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Differentiating Physicochemical Properties between Addictive and Nonaddictive ADHD Drugs Revealed by Molecular Dynamics Simulation Studies
Wang, PP; Zhang, XY; Fu, TT; Li, S; Li, B; Xue, WW; Yao, XJ(姚小军); Chen, YZ; Zhu, F; Zhu, F (reprint author), Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Zhejiang, Peoples R China.; Zhu, F (reprint author), Chongqing Univ, Collaborat Innovat Ctr Brain Sci, Chongqing 401331, Peoples R China.; Xue, WW (reprint author), Chongqing Univ, Sch Pharmaceut Sci, Chongqing, Peoples R China.
收录类别SCIE ; PUBMED
2017-06
发表期刊ACS CHEMICAL NEUROSCIENCE
卷号8期号:6页码:1416-1428
出版者AMER CHEMICAL SOC
出版地WASHINGTON
摘要Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed mental disorder of children and adolescents. Although psychostimulants are currently the first-line drugs for ADHD, their highly addictive profile raises great abuse concerns. It is known that psychostimulants' addictiveness is largely attributed to their interaction with dopamine transporter (DAT) and their binding modes in DAT can thus facilitate the understanding of the mechanism underlining drugs' addictiveness. However, no DAT residue able to discriminate ADHD drugs' addictiveness is identified, and the way how different drug structures affect their abuse liability is still elusive. In this study, multiple computational methods were integrated to differentiate binding modes between approved psychostimulants and ADHD drugs of little addictiveness. As a result, variation in energy contribution of 8 residues between addictive and nonaddictive drugs was observed, and a reduction in hydrophobicity of drugs' 2 functional groups was identified as the indicator of drugs' addictiveness. This finding agreed well with the physicochemical properties of 8 officially reported controlled substances. The identified variations in binding mode can shed light on the mechanism underlining drugs' addictiveness, which may thus facilitate the discovery of improved ADHD therapeutics with reduced addictive profile.
关键词ADHD drug psychostimulants addictive profile abuse potential molecular dynamics
作者部门
[Wang, Panpan;
Zhu, Feng] Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Zhejiang, Peoples R China;
[Wang, Panpan;
Zhang, Xiaoyu;
Fu, Tingting;
Li, Shuang;
Li, Bo;
Xue, Weiwei;
Zhu, Feng] Chongqing Univ, Sch Pharmaceut Sci, Innovat Drug Res & Bioinformat Grp, Chongqing 401331, Peoples R China;
[Wang, Panpan...更多
学科领域Biochemistry & Molecular Biology ; Pharmacology & Pharmacy ; Neurosciences & Neurology
所属项目编号National Natural Science Foundation of China [21505009] ; Precision Medicine Project of the National Key Research and Development Plan of China [2016YFC0902200] ; Innovation Project on Industrial Generic Key Technologies of Chongqing [cstc2015zdcy-ztzx120003] ; Fundamental Research Funds for Central Universities [10611CDJXZ238826, CDJZR14468801, CDJKXB14011]
资助项目国家自然科学基金项目 ; 国家重点研发计划
项目资助者NSFC ; MOST
DOI10.1021/acschemneuro.7b00173
ISSN1948-7193
文章类型Article
语种英语
WOS记录号WOS:000404098100032
PM记录号28557437
IR记录号WOS:000404098100032
第一机构
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文献类型期刊论文
条目标识符http://ir.lzu.edu.cn/handle/262010/190173
Collection化学化工学院
通讯作者Xue, WW; Zhu, F (reprint author), Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Zhejiang, Peoples R China.; Zhu, F (reprint author), Chongqing Univ, Collaborat Innovat Ctr Brain Sci, Chongqing 401331, Peoples R China.; Xue, WW (reprint author), Chongqing Univ, Sch Pharmaceut Sci, Chongqing, Peoples R China.
作者单位16CHEM
Recommended Citation:
GB/T 7714
Wang, PP,Zhang, XY,Fu, TT,et al. Differentiating Physicochemical Properties between Addictive and Nonaddictive ADHD Drugs Revealed by Molecular Dynamics Simulation Studies[J]. ACS CHEMICAL NEUROSCIENCE,2017,8(6):1416-1428.
APA Wang, PP.,Zhang, XY.,Fu, TT.,Li, S.,Li, B.,...&Xue, WW .(2017).Differentiating Physicochemical Properties between Addictive and Nonaddictive ADHD Drugs Revealed by Molecular Dynamics Simulation Studies.ACS CHEMICAL NEUROSCIENCE,8(6),1416-1428.
MLA Wang, PP,et al."Differentiating Physicochemical Properties between Addictive and Nonaddictive ADHD Drugs Revealed by Molecular Dynamics Simulation Studies".ACS CHEMICAL NEUROSCIENCE 8.6(2017):1416-1428.
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