Unlocking the Potential of APP: The Amyloid Intracellular Domain 57 as a Drug Target and Biomarker

Target Name: APP

NCBI ID: G351

Content of Review Report on APP Target / Biomarker

APP

Unlocking the Potential of APP: The Amyloid Intracellular Domain 57 as a Drug Target and Biomarker

Introduction

Amyloid intracellular domain 57 (APP57) is a highly conserved protein that is expressed in the brains of individuals with Alzheimer's disease (AD). It is a transmembrane protein that plays a crucial role in the formation of amyloid plaques, which are the hallmark pathology hallmarks of AD. As a result, APP57 has emerged as a promising drug target and biomarker for the development of new treatments for AD.

Disease Background

AD is a progressive neurodegenerative disorder that is characterized by the accumulation of misfolded proteins, including APP57, in the brain. The hallmark of AD is the formation of amyloid plaques, which are composed of aggregated APP57 and other proteins that form a toxic scaffold that accelerates the progression of neurodegeneration.

The Role of APP57 in AD

APP57 is a key player in the formation of amyloid plaques in AD. It is expressed in the brains of individuals with AD and has been shown to localize to the amyloid region of the brain, where it is involved in the formation of amyloid plaques. Additionally , studies have shown that APP57 levels are higher in individuals with AD than in age-matched control individuals, and that levels decrease with age, suggesting a possible role for APP57 in the development of AD.

Drug Target Potential

APP57 has the potential to be a drug target for the treatment of AD because of its involvement in the formation of amyloid plaques. Drugs that can inhibit the formation of amyloid plaques, such as those that target APP57, may have therapeutic benefits for AD.

One approach to targeting APP57 is to use small molecules that can inhibit the activity of APP57. Such molecules have been shown to be effective in animal models of AD. For example, a drug called BACE1 inhibitor, which targets the 尾-amyloid protein, has has been shown to reduce the formation of amyloid plaques in animal models of AD.

Another approach to targeting APP57 is to use antibodies that recognize and target APP57. This approach has been shown to be effective in animal models of AD. For example, an antibody called R42 has been shown to reduce the formation of amyloid plaques in animal models of AD.

Biomarker Potential

APP57 has the potential to serve as a biomarker for the diagnosis and monitoring of AD. As the hallmark of AD is the formation of amyloid plaques, researchers may be able to use APP57 as a biomarker for the disease.

One approach to using APP57 as a biomarker for AD is to measure the level of APP57 in the brain in individuals with AD. This can be done using techniques such as Western blotting, which involves the use of antibodies to measure the level of a specific protein in the brain. Additionally, researchers may be able to use APP57 as a biomarker to monitor the effectiveness of treatments for AD. For example, researchers may be able to measure the level of APP57 in the brain after an expose to a treatment for AD, and compare the level to a control group.

Conclusion

In conclusion, APP57 is a promising drug target and biomarker for the development of new treatments for AD. Its involvement in the formation of amyloid plaques makes it a potential target for small molecules and antibodies that can inhibit the formation of these plaques. Further research is needed to fully understand the role of APP57 in AD and to develop effective treatments for the disease.

Protein Name: Amyloid Beta Precursor Protein

Functions: Functions as a cell surface receptor and performs physiological functions on the surface of neurons relevant to neurite growth, neuronal adhesion and axonogenesis. Interaction between APP molecules on neighboring cells promotes synaptogenesis (PubMed:25122912). Involved in cell mobility and transcription regulation through protein-protein interactions. Can promote transcription activation through binding to APBB1-KAT5 and inhibits Notch signaling through interaction with Numb. Couples to apoptosis-inducing pathways such as those mediated by G(o) and JIP. Inhibits G(o) alpha ATPase activity (By similarity). Acts as a kinesin I membrane receptor, mediating the axonal transport of beta-secretase and presenilin 1 (By similarity). By acting as a kinesin I membrane receptor, plays a role in axonal anterograde transport of cargo towards synapes in axons (PubMed:17062754, PubMed:23011729). Involved in copper homeostasis/oxidative stress through copper ion reduction. In vitro, copper-metallated APP induces neuronal death directly or is potentiated through Cu(2+)-mediated low-density lipoprotein oxidation. Can regulate neurite outgrowth through binding to components of the extracellular matrix such as heparin and collagen I and IV. The splice isoforms that contain the BPTI domain possess protease inhibitor activity. Induces a AGER-dependent pathway that involves activation of p38 MAPK, resulting in internalization of amyloid-beta peptide and leading to mitochondrial dysfunction in cultured cortical neurons. Provides Cu(2+) ions for GPC1 which are required for release of nitric oxide (NO) and subsequent degradation of the heparan sulfate chains on GPC1

The "APP Target / Biomarker Review Report" is a customizable review of hundreds up to thousends of related scientific research literature by AI technology, covering specific information about APP comprehensively, including but not limited to:
•   general information;
•   protein structure and compound binding;
•   protein biological mechanisms;
•   its importance;
•   the target screening and validation;
•   expression level;
•   disease relevance;
•   drug resistance;
•   related combination drugs;
•   pharmacochemistry experiments;
•   related patent analysis;
•   advantages and risks of development, etc.
The report is helpful for project application, drug molecule design, research progress updates, publication of research papers, patent applications, etc. If you are interested to get a full version of this report, please feel free to contact us at BD@silexon.ai

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