The potentiation of central cholinergic activity has been proposed as a therapeutic approach for improving cognitive function in patients with Alzheimer's disease. Increasing the acetylcholine concentration in brain by modulating acetylcholinesterase (AChE) activity is among the most promising strategies. We have used a combinatorial approach to identify different 2,5-piperazinediones (DKP) with AChE inhibitory activity. Our goal was to find inhibitors exhibiting high AChE/BuChE (butyrylcholinesterase) selectivity, in order to reduce the undesirable side effects elicited by most of the inhibitors that have been developed to date. Screening of a DKP library constructed on solid-phase using the multiple parallel synthesis format, resulted in the identification of several compounds with moderate efficacy on AChE. In particular, DKP-80 had an IC50 = 2.2 microM with no significant inhibitory activity on BuChE. Moreover, estimated values of Clog P and log BB for the most active compounds fulfilled the bioavailability requirements for enzyme inhibitors acting on the central nervous system. In order to understand the inhibitory properties of the ligand at the molecular level, molecular dynamics simulations were computed on DKP-80 complexed to AChE, and the most relevant binding interactions of this inhibitor to the active center of the enzyme were characterized. Overall the present results indicate that the DKP-based compounds identified are novel AChE inhibitors which may be considered likely lead compounds for further development of drug candidates against Alzheimer's disease.
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http://dx.doi.org/10.1023/a:1016230600162 | DOI Listing |
Alzheimers Res Ther
January 2025
Department of Neurology, University Medical Center Rostock, 18147, Rostock, Germany.
Background: Degeneration of the basal forebrain cholinergic system is a hallmark feature shared by Alzheimer's disease (AD) and Lewy body disease (LBD) whereas hippocampus atrophy is more specifically related to AD. We aimed to investigate the relationship between basal forebrain and hippocampus atrophy, cognitive decline, and neuropathology in a large autopsy sample.
Methods: Data were obtained from the National Alzheimer's Coordinating Center (NACC).
Alzheimers Res Ther
January 2025
Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide, leading to cognitive and functional decline. Early detection and intervention are crucial for enhancing the quality of life of patients and their families. Remote Monitoring Technologies (RMTs) offer a promising solution for early detection by tracking changes in behavioral and cognitive functions, such as memory, language, and problem-solving skills.
View Article and Find Full Text PDFTransl Neurodegener
January 2025
Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea.
Alzheimer's disease (AD) is the most common type of dementia. Monoclonal antibodies (MABs) serve as a promising therapeutic approach for AD by selectively targeting key pathogenic factors, such as amyloid-β (Aβ) peptide, tau protein, and neuroinflammation. Specifically, based on their efficacy in removing Aβ plaques from the brains of patients with AD, the U.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
An essential task in spatial transcriptomics is identifying spatially variable genes (SVGs). Here, we present Celina, a statistical method for systematically detecting cell type-specific SVGs (ct-SVGs)-a subset of SVGs exhibiting distinct spatial expression patterns within specific cell types. Celina utilizes a spatially varying coefficient model to accurately capture each gene's spatial expression pattern in relation to the distribution of cell types across tissue locations, ensuring effective type I error control and high power.
View Article and Find Full Text PDFJ Alzheimers Dis
January 2025
Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
Background: The prevalence of Alzheimer's disease or dementia in the elderly population has been increasing both nationally and globally. Males and females are impacted differently when it comes to cognitive health, and this can be influenced by various risk factors.
Objective: This study highlights the sociodemographic, chronic disease, and genetic biomarker risk factors associated with gender differences and cognitive impairments in the elderly population living in Cochran, Parmer, and Bailey counties of rural West Texas.
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