4-(5-bromopentyl)-7-nitro-3,4-dihydro-1H-quinoxalin-2-one | 1571074-88-8

• 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: 4-(5-bromopentyl)-7-nitro-3,4-dihydro-1H-quinoxalin-2-one
• CAS: 1571074-88-8
• 化学式: C₁₃H₁₆BrN₃O₃
• 分子量: 342.192
• InChiKey: SLUAVQZXUSUVBL-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  2.92
• 重原子数：
  20.0
• 可旋转键数：
  6.0
• 环数：
  2.0
• sp3杂化的碳原子比例：
  0.46
• 拓扑面积：
  75.48
• 氢给体数：
  1.0
• 氢受体数：
  4.0

反应信息

• 作为反应物：
  描述：

  4-(5-bromopentyl)-7-nitro-3,4-dihydro-1H-quinoxalin-2-one 在 potassium dichromate 、 硫酸 作用下， 以 水 为溶剂， 反应 2.0h， 以95%的产率得到1-(5-bromopentyl)-6-nitroquinoxaline-2,3(1H,4H)-dione
  参考文献：
  名称：

  A Quinoxaline Derivative as a Potent Chemotherapeutic Agent, Alone or in Combination with Benznidazole, against Trypanosoma cruzi

  摘要：

  背景 查加斯病是由原生动物克氏锥虫（Trypanosoma cruzi）引起的一种疾病，影响数百万人，主要集中在拉丁美洲，被认为是地方性疾病。查加斯病的化疗仍然是一个问题；目前的标准治疗依赖于一种单一药物苯尼达唑，但不幸的是，它会引起多种副作用，并且对大多数慢性患者的治愈效果不佳。为了改善对查加斯病的药物武器库，本研究描述了化合物3-氯-7-甲氧基-2-(甲基磺酰基)喹喔啉（喹喔啉4）的合成及其在体外对克氏锥虫的活性，单独使用或与苯尼达唑联合使用。 方法/主要发现 喹喔啉4对克氏锥虫Y株表现出强烈活性，并对增殖形态的效果更为显著。对LLCMK2细胞的细胞毒性显示出所有寄生虫形态的选择性指数均大于1。该药物诱导的溶血非常低，但在针对锥虫时，加入小鼠血液后其抗原生动物活性部分受到抑制，这一效应与血液细胞特定相关。观察到喹喔啉4与苯尼达唑在对表慢性虫及锥虫时表现出协同效应，同时在LLCMK2细胞上则表现出拮抗作用。喹喔啉4诱导了多种超微结构改变，包括囊泡体的形成、环状内质网包围细胞器的轮廓以及高尔基体的解构。这些改变也伴随着细胞体积缩小和处理寄生虫细胞膜完整性的维持。 结论/重要性 我们的结果表明，喹喔啉4无论单独使用还是与苯尼达唑联用，对T. cruzi的所有主要形态均具有良好的效果。该化合物在低浓度下诱导了多种超微结构改变，并导致寄生虫发生类似自噬的细胞死亡。综合这些结果可能支持进一步开发作为查加斯病治疗的更有效替代方案的联合疗法。

  DOI：

  10.1371/journal.pone.0085706
• 作为产物：
  描述：

  6-nitro-3-oxo-1,2,3,4-tetrahydroquinoxaline-1-spiro-1'-piperidinium bromide 以 硝基甲烷 为溶剂， 反应 48.0h， 以94%的产率得到4-(5-bromopentyl)-7-nitro-3,4-dihydro-1H-quinoxalin-2-one
  参考文献：
  名称：

  Antiprotozoan lead discovery by aligning dry and wet screening: Prediction, synthesis, and biological assay of novel quinoxalinones

  摘要：

  Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In an effort to overcome this problem, the main purpose of this study is to develop a QSARs-based ensemble classifier for antiprotozoan drug-like entities from a heterogeneous compounds collection. Here, we use some of the TOMO-COMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved. Firstly, we construct a wide-spectrum benchmark database comprising of 680 organic chemicals with great structural variability (254 of them antiprotozoan agents and 426 to drugs having other clinical uses). This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. In total, seven discriminant functions were obtained, by using the whole set of atom-based linear indices. All the LDA-based QSAR models show accuracies above 85% in the training set and values of Matthews correlation coefficients (C) vary from 0.70 to 0.86. The external validation set shows rather-good global classifications of around 80% (92.05% for best equation). Later, we developed a multi-agent QSAR classification system, in which the individual QSAR outputs are the inputs of the aforementioned fusion approach. Finally, the fusion model was used for the identification of a novel generation of lead-like antiprotozoan compounds by using ligand-based virtual screening of 'available' small molecules (with synthetic feasibility) in our 'in-house' library. A new molecular subsystem (quinoxalinones) was then theoretically selected as a promising lead series, and its derivatives subsequently synthesized, structurally characterized, and experimentally assayed by using in vitro screening that took into consideration a battery of five parasite-based assays. The chemicals 11(12) and 16 are the most active (hits) against apicomplexa (sporozoa) and mastigophora (flagellata) subphylum parasites, respectively. Both compounds depicted good activity in every protozoan in vitro panel and they did not show unspecific cytotoxicity on the host cells. The described technical framework seems to be a promising QSAR-classifier tool for the molecular discovery and development of novel classes of broad-antiprotozoan-spectrum drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of protozoan illnesses. (C) 2014 Elsevier Ltd. All rights reserved.

  DOI：

  10.1016/j.bmc.2014.01.036