Homology modeling and 3D-QSAR study of benzhydrylpiperazine delta opioid receptor agonists
Pan, Chenling1; Meng, Hao3; Zhang, Shuqun2; Zuo, Zhili2; Shen, Yuehai1,2; Wang, Liangliang2; Chang, Kwen-Jen1
Corresponding AuthorShen, Yuehai(yuehaishen@kmust.edu.cn) ; Wang, Liangliang(wangliangliang@mail.kib.ac.cn)
2019-12-01
Source PublicationCOMPUTATIONAL BIOLOGY AND CHEMISTRY
ISSN1476-9271
Volume83Pages:9
AbstractThe binding affinity of a series of benzhydrylpiperazine delta opioid receptor agonists were pooled and evaluated by using 3D-QSAR and homology modeling/molecular docking methods. Ligand-based CoMFA and CoMSIA 3D-QSAR analyses with 46 compounds were performed on benzhydrylpiperazine analogues by taking the most active compound BW373U86 as the template. The models were generated successfully with q(2) value of 0.508 and r(2) value of 0.964 for CoMFA, and q(2) value of 0.530 and r(2) value of 0.927 for CoMSIA. The predictive capabilities of the two models were validated on the test set with R-pred(2) value of 0.720 and 0.814, respectively. The CoMSIA model appeared to work better in this case. A homology model of active form of 8 opioid receptor was established by Swiss-Model using a reported crystal structure of active mu opioid receptor as a template, and was further optimized using nanosecond scale molecular dynamics simulation. The most active compound BW373U86 was docked to the active site of 8 opioid receptor and the lowest energy binding pose was then used to identify binding residues such as s Gln105, Lys108, Leu125, Asp128, Tyr129, Leu200, Met132, Met199, Lys214, Trp274, Ile277, Ile304 and Tyr308. The docking and 3D-QSAR results showed that hydrogen bond and hydrophobic interactions played major roles in ligand-receptor interactions. Our results highlight that an approach combining structure-based homology modeling/molecular docking and ligand-based 3D-QSAR methods could be useful in designing of new opioid receptor agonists.
Keyworddelta opioid receptor agonists 3D-QSAR Homology modeling Molecular dynamics simulation Molecular docking
DOI10.1016/j.compbiolchem.2019.107109
Indexed BySCI ; SCI
Language英语
WOS Research AreaLife Sciences & Biomedicine - Other Topics ; Computer Science
WOS SubjectBiology ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000501651500015
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Document Type期刊论文
Identifierhttp://ir.kib.ac.cn/handle/151853/70580
Collection植物化学与西部植物资源持续利用国家重点实验室
Corresponding AuthorShen, Yuehai; Wang, Liangliang
Affiliation1.Kunming Univ Sci & Technol, Fac Life Sci & Technol, Kunming 650500, Yunnan, Peoples R China
2.Chinese Acad Sci, Kunming Inst Bot, State Key Lab Phytochem & Plant Resources West Ch, Kunming 650201, Yunnan, Peoples R China
3.Beijing Beike Deyuan Biopharrn Technol Co Ltd, Beijing 100094, Peoples R China
Recommended Citation
GB/T 7714
Pan, Chenling,Meng, Hao,Zhang, Shuqun,et al. Homology modeling and 3D-QSAR study of benzhydrylpiperazine delta opioid receptor agonists[J]. COMPUTATIONAL BIOLOGY AND CHEMISTRY,2019,83:9.
APA Pan, Chenling.,Meng, Hao.,Zhang, Shuqun.,Zuo, Zhili.,Shen, Yuehai.,...&Chang, Kwen-Jen.(2019).Homology modeling and 3D-QSAR study of benzhydrylpiperazine delta opioid receptor agonists.COMPUTATIONAL BIOLOGY AND CHEMISTRY,83,9.
MLA Pan, Chenling,et al."Homology modeling and 3D-QSAR study of benzhydrylpiperazine delta opioid receptor agonists".COMPUTATIONAL BIOLOGY AND CHEMISTRY 83(2019):9.
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