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QSAR analysis on tacrine-related acetylcholinesterase inhibitors
BACKGROUND: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer’s disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous i...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177578/ https://www.ncbi.nlm.nih.gov/pubmed/25239202 http://dx.doi.org/10.1186/s12929-014-0084-0 |
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author | Wong, Kai Y Mercader, Andrew G Saavedra, Laura M Honarparvar, Bahareh Romanelli, Gustavo P Duchowicz, Pablo R |
author_facet | Wong, Kai Y Mercader, Andrew G Saavedra, Laura M Honarparvar, Bahareh Romanelli, Gustavo P Duchowicz, Pablo R |
author_sort | Wong, Kai Y |
collection | PubMed |
description | BACKGROUND: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer’s disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous interest, and for this reason we establish Quantitative Structure-Activity Relationships on their Acetylcholinesterase inhibitory activity. RESULTS: Ten groups of new developed Tacrine-related inhibitors are explored, which have been experimentally measured in different biochemical conditions and AChE sources. The number of included descriptors in the structure-activity relationship is characterized by ‘Rule of Thumb’. The 1502 applied molecular descriptors could provide the best linear models for the selected Alzheimer’s data base and the best QSAR model is reported for the considered data sets. CONCLUSION: The QSAR models developed in this work have a satisfactory predictive ability, and are obtained by selecting the most representative molecular descriptors of the chemical structure, represented through more than a thousand of constitutional, topological, geometrical, quantum-mechanical and electronic descriptor types. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12929-014-0084-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4177578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41775782014-10-08 QSAR analysis on tacrine-related acetylcholinesterase inhibitors Wong, Kai Y Mercader, Andrew G Saavedra, Laura M Honarparvar, Bahareh Romanelli, Gustavo P Duchowicz, Pablo R J Biomed Sci Research BACKGROUND: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer’s disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous interest, and for this reason we establish Quantitative Structure-Activity Relationships on their Acetylcholinesterase inhibitory activity. RESULTS: Ten groups of new developed Tacrine-related inhibitors are explored, which have been experimentally measured in different biochemical conditions and AChE sources. The number of included descriptors in the structure-activity relationship is characterized by ‘Rule of Thumb’. The 1502 applied molecular descriptors could provide the best linear models for the selected Alzheimer’s data base and the best QSAR model is reported for the considered data sets. CONCLUSION: The QSAR models developed in this work have a satisfactory predictive ability, and are obtained by selecting the most representative molecular descriptors of the chemical structure, represented through more than a thousand of constitutional, topological, geometrical, quantum-mechanical and electronic descriptor types. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12929-014-0084-0) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-20 /pmc/articles/PMC4177578/ /pubmed/25239202 http://dx.doi.org/10.1186/s12929-014-0084-0 Text en © Wong et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Wong, Kai Y Mercader, Andrew G Saavedra, Laura M Honarparvar, Bahareh Romanelli, Gustavo P Duchowicz, Pablo R QSAR analysis on tacrine-related acetylcholinesterase inhibitors |
title | QSAR analysis on tacrine-related acetylcholinesterase inhibitors |
title_full | QSAR analysis on tacrine-related acetylcholinesterase inhibitors |
title_fullStr | QSAR analysis on tacrine-related acetylcholinesterase inhibitors |
title_full_unstemmed | QSAR analysis on tacrine-related acetylcholinesterase inhibitors |
title_short | QSAR analysis on tacrine-related acetylcholinesterase inhibitors |
title_sort | qsar analysis on tacrine-related acetylcholinesterase inhibitors |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177578/ https://www.ncbi.nlm.nih.gov/pubmed/25239202 http://dx.doi.org/10.1186/s12929-014-0084-0 |
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