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4-dimethylaminobenzaldehyde guanylhydrazone hydrochloride | 53973-09-4

中文名称
——
中文别名
——
英文名称
4-dimethylaminobenzaldehyde guanylhydrazone hydrochloride
英文别名
JR-219;(4-dimethylamino-benzylidenamino)-guanidine; monohydrochloride;(4-Dimethylamino-benzylidenamino)-guanidin; Monohydrochlorid;2-[[4-(dimethylamino)phenyl]methylideneamino]guanidine;hydrochloride
4-dimethylaminobenzaldehyde guanylhydrazone hydrochloride化学式
CAS
53973-09-4
化学式
C10H15N5*ClH
mdl
——
分子量
241.724
InChiKey
ZBCKJIJBDNZHRJ-UHFFFAOYSA-N
BEILSTEIN
——
EINECS
——
  • 物化性质
  • 计算性质
  • ADMET
  • 安全信息
  • SDS
  • 制备方法与用途
  • 上下游信息
  • 反应信息
  • 文献信息
  • 表征谱图
  • 同类化合物
  • 相关功能分类
  • 相关结构分类

计算性质

  • 辛醇/水分配系数(LogP):
    0.99
  • 重原子数:
    16.0
  • 可旋转键数:
    3.0
  • 环数:
    1.0
  • sp3杂化的碳原子比例:
    0.2
  • 拓扑面积:
    77.5
  • 氢给体数:
    3.0
  • 氢受体数:
    3.0

反应信息

  • 作为产物:
    参考文献:
    名称:
    Improving the inhibitory activity of arylidenaminoguanidine compounds at the N-methyl-d-aspartate receptor complex from a recursive computational-experimental structure–activity relationship study
    摘要:
    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.
    DOI:
    10.1016/j.bmc.2013.01.051
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文献信息

  • Design, synthesis, and evaluation of guanylhydrazones as potential inhibitors or reactivators of acetylcholinesterase
    作者:Elaine da Conceição Petronilho、Magdalena do Nascimento Rennó、Newton Gonçalves Castro、Fernanda Motta R. da Silva、Angelo da Cunha Pinto、José Daniel Figueroa-Villar
    DOI:10.3109/14756366.2015.1094468
    日期:2016.11.1
    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.
  • 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.
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