scholarly journals Front Cover: Minor Structural Variations of Small Molecules Tune Regulatory Activities toward Pathological Factors in Alzheimer's Disease (ChemMedChem 22/2017)

ChemMedChem ◽  
2017 ◽  
Vol 12 (22) ◽  
pp. 1818-1818 ◽  
Author(s):  
Michael W. Beck ◽  
Jeffrey S. Derrick ◽  
Jong-Min Suh ◽  
Mingeun Kim ◽  
Kyle J. Korshavn ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Structural Variations ◽  
Front Cover

scholarly journals Minor Structural Variations of Small Molecules Tune Regulatory Activities toward Pathological Factors in Alzheimer's Disease

ChemMedChem ◽  
2017 ◽  
Vol 12 (22) ◽  
pp. 1828-1838 ◽  
Author(s):  
Michael W. Beck ◽  
Jeffrey S. Derrick ◽  
Jong-Min Suh ◽  
Mingeun Kim ◽  
Kyle J. Korshavn ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Structural Variations

Small Molecules and Alzheimer’s Disease: Misfolding, Metabolism and Imaging

2015 ◽  
Vol 12 (5) ◽  
pp. 445-461 ◽  
Author(s):  
Viharkumar Patel ◽  
Xueli Zhang ◽  
Nicolas Tautiva ◽  
Akwe Nyabera ◽  
Opeyemi Owa ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules

Recent Updates in the Alzheimer’s Disease Etiopathology and Possible Treatment Approaches: A Narrative Review of Current Clinical Trials

2020 ◽  
Vol 13 (4) ◽  
pp. 273-294 ◽  
Author(s):  
Elahe Zarini-Gakiye ◽  
Javad Amini ◽  
Nima Sanadgol ◽  
Gholamhassan Vaezi ◽  
Kazem Parivar
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Small Molecules ◽  
Clinical Trial Design ◽  
Treatment Approaches ◽  
Drug Candidates ◽  
Novel Treatments ◽  
Approved Drugs ◽  
Tau Aggregation

Background: Alzheimer’s disease (AD) is the most frequent subtype of incurable neurodegenerative dementias and its etiopathology is still not clearly elucidated. Objective: Outline the ongoing clinical trials (CTs) in the field of AD, in order to find novel master regulators. Methods: We strictly reviewed all scientific reports from Clinicaltrials.gov and PubMed databases from January 2010 to January 2019. The search terms were “Alzheimer's disease” or “dementia” and “medicine” or “drug” or “treatment” and “clinical trials” and “interventions”. Manuscripts that met the objective of this study were included for further evaluations. Results: Drug candidates have been categorized into two main groups including antibodies, peptides or hormones (such as Ponezumab, Interferon β-1a, Solanezumab, Filgrastim, Levemir, Apidra, and Estrogen), and naturally-derived ingredients or small molecules (such as Paracetamol, Ginkgo, Escitalopram, Simvastatin, Cilostazo, and Ritalin-SR). The majority of natural candidates acted as anti-inflammatory or/and anti-oxidant and antibodies exert their actions via increasing amyloid-beta (Aβ) clearance or decreasing Tau aggregation. Among small molecules, most of them that are present in the last phases act as specific antagonists (Suvorexant, Idalopirdine, Intepirdine, Trazodone, Carvedilol, and Risperidone) or agonists (Dextromethorphan, Resveratrol, Brexpiprazole) and frequently ameliorate cognitive dysfunctions. Conclusion: The presences of a small number of candidates in the last phase suggest that a large number of candidates have had an undesirable side effect or were unable to pass essential eligibility for future phases. Among successful treatment approaches, clearance of Aβ, recovery of cognitive deficits, and control of acute neuroinflammation are widely chosen. It is predicted that some FDA-approved drugs, such as Paracetamol, Risperidone, Escitalopram, Simvastatin, Cilostazoand, and Ritalin-SR, could also be used in off-label ways for AD. This review improves our ability to recognize novel treatments for AD and suggests approaches for the clinical trial design for this devastating disease in the near future.

scholarly journals Cryo-EM structures of tau filaments from Alzheimer’s disease with PET ligand APN-1607

2021 ◽  
Vol 141 (5) ◽  
pp. 697-708
Author(s):  
Yang Shi ◽  
Alexey G. Murzin ◽  
Benjamin Falcon ◽  
Alexander Epstein ◽  
Jonathan Machin ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Binding Sites ◽  
Binding Activity ◽  
Cortical Atrophy ◽  
Binding Modes ◽  
Major Site ◽  
Age Related ◽  
Positron Emission

AbstractTau and Aβ assemblies of Alzheimer’s disease (AD) can be visualized in living subjects using positron emission tomography (PET). Tau assemblies comprise paired helical and straight filaments (PHFs and SFs). APN-1607 (PM-PBB3) is a recently described PET ligand for AD and other tau proteinopathies. Since it is not known where in the tau folds PET ligands bind, we used electron cryo-microscopy (cryo-EM) to determine the binding sites of APN-1607 in the Alzheimer fold. We identified two major sites in the β-helix of PHFs and SFs and a third major site in the C-shaped cavity of SFs. In addition, we report that tau filaments from posterior cortical atrophy (PCA) and primary age-related tauopathy (PART) are identical to those from AD. In support, fluorescence labelling showed binding of APN-1607 to intraneuronal inclusions in AD, PART and PCA. Knowledge of the binding modes of APN-1607 to tau filaments may lead to the development of new ligands with increased specificity and binding activity. We show that cryo-EM can be used to identify the binding sites of small molecules in amyloid filaments.

scholarly journals Systematic Development of Small Molecules to Inhibit Specific Microscopic Steps of Amyloid-Beta42 Aggregation in Alzheimer's Disease

2018 ◽  
Vol 114 (3) ◽  
pp. 225a
Author(s):  
Sean Chia ◽  
Johnny Habchi ◽  
Ryan Limbocker ◽  
Benedetta Mannini ◽  
Minkoo Ahn ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Systematic Development

Natural Compounds (Small Molecules) as Potential and Real Drugs of Alzheimer's Disease

2014 ◽  
pp. 153-194 ◽  
Author(s):  
Lucie Cahlíková ◽  
Kateřina Macáková ◽  
Nina Benešová ◽  
Jakub Chlebek ◽  
Anna Hošťálková ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Natural Compounds

Automatic Diagnosis of Alzheimer’s Disease Using Deep Learning Techniques

2021 ◽  
Vol 19 (11) ◽  
pp. 126-140
Author(s):  
Zahraa S. Aaraji ◽  
Hawraa H. Abbas
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Data Analysis ◽  
Binary Classification ◽  
Brain Mri ◽  
Three Dimensional ◽  
Structural Variations ◽  
Automatic Feature Extraction ◽  
Multi Class Classification

Neuroimaging data analysis has attracted a great deal of attention with respect to the accurate diagnosis of Alzheimer’s disease (AD). Magnetic Resonance Imaging (MRI) scanners have thus been commonly used to study AD-related brain structural variations, providing images that demonstrate both morphometric and anatomical changes in the human brain. Deep learning algorithms have already been effectively exploited in other medical image processing applications to identify features and recognise patterns for many diseases that affect the brain and other organs; this paper extends on this to describe a novel computer aided software pipeline for the classification and early diagnosis of AD. The proposed method uses two types of three-dimensional Convolutional Neural Networks (3D CNN) to facilitate brain MRI data analysis and automatic feature extraction and classification, so that pre-processing and post-processing are utilised to normalise the MRI data and facilitate pattern recognition. The experimental results show that the proposed approach achieves 97.5%, 82.5%, and 83.75% accuracy in terms of binary classification AD vs. cognitively normal (CN), CN vs. mild cognitive impairment (MCI) and MCI vs. AD, respectively, as well as 85% accuracy for multi class-classification, based on publicly available data sets from the Alzheimer’s disease Neuroimaging Initiative (ADNI).

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