3,4-dihydro-1-(2'-methoxycarbonylphenyl)isoquinoline

• 分子结构分类: 有机化合物 - 有机杂环化合物 - 二氢异喹啉
• 英文名称: 3,4-dihydro-1-(2'-methoxycarbonylphenyl)isoquinoline
• 英文别名: 1-(2-methoxycarbonylphenyl)-3,4-dihydroisoquinoline；Methyl 2-(3,4-dihydroisoquinolin-1-yl)benzoate；methyl 2-(3,4-dihydroisoquinolin-1-yl)benzoate
• 化学式: C₁₇H₁₅NO₂
• 分子量: 265.312
• InChiKey: AJIRUAFQIPUVOI-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  3.2
• 重原子数：
  20
• 可旋转键数：
  3
• 环数：
  3.0
• sp3杂化的碳原子比例：
  0.18
• 拓扑面积：
  38.7
• 氢给体数：
  0
• 氢受体数：
  3

反应信息

• 作为反应物：
  描述：

  3,4-dihydro-1-(2'-methoxycarbonylphenyl)isoquinoline 在 盐酸 、 硫酸 、 palladium 10% on activated carbon 、 三氧化硫 、 水 作用下， 以 苯 为溶剂， 反应 2.0h， 生成 7H-二苯并[de,H]喹啉-7-酮
  参考文献：
  名称：

  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

  摘要：

  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.

  DOI：

  10.1016/j.ejmech.2011.09.045
• 作为产物：
  描述：

  2,3-dihydro-3-hydroxy-2-(2-phenylethyl)-1H-isoindol-1-one 在 盐酸 、 potassium hydroxide 作用下， 以 甲醇 、 水 为溶剂， 反应 28.0h， 生成 3,4-dihydro-1-(2'-methoxycarbonylphenyl)isoquinoline
  参考文献：
  名称：

  Synthesis and antiplasmodial activity of some 1-azabenzanthrone derivatives

  摘要：

  Some synthetic 1-azabenzanthrones (7H-dibenzo[de,h]quinolin-7-ones) are weakly to moderately cytotoxic, suggesting that they might also show antiparasitic activity. We have now tested a small collection of these compounds in vitro against a chloroquine-resistant Plasmodium falciparum strain, comparing their cytotoxicity against normal human fibroblasts. Our results indicate that 5-methoxy-1-azabenzanthrone and its 2,3-dihydro analogue have low micromolar antiplasmodial activities and showed more than 10-fold selectivity against the parasite, indicating that the dihydro compound, in particular, might serve as a lead compound for further development. (C) 2012 Elsevier Ltd. All rights reserved.

  DOI：

  10.1016/j.bmcl.2012.10.092

文献信息

• Complete structural and spectral assignment of oxoisoaporphines by HMQC and HMBC experiments
  作者：Eduardo Sobarzo-Sánchez、Bruce K. Cassels、Carolina Jullian、Luis Castedo

  DOI：10.1002/mrc.1177

  日期：2003.4

  The oxoisoaporphines 2,3‐dihydro‐7H‐dibenzo[de,h]quinolin‐7‐one, 2,3‐dihydro‐5‐methoxy‐7H‐dibenzo [de,h] quinolin‐7‐one, 5‐methoxy‐6‐hydroxy‐2,3‐dihydro‐7H‐dibenzo[de,h]quinolin‐7‐one, 5,6‐dimethoxy‐2,3‐dihydro‐7H‐dibenzo[de,h]quinolin‐7‐one and 5,6‐methylenedi‐oxy‐2,3‐dihydro‐7H‐dibenzo[de,h]quinolin‐7‐one were prepared by cyclization of phenylethylaminophthalides with polyphosphoric acid or by treating

  2,3-二氢-7H-二苯并[de,h]喹啉-7-酮、2,3-二氢-5-甲氧基-7H-二苯并[de,h]喹啉-7-酮、5-甲氧基-7-酮6-羟基-2,3-二氢-7H-二苯并[de,h]喹啉-7-one, 5,6-二甲氧基-2,3-二氢-7H-二苯并[de,h]喹啉-7-one和5,6-methylenedi-oxy-2,3-dihydro-7H-dibenzo[de,h]quinolin-7-one 通过苯乙氨基苯酞与多磷酸的环化或通过处理 1-(2-carboxyphenyl)-3,4 制备-二氢异喹啉盐酸盐与硫酸在 0 °C 下反应。使用一维和二维核磁共振技术的组合确认了结构，并完全确定了 1H 和 13C 核磁共振谱。版权所有 © 2003 John Wiley & Sons, Ltd.
• 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.
• Synthesis and antiplasmodial activity of some 1-azabenzanthrone derivatives
  作者：Vicente Castro-Castillo、Cristian Suárez-Rozas、Adriana Pabón、Edwin G. Pérez、Bruce K. Cassels、Silvia Blair

  DOI：10.1016/j.bmcl.2012.10.092

  日期：2013.1

  Some synthetic 1-azabenzanthrones (7H-dibenzo[de,h]quinolin-7-ones) are weakly to moderately cytotoxic, suggesting that they might also show antiparasitic activity. We have now tested a small collection of these compounds in vitro against a chloroquine-resistant Plasmodium falciparum strain, comparing their cytotoxicity against normal human fibroblasts. Our results indicate that 5-methoxy-1-azabenzanthrone and its 2,3-dihydro analogue have low micromolar antiplasmodial activities and showed more than 10-fold selectivity against the parasite, indicating that the dihydro compound, in particular, might serve as a lead compound for further development. (C) 2012 Elsevier Ltd. All rights reserved.