4-methylbenzaldehyde guanylhydrazone hydrochloride | 173787-40-1

• 分子结构分类: 有机化合物 - 苯类化合物 - 苯和取代衍生物
• 英文名称: 4-methylbenzaldehyde guanylhydrazone hydrochloride
• 英文别名: AG-6；2-[(4-Methylphenyl)methylideneamino]guanidine;hydrochloride；2-[(4-methylphenyl)methylideneamino]guanidine;hydrochloride
• CAS: 173787-40-1
• 化学式: C₉H₁₂N₄*ClH
• 分子量: 212.682
• InChiKey: CDGLYNFLSABGEU-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  1.02
• 重原子数：
  14
• 可旋转键数：
  2
• 环数：
  1.0
• sp3杂化的碳原子比例：
  0.11
• 拓扑面积：
  76.8
• 氢给体数：
  3
• 氢受体数：
  2

反应信息

• 作为产物：
  描述：

  对甲基苯甲醛 、 肼甲酰亚胺酰胺一氯化氢 在 盐酸 作用下， 以 乙醇 为溶剂， 以40%的产率得到4-methylbenzaldehyde guanylhydrazone hydrochloride
  参考文献：
  名称：

  Design, synthesis, and evaluation of guanylhydrazones as potential inhibitors or reactivators of acetylcholinesterase

  摘要：

  Analogs of pralidoxime, which is a commercial antidote for intoxication from neurotoxic organophosphorus compounds, were designed, synthesized, characterized, and tested as potential inhibitors or reactivators of acetylcholinesterase (AChE) using the Ellman's test, nuclear magnetic resonance, and molecular modeling. These analogs include 1-methylpyridine-2-carboxaldehyde hydrazone, 1-methylpyridine-2-carboxaldehyde guanylhydrazone, and six other guanylhydrazones obtained from different benzaldehydes. The results indicate that all compounds are weak AChE reactivators but relatively good AChE inhibitors. The most effective AChE inhibitor discovered was the guanylhydrazone derived from 2,4-dinitrobenzaldehyde and was compared with tacrine, displaying similar activity to this reference material. These results indicate that guanylhydrazones as well as future similar derivatives may function as drugs for the treatment of Alzheimer's disease.

  DOI：

  10.3109/14756366.2015.1094468

文献信息

• Improving the inhibitory activity of arylidenaminoguanidine compounds at the N-methyl-d-aspartate receptor complex from a recursive computational-experimental structure–activity relationship study
  作者：Joshua R. Ring、Fang Zheng、Aaron J. Haubner、John M. Littleton、Peter A. Crooks

  DOI：10.1016/j.bmc.2013.01.051

  日期：2013.4

  Using a combination of both the partial least squares (PLS) and back-propagation artificial neural network (ANN) pattern recognition methods, several models have been developed to predict the activity of a series of arylidenaminoguanidine analogs as inhibitory modulators of the N-methyl-D-aspartate receptor complex. This was done by correlating structural and physicochemical descriptors obtained from computation software with the experimentally observed [H-3]MK-801 displacement ability of a small library of synthesized and in vitro screened arylidenaminoguanidines. Results for the generated PLS model were r(2) = 0.814, rmsd = 0.208, r(CV)(2) = 0.714, loormsd = 0.261. The ANN model was created utilizing the eleven descriptors from the PLS model for comparison. The quality of the ANN model (r(2)=0.828, rmsd = 0.200, r(CV)(2) = 0.721, loormsd = 0.257) is similar to the PLS model, and indicates that the feature between the inputs and the output is majorly linear. These computational models were able to predict inhibition of the NMDA receptor complex by this series of compounds in silico, affording a predictive structure-based 'pre-screening' paradigm for the arylideneaminoguanidine analogs. (C) 2013 Elsevier Ltd. All rights reserved.