A peptide–WS2 nanosheet based biosensing platform for determination of β-secretase and screening of its inhibitors

The Analyst ◽  
2018 ◽  
Vol 143 (19) ◽  
pp. 4585-4591 ◽  
Author(s):  
Xianwei Zuo ◽  
Hongxia Dai ◽  
Huige Zhang ◽  
Juanjuan Liu ◽  
Sudai Ma ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Target ◽  
Important Drug

β-Secretase (BACE1) is an important drug target in the treatment of Alzheimer's disease (AD).

Memapsin 2, a drug target for Alzheimer's disease

2003 ◽  
Vol 70 ◽  
pp. 213-220 ◽  
Author(s):  
Gerald Koelsch ◽  
Robert T. Turner ◽  
Lin Hong ◽  
Arun K. Ghosh ◽  
Jordan Tang
Keyword(s):  
Crystal Structure ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Transition State ◽  
Amyloid Precursor Protein ◽  
Therapeutic Target ◽  
Drug Target ◽  
Aspartic Protease ◽  
Precursor Protein ◽  
Memapsin 2

Mempasin 2, a ϐ-secretase, is the membrane-anchored aspartic protease that initiates the cleavage of amyloid precursor protein leading to the production of ϐ-amyloid and the onset of Alzheimer's disease. Thus memapsin 2 is a major therapeutic target for the development of inhibitor drugs for the disease. Many biochemical tools, such as the specificity and crystal structure, have been established and have led to the design of potent and relatively small transition-state inhibitors. Although developing a clinically viable mempasin 2 inhibitor remains challenging, progress to date renders hope that memapsin 2 inhibitors may ultimately be useful for therapeutic reduction of ϐ-amyloid.

scholarly journals Artificial intelligence-based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shingo Tsuji ◽  
Takeshi Hase ◽  
Ayako Yachie-Kinoshita ◽  
Taiko Nishino ◽  
Samik Ghosh ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Drug Target ◽  
Target Genes ◽  
Drug Repositioning ◽  
Therapeutic Targets ◽  
Machine Learning Techniques ◽  
Computational Framework ◽  
Novel Therapeutic

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.

A ratiometric electrochemical strategy for sensitive determination of Furin activity based on dual signal amplification and antifouling nanosurfaces

The Analyst ◽  
2017 ◽  
Vol 142 (22) ◽  
pp. 4215-4220 ◽  
Author(s):  
Dazhi Yao ◽  
Wenqi Zhao ◽  
Limin Zhang ◽  
Yang Tian
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cell Surface ◽  
Signal Amplification ◽  
Accurate Method ◽  
Sensitive Determination ◽  
Dual Signal Amplification

Developing a sensitive and accurate method for Furin activity is still the bottleneck for understanding the role played by Furin in cell-surface systems and even in Alzheimer's disease.

Automatic determination of white matter hyperintensity properties in relation to the development of Alzheimer's disease

2016 ◽  
Author(s):  
Sandra van der Velden ◽  
Christoph Moenninghoff ◽  
Isabel Wanke ◽  
Martha Jokisch ◽  
Christian Weimar ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
White Matter Hyperintensity ◽  
Automatic Determination

The case for soluble Aβ oligomers as a drug target in Alzheimer's disease

2013 ◽  
Vol 34 (5) ◽  
pp. 261-266 ◽  
Author(s):  
Franz Hefti ◽  
William F. Goure ◽  
Jasna Jerecic ◽  
Kent S. Iverson ◽  
Patricia A. Walicke ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Target ◽  
Aβ Oligomers ◽  
Soluble Aβ Oligomers
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