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Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease

Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approach...

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Autores principales: Hassan, Mubashir, Abbas, Qamar, Seo, Sung-Yum, Shahzadi, Saba, Ashwal, Hany Al, Zaki, Nazar, Iqbal, Zeeshan, Moustafa, Ahmed A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6059694/
https://www.ncbi.nlm.nih.gov/pubmed/29845262
http://dx.doi.org/10.3892/mmr.2018.9044
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author Hassan, Mubashir
Abbas, Qamar
Seo, Sung-Yum
Shahzadi, Saba
Ashwal, Hany Al
Zaki, Nazar
Iqbal, Zeeshan
Moustafa, Ahmed A.
author_facet Hassan, Mubashir
Abbas, Qamar
Seo, Sung-Yum
Shahzadi, Saba
Ashwal, Hany Al
Zaki, Nazar
Iqbal, Zeeshan
Moustafa, Ahmed A.
author_sort Hassan, Mubashir
collection PubMed
description Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule-associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity.
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spelling pubmed-60596942018-07-26 Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease Hassan, Mubashir Abbas, Qamar Seo, Sung-Yum Shahzadi, Saba Ashwal, Hany Al Zaki, Nazar Iqbal, Zeeshan Moustafa, Ahmed A. Mol Med Rep Review Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule-associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity. D.A. Spandidos 2018-07 2018-05-22 /pmc/articles/PMC6059694/ /pubmed/29845262 http://dx.doi.org/10.3892/mmr.2018.9044 Text en Copyright: © Hassan et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Review
Hassan, Mubashir
Abbas, Qamar
Seo, Sung-Yum
Shahzadi, Saba
Ashwal, Hany Al
Zaki, Nazar
Iqbal, Zeeshan
Moustafa, Ahmed A.
Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease
title Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease
title_full Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease
title_fullStr Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease
title_full_unstemmed Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease
title_short Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease
title_sort computational modeling and biomarker studies of pharmacological treatment of alzheimer's disease
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6059694/
https://www.ncbi.nlm.nih.gov/pubmed/29845262
http://dx.doi.org/10.3892/mmr.2018.9044
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