@article {Jiang:2013:1573-4099:385,
title = "CoMFA, CoMSIA and HQSAR Studies of Acetylcholinesterase Inhibitors",
journal = "Current Computer - Aided Drug Design",
parent_itemid = "infobike://ben/cad",
publishercode ="ben",
year = "2013",
volume = "9",
number = "3",
publication date ="2013-09-01T00:00:00",
pages = "385-395",
itemtype = "ARTICLE",
issn = "1573-4099",
url = "https://www.ingentaconnect.com/content/ben/cad/2013/00000009/00000003/art00009",
keyword = "multi-fit alignment, AChE inhibitors, CoMSIA, atom-fit alignment, CoMFA, database alignment, HQSAR, QSAR",
author = "Jiang, Yu-Ren and Yang, Yan-Yan and Chen, Yu-Ling and Liang, Zhong-Jie",
abstract = "A quantitative structure-activity relationship (QSAR) study has been carried out on acetylcholinesterase (AChE) inhibitors with comparative field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR).
In order to investigate the effect of alignment on modeling and find out the best alignment strategy, three different alignment rules were applied to generate CoMFA and CoMSIA models. Statistical results of the highly significant models (CoMFA q2 = 0.748, r2 =0.996, predicted r2 =0.789; CoMSIA
q2 =0.755, r2 =0.973, predicted r2 = 0.706; HQSAR q2 = 0.884, r2 = 0.973, predicted r2 = 0.734) reveal considerable predictive ability. Analysis of the contour maps of CoMFA and CoMSIA models and the atomic contribution maps of HQSAR model may contribute to develop novel and potential AChE
inhibitors.",
}