Benzyl (1-(methoxy(methyl)amino)-1-oxopropan-2-yl)carbamate

• 分子结构分类: 有机化合物 - 有机酸及其衍生物 - 羧酸及其衍生物
• 英文名称: Benzyl (1-(methoxy(methyl)amino)-1-oxopropan-2-yl)carbamate
• 英文别名: benzyl N-[1-[methoxy(methyl)amino]-1-oxopropan-2-yl]carbamate
• 化学式: C₁₃H₁₈N₂O₄
• mdl: MFCD11822267
• 分子量: 266.297
• InChiKey: JJWLCBIYQXRMNO-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  1.4
• 重原子数：
  19
• 可旋转键数：
  6
• 环数：
  1.0
• sp3杂化的碳原子比例：
  0.384
• 拓扑面积：
  67.9
• 氢给体数：
  1
• 氢受体数：
  4

反应信息

• 作为反应物：
  描述：

  1-溴辛烷 、 Benzyl (1-(methoxy(methyl)amino)-1-oxopropan-2-yl)carbamate 在 碘 、 magnesium 作用下， 以 四氢呋喃 为溶剂， 反应 11.0h， 以94%的产率得到benzyl (3-oxoundecan-2-yl)carbamate
  参考文献：
  名称：

  Regioselective double Boekelheide reaction: first synthesis of 3,6-dialkylpyrazine-2,5-dicarboxaldehydes from dl-alanine

  摘要：

  Pyrazine-2,5-dicarboxaldehyde was synthesized on a multi-gram scale by MnO2 oxidation of 2,5-bis(hydroxymethyl)pyrazine, which in turn was obtained from 2,5-dimethylpyrazine employing double Boekelheide reaction as a key step as reported previously. This reaction was subsequently utilized in a regioselective fashion as a key step to synthesize efficiently, for the first time, 3,6-di(long-chain)alkylpyrazine-2,5-dicarboxaldehydes starting from DL-alanine. These monomers are certain to have importance as electron deficient and chemically versatile components for new materials development. (C) 2012 Elsevier Ltd. All rights reserved.

  DOI：

  10.1016/j.tetlet.2012.05.057
• 作为产物：
  描述：

  N-CBZ-DL-丙氨酸 、 N-甲基-N-甲氧基胺盐酸盐 在 N-甲基吗啉 、 氯甲酸异丁酯 作用下， 以 四氢呋喃 为溶剂， 反应 1.31h， 以88%的产率得到Benzyl (1-(methoxy(methyl)amino)-1-oxopropan-2-yl)carbamate
  参考文献：
  名称：

  Application of Predictive QSAR Models to Database Mining:  Identification and Experimental Validation of Novel Anticonvulsant Compounds

  摘要：

  We have developed a drug discovery strategy that employs variable selection quantitative structure-activity relationship (QSAR) models for chemical database mining. The approach starts with the development of rigorously validated QSAR models obtained with the variable selection k nearest neighbor (kNN) method (or, in principle, with any other robust model-building technique). Model validation. is based on several statistical criteria, including the randomization of the target property (Y-randomization), independent assessment of the training set model's predictive power using external test sets, and the establishment of the model's applicability domain. All successful models are employed in database mining concurrently; in each case, only variables selected as a result of model building (termed descriptor pharmacophore) are used in chemical similarity searches comparing active compounds of the training set (queries) with those in chemical databases. Specific biological activity (characteristic of the training set compounds) of external database entries found to be within a predefined similarity threshold of the training set molecules is predicted on the basis of the validated QSAR models using the applicability domain criteria. Compounds judged to have high predicted activities by all or the majority of all models are considered as consensus hits. We report on the application of this computational strategy for the first time for the discovery of anticonvulsant agents in the Maybridge and National Cancer Institute (NCI) databases containing ca. 250 000 compounds combined. Forty-eight anticonvulsant agents of the functionalized amino acid (FAA) series were used to build kNN variable selection QSAR models. The 10 best models were applied to mining chemical databases, and 22 compounds were selected as consensus hits. Nine compounds were synthesized and tested at the NIH Epilepsy Branch, Rockville, MD using the same biological test that was employed to assess the anticonvulsant activity of the training set compounds; of these nine, four were exact database hits and five were derived from the hits by minor chemical modifications. Seven of these nine compounds were confirmed to be active, indicating an exceptionally high hit rate. The approach described in this report can be used as a general rational drug discovery tool.

  DOI：

  10.1021/jm030584q

文献信息

• Process For Synthesizing A CETP Inhibitor
  申请人：Miller Ross A.

  公开号：US20100041724A1

  公开（公告）日：2010-02-18

  An efficient process is disclosed for producing a compound that is an inhibitor of CETP. The last step of the process is the coupling of an oxazolidinone derivative with a biphenyl moiety to provide a compound of formula (I). In a specific embodiment of this synthesis, a crystalline product is produced which is characterized as a non-solvated crystalline polymorph.
• Polymer Formulations of CETP Inhibitors
  申请人：Geers Sarah

  公开号：US20100227903A1

  公开（公告）日：2010-09-09

  A pharmaceutical composition comprises (a) a CETP inhibiting compound, or a pharmaceutically acceptable salt thereof; (b) a concentration-enhancing polymer, and (c) optionally one or more surfactants; wherein the compound has the structure shown as Formula I below. The composition raises HDL-cholesterol and lowers LDL-cholesterol.
• US7863307B2
  申请人：——

  公开号：US7863307B2

  公开（公告）日：2011-01-04
• US8030359B2
  申请人：——

  公开号：US8030359B2

  公开（公告）日：2011-10-04
• [EN] SUBSTITUTED N-(PHENETHYL)BENZAMIDE DERIVATIVES, PREPARATION AND USES THEREOF<br/>[FR] COMPOSES DERIVES DE N-(PHENETHYL)BENZAMIDE SUBSTITUES, PREPARATION ET UTILISATIONS
  申请人：GENFIT

  公开号：WO2007118963A2

  公开（公告）日：2007-10-25

  [EN] The invention concerns polysubstituted N-(phenethyl)benzamide derivatives, pharmaceutical compositions containing same, as well as their therapeutic uses, in particular in the field of human and animal health. The invention also concerns a method for preparing said derivatives.
  [FR] La présente invention concerne des dérivés du type N-(phénéthyl)benzamide poly-substitués, les compositions pharmaceutiques les comprenant ainsi que leurs applications thérapeutiques, notamment dans les domaines de la santé humaine et animale. La présente invention a également trait à un procédé de préparation de ces dérivés.