Homology modeling and 3D-QSAR study of benzhydrylpiperazine delta opioid receptor agonists

doi:10.1016/j.compbiolchem.2019.107109

CORC > 昆明植物研究所 > 中国科学院昆明植物研究所 > 植物化学与西部植物资源持续利用国家重点实验室

	Homology modeling and 3D-QSAR study of benzhydrylpiperazine delta opioid receptor agonists
	Pan, Chenling 3; Meng, Hao 1; Zhang, Shuqun 2; Zuo, Zhili 2; Shen, Yuehai 2,3; Wang, Liangliang 2; Chang, Kwen-Jen 3
刊名	COMPUTATIONAL BIOLOGY AND CHEMISTRY
	2019-12-01
卷号	83 页码:9
关键词	delta opioid receptor agonists 3D-QSAR Homology modeling Molecular dynamics simulation Molecular docking
ISSN号	1476-9271
DOI	10.1016/j.compbiolchem.2019.107109
通讯作者	Shen, Yuehai(yuehaishen@kmust.edu.cn) ; Wang, Liangliang(wangliangliang@mail.kib.ac.cn)
英文摘要	The 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.
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Computer Science
语种	英语
WOS记录号	WOS:000501651500015
内容类型	期刊论文
源URL	[http://ir.kib.ac.cn/handle/151853/70579]
专题	昆明植物研究所_植物化学与西部植物资源持续利用国家重点实验室
通讯作者	Shen, Yuehai; Wang, Liangliang
作者单位	1.Beijing Beike Deyuan Biopharrn Technol Co Ltd, Beijing 100094, 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.Kunming Univ Sci & Technol, Fac Life Sci & Technol, Kunming 650500, Yunnan, Peoples R China
推荐引用方式 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.