1-(4-Bromophenyl)-2-[[5-(3,4,5-trimethoxyphenyl)-1,3,4-oxadiazol-2-yl]sulfanyl]ethanone | 110767-46-9

• 分子结构分类: 有机化合物 - 有机氧化合物
• 英文名称: 1-(4-Bromophenyl)-2-[[5-(3,4,5-trimethoxyphenyl)-1,3,4-oxadiazol-2-yl]sulfanyl]ethanone
• CAS: 110767-46-9
• 化学式: C₁₉H₁₇BrN₂O₅S
• 分子量: 465.324
• InChiKey: SKLOLKUMVZDDAD-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  4.3
• 重原子数：
  28
• 可旋转键数：
  8
• 环数：
  3.0
• sp3杂化的碳原子比例：
  0.21
• 拓扑面积：
  109
• 氢给体数：
  0
• 氢受体数：
  8

反应信息

• 作为反应物：
  描述：

  1-(4-Bromophenyl)-2-[[5-(3,4,5-trimethoxyphenyl)-1,3,4-oxadiazol-2-yl]sulfanyl]ethanone 在 一水合肼 作用下， 以 溶剂黄146 为溶剂， 反应 2.5h， 生成 6-(4-bromophenyl)-3-(3,4,5-trimethoxyphenyl)-7H-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazine
  参考文献：
  名称：

  Mazzone; Bonina; Panico, Farmaco, Edizione Scientifica, 1987, vol. 42, # 7, p. 525 - 539

  摘要：

  DOI：
• 作为产物：
  描述：

  3,4,5-三甲氧基苯甲酰肼 以 N,N-二甲基甲酰胺 、 丙酮 为溶剂， 反应 1.0h， 生成 1-(4-Bromophenyl)-2-[[5-(3,4,5-trimethoxyphenyl)-1,3,4-oxadiazol-2-yl]sulfanyl]ethanone
  参考文献：
  名称：

  Synthesis of novel 5-aryl-2-thio-1,3,4-oxadiazoles and the study of their structure–anti-mycobacterial activities

  摘要：

  The preparation of novel 5-aryt-2-thio-1,3,4-oxadiazoles 4a 41 and the computer-aided study of their in vitro anti-tubercular activity against Myeobacterium tuberculosis H(37)Rv (ATCC 27294) are reported. The average accuracy of the electronic-topological method and neural network methods applied to the activity prediction in leave-one-out cross validation is 80%. (c) 2005 Elsevier Ltd. All rights reserved.

  DOI：

  10.1016/j.bmc.2005.05.011

文献信息

• Synthesis of novel 5-aryl-2-thio-1,3,4-oxadiazoles and the study of their structure–anti-mycobacterial activities
  作者：Fliur Macaev、Ghenadie Rusu、Serghei Pogrebnoi、Alexandru Gudima、Eugenia Stingaci、Ludmila Vlad、Nathaly Shvets、Fatma Kandemirli、Anatholy Dimoglo、Robert Reynolds

  DOI：10.1016/j.bmc.2005.05.011

  日期：2005.8

  The preparation of novel 5-aryt-2-thio-1,3,4-oxadiazoles 4a 41 and the computer-aided study of their in vitro anti-tubercular activity against Myeobacterium tuberculosis H(37)Rv (ATCC 27294) are reported. The average accuracy of the electronic-topological method and neural network methods applied to the activity prediction in leave-one-out cross validation is 80%. (c) 2005 Elsevier Ltd. All rights reserved.
• Mazzone; Bonina; Panico, Farmaco, Edizione Scientifica, 1987, vol. 42, # 7, p. 525 - 539
  作者：Mazzone、Bonina、Panico、Amico-Roxas、Caruso、Blandino、Vanella

  DOI：——

  日期：——