Please wait a minute...
Acta Physico-Chimica Sinica  2005, Vol. 21 Issue (07): 800-803    DOI: 10.3866/PKU.WHXB20050720
Research on Pseudoreceptor Models for the Inhibitors at GABA Receptors via Flexible Atom Receptor Model
SHEN Bin; LU Zhong-hua; CHI Xue-bin; LÜ Hai-feng; REN Tian-rui
Computer Network Information Center, Chinese Academy of Sciences, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100080
Download:   PDF(359KB) Export: BibTeX | EndNote (RIS)      

Abstract  A selective pseudoreceptor models for the inhibitors at GABA receptors of fly and rat were built via Flarm program. The pseudoreceptor models simulated the receptors very well and had good predicting ability. The q2 values of the training sets were 0.874 and 0.897, and the r2 values of the predict sets were 0.962 and 0.733. The Flarm models predicted that there are five binding sites when the compounds bind with GABA receptors, but there might be some different favoritism between the GABA receptors of fly and rat. The results were in accordance with pharmacorphore models built in previous research, and all the results gave insight to find the relations and differences between the inhibitors acting on the GABA receptor of fly and rat.

Key wordsFlexible atom receptor model (Flarm)      GABA receptor      Quantitative structure activity relationship(QSAR)      Inhibitor     
Received: 06 November 2004      Published: 15 July 2005
Corresponding Authors: SHEN Bin     E-mail:
Cite this article:

SHEN Bin; LU Zhong-hua; CHI Xue-bin; LÜ Hai-feng; REN Tian-rui. Research on Pseudoreceptor Models for the Inhibitors at GABA Receptors via Flexible Atom Receptor Model. Acta Physico-Chimica Sinica, 2005, 21(07): 800-803.

URL:     OR

[1] DING Xiaoqin, DING Junjie, LI Dayu, PAN Li, PEI Chengxin. Toxicity Prediction of Organoph Osphorus Chemical Reactivity Compounds Based on Conceptual DFT[J]. Acta Physico-Chimica Sinica, 2018, 34(3): 314-322.
[2] YUAN Lian, LIU Yu-Jiao, HE Huan, JIANG Feng-Lei, LI Hui-Rong, LIU Yi. Microcalorimetric Analysis of Isolated Rat Liver Mitochondrial Metabolism under Different Conditions[J]. Acta Physico-Chimica Sinica, 2018, 34(1): 73-80.
[3] LIU Fu-Feng, FAN Yu-Bo, LIU Zhen, BAI Shu. Molecular Mechanism Underlying Affinity Interactions between ZAβ3 and the Aβ16-40 Monomer[J]. Acta Physico-Chimica Sinica, 2017, 33(9): 1905-1914.
[4] DENG Yu-Ling, YU Lu, HUANG Qiang. A Multi-Target Docking System of Human Kinome[J]. Acta Physico-Chimica Sinica, 2016, 32(9): 2355-2363.
[5] MENG Xian-Mei, ZHANG Shao-Long, ZHANG Qing-Gang . Effect of the Allosteric Inhibitor Efavirenz on HIV-1 Reverse Transcriptase by Molecular Dynamics Simulation[J]. Acta Physico-Chimica Sinica, 2016, 32(2): 436-444.
[6] LIN Feng, FU Xin-Mei, WANG Chao, JIANG Si-Yu, WANG Jing-Hui, ZHANG Shu-Wei, YANG Ling, LI Yan. QSAR, Molecular Docking and Molecular Dynamics of 3C-like Protease Inhibitors[J]. Acta Physico-Chimica Sinica, 2016, 32(11): 2693-2708.
[7] LUO Qi-Yao, WANG Zi-Yun, JIN Hong-Wei, LIU Zhen-Ming, ZHANG Liang-Ren. Improved Docking-Based Virtual Screening Using the Score Correction Strategy for Specific Endothelial Lipase Inhibitors Identification[J]. Acta Physico-Chimica Sinica, 2016, 32(10): 2606-2619.
[8] HE Bing, LUO Yong, LI Bing-Ke, XUE Ying, YU Luo-Ting, QIU Xiao-Long, YANG Teng-Kuei. Predicting and Virtually Screening Breast Cancer Targeting Protein HEC1 Inhibitors by Molecular Descriptors and Machine Learning Methods[J]. Acta Physico-Chimica Sinica, 2015, 31(9): 1795-1802.
[9] ZHANG Shu-Zhen, ZHENG Chao, ZHU Chang-Jin. Molecular Docking and Receptor-Based 3D-QSAR Studies on Aromatic Thiazine Derivatives as Selective Aldose Reductase Inhibitors[J]. Acta Physico-Chimica Sinica, 2015, 31(12): 2395-2404.
[10] WANG Tai-Yang, ZOU Chang-Jun, LI Dai-Xi, CHEN Zheng-Long, LIU Yuan, LI Xiao-Ke, LI Ming. Theoretical Investigation on Cyclodextrin Inclusion Complexes with Organic Phosphoric Acid as Corrosion Inhibitor[J]. Acta Physico-Chimica Sinica, 2015, 31(12): 2294-2302.
[11] LIU Hai-Chun, LU Shuai, RAN Ting, ZHANG Yan-Min, XU Jin-Xing, XIONG Xiao, XU An-Yang, LU Tao, CHEN Ya-Dong. Accurate Activity Predictions of B-Raf Type II Inhibitors via Molecular Docking and QSAR Methods[J]. Acta Physico-Chimica Sinica, 2015, 31(11): 2191-2206.
[12] LI Bing-Ke, CONG Yong, TIAN Zhi-Yue, XUE Ying. Predicting and Virtually Screening the Selective Inhibitors of MMP-13 over MMP-1 by Molecular Descriptors and Machine Learning Methods[J]. Acta Physico-Chimica Sinica, 2014, 30(1): 171-182.
[13] LI Xiang-Hong, XIE Xiao-Guang. Inhibition Effect of Pyrimidine Derivatives on the Corrosion of Steel in Hydrochloric Acid Solution[J]. Acta Physico-Chimica Sinica, 2013, 29(10): 2221-2231.
[14] CONG Yong, XUE Ying. Quantitative Structure-Activity Relationship Study of the Non-Nucleoside Inhibitors of HCV NS5B Polymerase by Machine Learning Methods[J]. Acta Physico-Chimica Sinica, 2013, 29(08): 1639-1647.
[15] SUN Sang-Dun, MI Si-Qi, YOU Jing, YU Ji-Liang, HU Song-Qing, LIU Xin-Yong. HQSAR Study and Molecular Design of Benzimidazole Derivatives as Corrosion Inhibitors[J]. Acta Physico-Chimica Sinica, 2013, 29(06): 1192-1200.