tert-butyl 4-(6-amino-5-chloropyrimidin-4-yl)piperazine-1-carboxylate | 1578262-46-0

• 分子结构分类: 有机化合物 - 有机杂环化合物 - 二嗪烷类
• 英文名称: tert-butyl 4-(6-amino-5-chloropyrimidin-4-yl)piperazine-1-carboxylate
• 英文别名: Tert-butyl 4-(6-amino-5-chloropyrimidin-4-yl)piperazine-1-carboxylate
• CAS: 1578262-46-0
• 化学式: C₁₃H₂₀ClN₅O₂
• 分子量: 313.787
• InChiKey: TUHNTQRWFUBLST-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  1.6
• 重原子数：
  21
• 可旋转键数：
  3
• 环数：
  2.0
• sp3杂化的碳原子比例：
  0.62
• 拓扑面积：
  84.6
• 氢给体数：
  1
• 氢受体数：
  6

反应信息

• 作为反应物：
  描述：

  tert-butyl 4-(6-amino-5-chloropyrimidin-4-yl)piperazine-1-carboxylate 在 三氟乙酸 作用下， 以 二氯甲烷 为溶剂， 反应 3.0h， 以95%的产率得到5-chloro-6-(piperazin-1-yl)pyrimidin-4-amine
  参考文献：
  名称：

  Integrating docking scores, interaction profiles and molecular descriptors to improve the accuracy of molecular docking: Toward the discovery of novel Akt1 inhibitors

  摘要：

  A set of forty-seven Akt1 inhibitors was used for the development of molecular docking based QSAR model by using nonlinear regression. The integration of docking scores, key interaction profiles and molecular descriptors remarkably improved the accuracy of the QSAR models, providing reasonable statistical parameters (R-train(2) = 0.948, R-test(2) = 0.907 and Q(cv)(2) = 0.794). The established MD-SVR model based structural modification of new 4-amino-pyrimidine derivatives was further performed, and six compounds 56a,b and 60a-d with good prediction activities were synthesized and biologically evaluated. All of these compounds exhibited promising Akt1 inhibitory and antiproliferative activities, suggesting the reliability and good application value of the established MD-SVR model in the development of Akt1 inhibitors. (C) 2014 Elsevier Masson SAS. All rights reserved.

  DOI：

  10.1016/j.ejmech.2014.01.019
• 作为产物：
  描述：

  1-Boc-4-(6-氨基嘧啶-4-基)哌嗪 在 N-氯代丁二酰亚胺 作用下， 以 四氢呋喃 为溶剂， 反应 5.0h， 以81%的产率得到tert-butyl 4-(6-amino-5-chloropyrimidin-4-yl)piperazine-1-carboxylate
  参考文献：
  名称：

  Integrating docking scores, interaction profiles and molecular descriptors to improve the accuracy of molecular docking: Toward the discovery of novel Akt1 inhibitors

  摘要：

  A set of forty-seven Akt1 inhibitors was used for the development of molecular docking based QSAR model by using nonlinear regression. The integration of docking scores, key interaction profiles and molecular descriptors remarkably improved the accuracy of the QSAR models, providing reasonable statistical parameters (R-train(2) = 0.948, R-test(2) = 0.907 and Q(cv)(2) = 0.794). The established MD-SVR model based structural modification of new 4-amino-pyrimidine derivatives was further performed, and six compounds 56a,b and 60a-d with good prediction activities were synthesized and biologically evaluated. All of these compounds exhibited promising Akt1 inhibitory and antiproliferative activities, suggesting the reliability and good application value of the established MD-SVR model in the development of Akt1 inhibitors. (C) 2014 Elsevier Masson SAS. All rights reserved.

  DOI：

  10.1016/j.ejmech.2014.01.019

文献信息

• Integrating docking scores, interaction profiles and molecular descriptors to improve the accuracy of molecular docking: Toward the discovery of novel Akt1 inhibitors
  作者：Wenhu Zhan、Daqiang Li、Jinxin Che、Liangren Zhang、Bo Yang、Yongzhou Hu、Tao Liu、Xiaowu Dong

  DOI：10.1016/j.ejmech.2014.01.019

  日期：2014.3

  A set of forty-seven Akt1 inhibitors was used for the development of molecular docking based QSAR model by using nonlinear regression. The integration of docking scores, key interaction profiles and molecular descriptors remarkably improved the accuracy of the QSAR models, providing reasonable statistical parameters (R-train(2) = 0.948, R-test(2) = 0.907 and Q(cv)(2) = 0.794). The established MD-SVR model based structural modification of new 4-amino-pyrimidine derivatives was further performed, and six compounds 56a,b and 60a-d with good prediction activities were synthesized and biologically evaluated. All of these compounds exhibited promising Akt1 inhibitory and antiproliferative activities, suggesting the reliability and good application value of the established MD-SVR model in the development of Akt1 inhibitors. (C) 2014 Elsevier Masson SAS. All rights reserved.