Literature DB >> 24212027

A combination of pharmacophore modeling, molecular docking and virtual screening for iNOS inhibitors from Chinese herbs.

Xing Wang1, Zhenzhen Ren, Yusu He, Yuhong Xiang, Yanling Zhang, Yanjiang Qiao.   

Abstract

Inducible Nitric Oxide Synthase (iNOS) has been involved in a variety of diseases, and thus it is interesting to discover new iNOS inhibitors. This study was performed to identify natural iNOS inhibitors from traditional Chinese herbs through a combination of pharmacophore modeling, molecular docking and virtual screening. First, the pharmacophore models were generated though six known iNOS inhibitors and validated by a test database. The pharmacophore model_017 showed good performance in external validation and was employed to screen Traditional Chinese Medicine Database (Version 2009), which resulting in a hit list of 498 compounds with matching score (QFIT) above 40. Then, the hits were subjected to molecular docking for further refinement. An empirical scoring function was used to evaluate the affinity of the compounds and the target protein. Parts of compounds with high docking scores have been reported to have the related pharmacological activity from the literatures. The results provide a set of useful guidelines for the rational discovery of natural iNOS inhibitors from Chinese herbs.

Entities:  

Keywords:  Inducible Nitric Oxide Synthase; Traditional Chinese Medicine; Virtual screening; active natural ingredients identification; pharmacophore

Mesh:

Substances:

Year:  2014        PMID: 24212027     DOI: 10.3233/BME-130934

Source DB:  PubMed          Journal:  Biomed Mater Eng        ISSN: 0959-2989            Impact factor:   1.300


  9 in total

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2.  Discovery of New Inhibitors of eEF2K from Traditional Chinese Medicine Based on In Silico Screening and In Vitro Experimental Validation.

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Journal:  Molecules       Date:  2022-07-30       Impact factor: 4.927

3.  The Mechanism Research of Qishen Yiqi Formula by Module-Network Analysis.

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Journal:  Evid Based Complement Alternat Med       Date:  2015-08-24       Impact factor: 2.629

4.  Discovery of Potential Inhibitors of Aldosterone Synthase from Chinese Herbs Using Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation Studies.

Authors:  Ganggang Luo; Fang Lu; Liansheng Qiao; Xi Chen; Gongyu Li; Yanling Zhang
Journal:  Biomed Res Int       Date:  2016-10-03       Impact factor: 3.411

5.  Virtual Screening and Molecular Dynamics Study of Potential Negative Allosteric Modulators of mGluR1 from Chinese Herbs.

Authors:  Ludi Jiang; Xianbao Zhang; Xi Chen; Yusu He; Liansheng Qiao; Yanling Zhang; Gongyu Li; Yuhong Xiang
Journal:  Molecules       Date:  2015-07-15       Impact factor: 4.411

6.  Discovery of Dual ETA/ETB Receptor Antagonists from Traditional Chinese Herbs through in Silico and in Vitro Screening.

Authors:  Xing Wang; Yuxin Zhang; Qing Liu; Zhixin Ai; Yanling Zhang; Yuhong Xiang; Yanjiang Qiao
Journal:  Int J Mol Sci       Date:  2016-03-16       Impact factor: 5.923

7.  ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Authors:  Baixia Zhang; Yanwen Li; Yanling Zhang; Zhiyong Li; Tian Bi; Yusu He; Kuokui Song; Yun Wang
Journal:  Evid Based Complement Alternat Med       Date:  2016-02-29       Impact factor: 2.629

8.  Discovery of Potential Inhibitors of Squalene Synthase from Traditional Chinese Medicine Based on Virtual Screening and In Vitro Evaluation of Lipid-Lowering Effect.

Authors:  Yankun Chen; Xi Chen; Ganggang Luo; Xu Zhang; Fang Lu; Liansheng Qiao; Wenjing He; Gongyu Li; Yanling Zhang
Journal:  Molecules       Date:  2018-04-28       Impact factor: 4.411

9.  Study on Structure Activity Relationship of Natural Flavonoids against Thrombin by Molecular Docking Virtual Screening Combined with Activity Evaluation In Vitro.

Authors:  Xiaoyan Wang; Zhen Yang; Feifei Su; Jin Li; Evans Owusu Boadi; Yan-Xu Chang; Hui Wang
Journal:  Molecules       Date:  2020-01-20       Impact factor: 4.411

  9 in total

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