Generation of the AD Informer Set: Chemical tools to facilitate Alzheimer’s disease drug discovery
Background Currently, treatments for Alzheimer’s disease (AD) predominantly include acetylcholinesterase inhibitors, which address the symptomatic effects of the disease. The discovery of disease modifying interventions in the development and progression of AD are critical as there are currently no...
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Veröffentlicht in: | Alzheimer's & dementia 2021-12, Vol.17 (S9), p.n/a |
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Sprache: | eng |
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Zusammenfassung: | Background
Currently, treatments for Alzheimer’s disease (AD) predominantly include acetylcholinesterase inhibitors, which address the symptomatic effects of the disease. The discovery of disease modifying interventions in the development and progression of AD are critical as there are currently no drugs or biologics which can elicit disease modifying effects. Promisingly there is an increase in the number of novel therapeutic strategies targeting AD that have progressed to clinical trials, and interrogation of targets implicated in AD pathology remains an area of extensive research.
Method
To assist the discovery of novel strategies that slow or halt AD pathology we have generated the AD Informer Set, the first iteration of which contains more than 150 chemical tools. We will make solutions of the physical set as well as all associated data available to the scientific community in 2021. Further data is being collected on compound kinetic solubility, pharmacokinetic properties, potential off‐target liabilities, and AD‐specific readouts, including mitochondrial metabolism, oxidative stress and glycolysis, and effects on p‐Tau and Aβ expression levels.
Result
The AD Informer Set includes compounds for targets that have AD implicated biology, either well validated or recently suggested, and contains relevant information about the gene, compound structure and activity, and associated AD phenotypes. 1, 2
Conclusion
The AD Informer Set will be shared with the scientific community at large to qualify assays, interrogate target validity in AD models, and to provide positive controls to aid in the discovery of new chemical entities. References: (1) Hodes RJ, Buckholtz N. Accelerating Medicines Partnership: Alzheimer's Disease (AMP‐AD) Knowledge Portal Aids Alzheimer's Drug Discovery through Open Data Sharing. Expert Opin Ther Targets. 2016, 20, 389‐91. PMID: 26853544. (2) Mullard A. NIH launches open science Alzheimer initiative. Nat Rev Drug Discov. 2019, 18, 895. PMID: 31780852. |
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ISSN: | 1552-5260 1552-5279 |
DOI: | 10.1002/alz.051113 |