2-(pyrrolidin-1-yl)ethyl trifluoromethanesulfonate

• 分子结构分类: 有机化合物 - 有机酸及其衍生物 - 有机磺酸及其衍生物
• 英文名称: 2-(pyrrolidin-1-yl)ethyl trifluoromethanesulfonate
• 英文别名: 2-Pyrrolidin-1-ylethyl trifluoromethanesulfonate
• 化学式: C₇H₁₂F₃NO₃S
• 分子量: 247.238
• InChiKey: VMDWTUXDOCMYFP-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  1.4
• 重原子数：
  15
• 可旋转键数：
  4
• 环数：
  1.0
• sp3杂化的碳原子比例：
  1.0
• 拓扑面积：
  55
• 氢给体数：
  0
• 氢受体数：
  7

反应信息

• 作为反应物：
  描述：

  苯甲基苯胺 、 2-(pyrrolidin-1-yl)ethyl trifluoromethanesulfonate 在 sodium hydride 作用下， 以 甲苯 、 mineral oil 为溶剂， 以21%的产率得到希司吡定
  参考文献：
  名称：

  Flavin Monooxygenase Metabolism: Why Medicinal Chemists Should Matter

  摘要：

  FMO enzymes (FMOs) play a key role in the processes of detoxification and/or bioactivation of specific pharmaceuticals and xenobiotics bearing nucleophilic centers. The N-oxide and S-oxide metabolites produced by FMOs are often active metabolites. The FMOs are more active than cytochromes in the brain and work in tandem with CYP3A4 in the liver. FMOs might reduce the risk of phospholipidosis of CAD-like drugs, although some FMOs metabolites seem to be neurotoxic and hepatotoxic. However, in silico methods for FMO metabolism prediction are not yet available. This paper reports, for the first time, a substrate-specificity and catalytic-activity model for FMO3, the most relevant isoform of the FMOs in humans. The application of this model to a series of compounds with unknown FMO metabolism is also reported. The model has also been very useful to design compounds with optimal clearance and in finding erroneous literature data, particularly cases in which substances have been reported to be FMO3 substrates when, in reality, the experimentally validated in silico model correctly predicts that they are not.

  DOI：

  10.1021/jm5007098
• 作为产物：
  描述：

  N-(2-羟乙基)-吡咯烷 、 三氟甲磺酸酐 以 二氯甲烷 为溶剂， 反应 0.5h， 生成 2-(pyrrolidin-1-yl)ethyl trifluoromethanesulfonate
  参考文献：
  名称：

  Flavin Monooxygenase Metabolism: Why Medicinal Chemists Should Matter

  摘要：

  FMO enzymes (FMOs) play a key role in the processes of detoxification and/or bioactivation of specific pharmaceuticals and xenobiotics bearing nucleophilic centers. The N-oxide and S-oxide metabolites produced by FMOs are often active metabolites. The FMOs are more active than cytochromes in the brain and work in tandem with CYP3A4 in the liver. FMOs might reduce the risk of phospholipidosis of CAD-like drugs, although some FMOs metabolites seem to be neurotoxic and hepatotoxic. However, in silico methods for FMO metabolism prediction are not yet available. This paper reports, for the first time, a substrate-specificity and catalytic-activity model for FMO3, the most relevant isoform of the FMOs in humans. The application of this model to a series of compounds with unknown FMO metabolism is also reported. The model has also been very useful to design compounds with optimal clearance and in finding erroneous literature data, particularly cases in which substances have been reported to be FMO3 substrates when, in reality, the experimentally validated in silico model correctly predicts that they are not.

  DOI：

  10.1021/jm5007098

文献信息

• Flavin Monooxygenase Metabolism: Why Medicinal Chemists Should Matter
  作者：Gabriele Cruciani、Aurora Valeri、Laura Goracci、Roberto Maria Pellegrino、Federica Buonerba、Massimo Baroni

  DOI：10.1021/jm5007098

  日期：2014.7.24

  FMO enzymes (FMOs) play a key role in the processes of detoxification and/or bioactivation of specific pharmaceuticals and xenobiotics bearing nucleophilic centers. The N-oxide and S-oxide metabolites produced by FMOs are often active metabolites. The FMOs are more active than cytochromes in the brain and work in tandem with CYP3A4 in the liver. FMOs might reduce the risk of phospholipidosis of CAD-like drugs, although some FMOs metabolites seem to be neurotoxic and hepatotoxic. However, in silico methods for FMO metabolism prediction are not yet available. This paper reports, for the first time, a substrate-specificity and catalytic-activity model for FMO3, the most relevant isoform of the FMOs in humans. The application of this model to a series of compounds with unknown FMO metabolism is also reported. The model has also been very useful to design compounds with optimal clearance and in finding erroneous literature data, particularly cases in which substances have been reported to be FMO3 substrates when, in reality, the experimentally validated in silico model correctly predicts that they are not.