5-Methoxy-2,3,7,11b-tetrahydro-1H-1-aza-benzo[de]anthracen-7-ol | 28399-75-9

• 分子结构分类: 有机化合物 - 生物碱及其衍生物 - 异卟啉
• 英文名称: 5-Methoxy-2,3,7,11b-tetrahydro-1H-1-aza-benzo[de]anthracen-7-ol
• 英文别名: 11-Methoxy-16-azatetracyclo[7.7.1.02,7.013,17]heptadeca-2,4,6,9,11,13(17)-hexaen-8-ol
• CAS: 28399-75-9
• 化学式: C₁₇H₁₇NO₂
• 分子量: 267.327
• InChiKey: JDANGUZHAQZTQA-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  1.9
• 重原子数：
  20
• 可旋转键数：
  1
• 环数：
  4.0
• sp3杂化的碳原子比例：
  0.29
• 拓扑面积：
  41.5
• 氢给体数：
  2
• 氢受体数：
  3

反应信息

• 作为反应物：
  描述：

  5-Methoxy-2,3,7,11b-tetrahydro-1H-1-aza-benzo[de]anthracen-7-ol 在 三氯化铝 作用下， 以 二氯甲烷 、 水 、 乙腈 为溶剂， 反应 2.75h， 生成 8-Methoxy-10,11-dihydro-2H-11a-aza-benzo[cd]pyren-1-one
  参考文献：
  名称：

  氯乙酰胺的光解是获得新的2,8-桥联异喹啉衍生物的途径。8,13-二氢-2-甲氧基-4,6-乙二苯并[ c，f ]氮酮-5,7-二酮的X射线晶体结构

  摘要：

  1-氯乙酰基-2,3-二氢-5-甲氧基-1 H-二苯并[ de，h ]喹啉（3a）和相应的5,6-二甲氧基衍生物（3b）在乙腈水溶液中的光解得到良好的收率8，（4a）和（4b）分别为13-二氢-2-甲氧基-和8,13-二氢-1,2-二甲氧基-4,6-乙二苯并[ c，f ]-叠氮基-5,7-二酮。这些代表2，8-桥连的异喹啉衍生物的第一个实例。通过X射线晶体学确认（4a）的结构。

  DOI：

  10.1016/s0040-4039(00)99204-9
• 作为产物：
  描述：

  5-methoxy-2,3-dihydro-7H-dibenzo[de,h]quinolin-7-one 在 sodium tetrahydroborate 作用下， 以 甲醇 为溶剂， 生成 5-Methoxy-2,3,7,11b-tetrahydro-1H-1-aza-benzo[de]anthracen-7-ol
  参考文献：
  名称：

  氯乙酰胺的光解是获得新的2,8-桥联异喹啉衍生物的途径。8,13-二氢-2-甲氧基-4,6-乙二苯并[ c，f ]氮酮-5,7-二酮的X射线晶体结构

  摘要：

  1-氯乙酰基-2,3-二氢-5-甲氧基-1 H-二苯并[ de，h ]喹啉（3a）和相应的5,6-二甲氧基衍生物（3b）在乙腈水溶液中的光解得到良好的收率8，（4a）和（4b）分别为13-二氢-2-甲氧基-和8,13-二氢-1,2-二甲氧基-4,6-乙二苯并[ c，f ]-叠氮基-5,7-二酮。这些代表2，8-桥连的异喹啉衍生物的第一个实例。通过X射线晶体学确认（4a）的结构。

  DOI：

  10.1016/s0040-4039(00)99204-9

文献信息

• BREMNER, J. B.;JATURONRUSMEE, W.;ENGELHARDT, L. M.;WHITE, A. H., TETRAHEDRON. LETT., 30,(1989) N4, C. 3213-3216
  作者：BREMNER, J. B.、JATURONRUSMEE, W.、ENGELHARDT, L. M.、WHITE, A. H.

  DOI：——

  日期：——
• 2D MI-DRAGON: A new predictor for protein–ligands interactions and theoretic-experimental studies of US FDA drug-target network, oxoisoaporphine inhibitors for MAO-A and human parasite proteins
  作者：Francisco Prado-Prado、Xerardo García-Mera、Manuel Escobar、Eduardo Sobarzo-Sánchez、Matilde Yañez、Pablo Riera-Fernandez、Humberto González-Díaz

  DOI：10.1016/j.ejmech.2011.09.045

  日期：2011.12

  There are many pairs of possible Drug-Proteins Interactions that may take place or not (DPIs/nDPIs) between drugs with high affinity/non-affinity for different proteins. This fact makes expensive in terms of time and resources, for instance, the determination of all possible ligands-protein interactions for a single drug. In this sense, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out rational DPIs prediction. Unfortunately, almost all QSAR models predict activity against only one target. To solve this problem we can develop multi-target QSAR (mt-QSAR) models. In this work, we introduce the technique 2D MI-DRAGON a new predictor for DPIs based on two different well-known software. We use the software MARCH-INSIDE (MI) to calculate 3D structural parameters for targets and the software DRAGON was used to calculated 2D molecular descriptors all drugs showing known DPIs present in the Drug Bank (US FDA benchmark dataset). Both classes of parameters were used as input of different Artificial Neural Network (ANN) algorithms to seek an accurate non-linear mt-QSAR predictor. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 21:21-31-1:1. This MLP classifies correctly 303 out of 339 DPIs (Sensitivity = 89.38%) and 480 out of 510 nDPIs (Specificity = 94.12%), corresponding to training Accuracy = 92.23%. The validation of the model was carried out by means of external predicting series with Sensitivity = 92.18% (625/678 DPIs: Specificity = 90.12% (730/780 nDPIs) and Accuracy = 91.06%. 2D MI-DRAGON offers a good opportunity for fast-track calculation of all possible DPIs of one drug enabling us to re-construct large drug-target or DPIs Complex Networks (CNs). For instance, we reconstructed the CN of the US FDA benchmark dataset with 855 nodes 519 drugs + 336 targets). We predicted CN with similar topology (observed and predicted values of average distance are equal to 6.7 vs. 6.6). These CNs can be used to explore large DPIs databases in order to discover both new drugs and/or targets. Finally, we illustrated in one theoretic-experimental study the practical use of 2D MI-DRAGON. We reported the prediction, synthesis, and pharmacological assay of 10 different oxoisoaporphines with MAO-A inhibitory activity. The more active compound OXO5 presented IC50 = 0.00083 mu M, notably better than the control drug Clorgyline. (C) 2011 Elsevier Masson SAS. All rights reserved.
• Photolysis of chloroacetamides as a route to new 2,8-bridged isoquinoline derivatives. X-ray crystal structure of 8,13-dihydro-2-methoxy-4,6- ethanodibenz[c,f]azonine-5,7-dione
  作者：J.B. Bremner、W. Jaturonrusmee、L.M. Engelhardt、A.H. White

  DOI：10.1016/s0040-4039(00)99204-9

  日期：——

  Photolysis of 1-chloroacetyl-2,3-dihydro-5-methoxy-1H-dibenzo[de,h]quinoline (3a) and the corresponding 5,6-dimethoxy derivative (3b) in aqueous acetonitrile gave good yields of 8,13-dihydro-2-methoxy- and 8,13-dihydro-1,2-dimethoxy-4,6-ethanodibenz[c,f]-azonine-5,7-dione, (4a) and (4b), respectively. These represent the first examples of 2,8-bridged isoquinoline derivatives. The structure of (4a)

  1-氯乙酰基-2,3-二氢-5-甲氧基-1 H-二苯并[ de，h ]喹啉（3a）和相应的5,6-二甲氧基衍生物（3b）在乙腈水溶液中的光解得到良好的收率8，（4a）和（4b）分别为13-二氢-2-甲氧基-和8,13-二氢-1,2-二甲氧基-4,6-乙二苯并[ c，f ]-叠氮基-5,7-二酮。这些代表2，8-桥连的异喹啉衍生物的第一个实例。通过X射线晶体学确认（4a）的结构。