scholarly journals Current and emerging therapeutic targets of alzheimer's disease for the design of multi-target directed ligands

MedChemComm ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 2052-2072 ◽  
Author(s):  
Laura Blaikie ◽  
Graeme Kay ◽  
Paul Kong Thoo Lin

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, and a major cause of death worldwide. Since AD is a multi-factorial disease, a MTDL approach to drug discovery is discussed.

Author(s):  
Alexander P. Ducruet ◽  
Andreas Vogt ◽  
Peter Wipf ◽  
John S. Lazo

The complete sequencing of the human genome is generating many novel targets for drug discovery. Understanding the pathophysiological roles of these putative targets and assessing their suitability for therapeutic intervention has become the major hurdle for drug discovery efforts. The dual-specificity phosphatases (DSPases), which dephosphorylate serine, threonine, and tyrosine residues in the same protein substrate, have important roles in multiple signaling pathways and appear to be deregulated in cancer and Alzheimer's disease. We examine the potential of DSPases as new molecular therapeutic targets for the treatment of human disease.


RSC Advances ◽  
2017 ◽  
Vol 7 (10) ◽  
pp. 6046-6058 ◽  
Author(s):  
Zhidong Liu ◽  
Aihua Zhang ◽  
Hui Sun ◽  
Ying Han ◽  
Ling Kong ◽  
...  

Alzheimer's disease is a progressive and irreversible neurodegenerative disease, associated with a decreased cognitive function and severe behavioral abnormalities.


2021 ◽  
Vol 53 (5) ◽  
pp. 405-422
Author(s):  
MG Figueiro ◽  
HC Kales

Alzheimer’s disease and related dementias is the collective term for a progressive neurodegenerative disease for which there is presently no cure. This paper focuses on two symptoms of the disease, sleep disturbances and depression, and discusses how light can be used as a non-pharmacological intervention to mitigate their negative effects. Bright days and dark nights are needed for health and well-being, but the present components of the built environment, especially those places where older adults spend most of their days, are too dimly illuminated during the day and too bright at night. To be effective light needs to be correctly specified, implemented and measured. Yet, without the appropriate specification and measurement of the stimulus, researchers will not be able to successfully demonstrate positive results in the field, nor will lighting designers and specifiers have the confidence to implement lighting solutions for promoting better sleep and mood in this population.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lishu Duan ◽  
Mufeng Hu ◽  
Joseph A. Tamm ◽  
Yelena Y. Grinberg ◽  
Fang Shen ◽  
...  

AbstractAlzheimer’s disease (AD) is a common neurodegenerative disease with poor prognosis. New options for drug discovery targets are needed. We developed an imaging based arrayed CRISPR method to interrogate the human genome for modulation of in vitro correlates of AD features, and used this to assess 1525 human genes related to tau aggregation, autophagy and mitochondria. This work revealed (I) a network of tau aggregation modulators including the NF-κB pathway and inflammatory signaling, (II) a correlation between mitochondrial morphology, respiratory function and transcriptomics, (III) machine learning predicted novel roles of genes and pathways in autophagic processes and (IV) individual gene function inferences and interactions among biological processes via multi-feature clustering. These studies provide a platform to interrogate underexplored aspects of AD biology and offer several specific hypotheses for future drug discovery efforts.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shingo Tsuji ◽  
Takeshi Hase ◽  
Ayako Yachie-Kinoshita ◽  
Taiko Nishino ◽  
Samik Ghosh ◽  
...  

Abstract Background Identifying novel therapeutic targets is crucial for the successful development of drugs. However, the cost to experimentally identify therapeutic targets is huge and only approximately 400 genes are targets for FDA-approved drugs. As a result, it is inevitable to develop powerful computational tools that can identify potential novel therapeutic targets. Fortunately, the human protein-protein interaction network (PIN) could be a useful resource to achieve this objective. Methods In this study, we developed a deep learning-based computational framework that extracts low-dimensional representations of high-dimensional PIN data. Our computational framework uses latent features and state-of-the-art machine learning techniques to infer potential drug target genes. Results We applied our computational framework to prioritize novel putative target genes for Alzheimer’s disease and successfully identified key genes that may serve as novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we could infer repositionable candidate-compounds for the disease (e.g., tamoxifen, bosutinib, and dasatinib). Conclusions Our deep learning-based computational framework could be a powerful tool to efficiently prioritize new therapeutic targets and enhance the drug repositioning strategy.


Author(s):  
Michele Rossi ◽  
Michela Freschi ◽  
Luciana de Camargo Nascente ◽  
Alessandra Salerno ◽  
Sarah de Melo Viana Teixeira ◽  
...  

2020 ◽  
Vol 107 (4) ◽  
pp. 796-805 ◽  
Author(s):  
Daniela J. Conrado ◽  
Sridhar Duvvuri ◽  
Hugo Geerts ◽  
Jackson Burton ◽  
Carla Biesdorf ◽  
...  

2016 ◽  
Vol 39 ◽  
pp. S6
Author(s):  
Claudio Villegas-Llerena ◽  
Mar Matarin ◽  
John Hardy ◽  
Jennifer Pocock

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