Literature DB >> 26605982

Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes.

Qingzhu Jia, Xue Cui, Lei Li, Qiang Wang, Ying Liu, Shuqian Xia1, Peisheng Ma1.   

Abstract

Arylpiperazine derivatives are promising 5-hydroxytryptamine (5-HT) receptor ligands which can inhibit serotonin reuptake effectively. In this work, some norm index descriptors were proposed and further utilized to develop a model for predicting 5-HT1A receptor affinity (pKi) of 88 arylpiperazine derivatives. Results showed that this new model could provide satisfactory predictions with the square of the correction coefficient (R(2)) of 0.8891 and the squared correlation coefficient of cross-validation (Q(2)) of 0.8082, respectively. In addition, the applicability domain of this model was validated by using the leverage approach and results which suggested potential large scale for further utilization of this model. The results of statistical values and validation tests demonstrated that our proposed norm index based model could be successfully applied for predicting the affinity 5-HT1A receptor ligands of arylpiperazine derivatives.

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Year:  2015        PMID: 26605982     DOI: 10.1021/acs.jpcb.5b08980

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  1 in total

1.  QSAR model for predicting the toxicity of organic compounds to fathead minnow.

Authors:  Qingzhu Jia; Yunpeng Zhao; Fangyou Yan; Qiang Wang
Journal:  Environ Sci Pollut Res Int       Date:  2018-10-22       Impact factor: 4.223

  1 in total

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