TY - JOUR
T1 - Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives
AU - Zhang, Shuqun
AU - Hou, Bo
AU - Yang, Huaiyu
AU - Zuo, Zhili
N1 - Publisher Copyright:
© 2016, The Pharmaceutical Society of Korea.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer’s disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r2 = 0.988, q2 = 0.757, ONC = 6; r2 = 0.966, q2 = 0.645, ONC = 5; and r2 = 0.957, q2 = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r2values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.
AB - Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer’s disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r2 = 0.988, q2 = 0.757, ONC = 6; r2 = 0.966, q2 = 0.645, ONC = 5; and r2 = 0.957, q2 = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r2values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.
KW - AChE
KW - AD
KW - CoMFA
KW - CoMSIA
KW - HQSAR
KW - Huprines inhibitors
UR - https://www.scopus.com/pages/publications/84971607443
U2 - 10.1007/s12272-016-0709-9
DO - 10.1007/s12272-016-0709-9
M3 - 文章
C2 - 26832327
AN - SCOPUS:84971607443
SN - 0253-6269
VL - 39
SP - 591
EP - 602
JO - Archives of Pharmacal Research
JF - Archives of Pharmacal Research
IS - 5
ER -