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

Mubashir Hassan, Qamar Abbas, Sung Yum Seo, Saba Shahzadi, Hany Al Ashwal, Nazar Zaki, Zeeshan Iqbal, Ahmed A. Moustafa

Research output: Contribution to journalReview articlepeer-review

13 Citations (Scopus)

Abstract

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 ? 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.

Original languageEnglish
Pages (from-to)639-655
Number of pages17
JournalMolecular Medicine Reports
Volume18
Issue number1
DOIs
Publication statusPublished - Jul 2018

Keywords

  • Alzheimer's disease
  • Biomarkers
  • Computational modeling
  • Genetics
  • Simulation

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Oncology
  • Cancer Research

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