Literature DB >> 22460031

Quantitative structure and bioactivity relationship study on human acetylcholinesterase inhibitors.

Aixia Yan1, Kai Wang.   

Abstract

Several QSAR (Quantitative Structure-Activity Relationships) models for predicting the inhibitory activity of 404 Acetylcholinesterase inhibitors were developed. The whole dataset was split into a training set and a test set randomly or using a Kohonen's self-organizing map. Then the inhibitory activity of 404 Acetylcholinesterase inhibitors was predicted using Multilinear Regression (MLR) analysis and Support Vector Machine (SVM) methods, respectively. For the test sets, correlation coefficients of all our models over 0.90 were achieved. Y-randomization test was employed to ensure the robustness of our models and a docking simulation was used to confirm the descriptors we used.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22460031     DOI: 10.1016/j.bmcl.2012.02.108

Source DB:  PubMed          Journal:  Bioorg Med Chem Lett        ISSN: 0960-894X            Impact factor:   2.823


  3 in total

1.  Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking.

Authors:  Saw Simeon; Nuttapat Anuwongcharoen; Watshara Shoombuatong; Aijaz Ahmad Malik; Virapong Prachayasittikul; Jarl E S Wikberg; Chanin Nantasenamat
Journal:  PeerJ       Date:  2016-08-09       Impact factor: 2.984

2.  Development of dual inhibitors against Alzheimer's disease using fragment-based QSAR and molecular docking.

Authors:  Manisha Goyal; Jaspreet Kaur Dhanjal; Sukriti Goyal; Chetna Tyagi; Rabia Hamid; Abhinav Grover
Journal:  Biomed Res Int       Date:  2014-06-12       Impact factor: 3.411

3.  7-Methoxytacrine-adamantylamine heterodimers as cholinesterase inhibitors in Alzheimer's disease treatment--synthesis, biological evaluation and molecular modeling studies.

Authors:  Katarina Spilovska; Jan Korabecny; Jan Kral; Anna Horova; Kamil Musilek; Ondrej Soukup; Lucie Drtinova; Zuzana Gazova; Katarina Siposova; Kamil Kuca
Journal:  Molecules       Date:  2013-02-20       Impact factor: 4.411

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.