the iterative variable elimination method gives a highly predictive model. (c) 2005 Elsevier Ltd. All rights reserved.