scholarly journals AD Informer Set: Chemical tools to facilitate Alzheimer's disease drug discovery

2021 ◽  
Author(s):  
Frances M Potjewyd ◽  
Joel K Annor-Gyamfi ◽  
Jeffrey Aube ◽  
Shaoyou Chu ◽  
Ivie L Conlon ◽  
...  

Introduction: The portfolio of novel targets to treat Alzheimer's disease (AD) has been enriched by the AMP-AD program. Methods: A cheminformatics-driven effort enabled identification of existing small molecule modulators for many protein targets nominated by AMP-AD and suitable positive control compounds to be included in the set. Results: We have built an annotated set of 171 small molecule modulators, including mostly inhibitors, targeting 98 unique proteins that have been nominated by AMP-AD consortium members as novel targets for AD treatment. These small molecules vary in their quality and should be considered chemical tools that can be used in efforts to validate therapeutic hypotheses, but which would require further optimization. A physical copy of the AD Informer Set can be ordered via the AD Knowledge Portal. Discussion: Small molecule tools that enable target validation are important tools for the translation of novel hypotheses into viable therapeutic strategies for AD.

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Joanna E. Luo ◽  
Yue-Ming Li

AbstractAlzheimer’s disease (AD) is the most common type of neurodegenerative disorder. Amyloid-beta (Aβ) plaques are integral to the “amyloid hypothesis,” which states that the accumulation of Aβ peptides triggers a cascade of pathological events leading to neurodegeneration and ultimately AD. While the FDA approved aducanumab, the first Aβ-targeted therapy, multiple safe and effective treatments will be needed to target the complex pathologies of AD. γ-Secretase is an intramembrane aspartyl protease that is critical for the generation of Aβ peptides. Activity and specificity of γ-secretase are regulated by both obligatory subunits and modulatory proteins. Due to its complex structure and function and early clinical failures with pan inhibitors, γ-secretase has been a challenging drug target for AD. γ-secretase modulators, however, have dramatically shifted the approach to targeting γ-secretase. Here we review γ-secretase and small molecule modulators, from the initial characterization of a subset of NSAIDs to the most recent clinical candidates. We also discuss the chemical biology of γ-secretase, in which small molecule probes enabled structural and functional insights into γ-secretase before the emergence of high-resolution structural studies. Finally, we discuss the recent crystal structures of γ-secretase, which have provided valuable perspectives on substrate recognition and molecular mechanisms of small molecules. We conclude that modulation of γ-secretase will be part of a new wave of AD therapeutics.


2019 ◽  
Vol 01 (01) ◽  
pp. e22-e32
Author(s):  
Sharmin Reza Chowdhury ◽  
Fangzhou Xie ◽  
Jinxin Gu ◽  
Lei Fu

AbstractAlzheimer's disease (AD) is still an incurable neurodegenerative disease that causes dementia. AD changes the brain function that, over time, impairs memory and diminishes judgment and reasoning ability. Pathophysiology of AD is complex. Till now the cause of AD remains unknown, but risk factors include family history and genetic predisposition. The drugs previously approved for AD treatment do not modify the disease process and only provide symptomatic improvement. Over the past few decades, research has led to significant progress in the understanding of the disease, leading to several novel strategies that may modify the disease process. One of the major developments in this direction is the amyloid β (Aβ) aggregation. Small molecules could block the initial stages of Aβ aggregation, which could be the starting point for the design and development of new AD drugs in the near future. In this review we summarize the most promising small-molecule Aβ-aggregation inhibitors including natural compounds, novel small molecules, and also those are in clinical trials. Moreover, we briefly summarized some reported docking studies of small-molecule Aβ aggregation inhibitors. These will give us an idea about the chemical features required to design novel small molecules with anti-Aβ aggregation properties.


2014 ◽  
Vol 50 (40) ◽  
pp. 5301-5303 ◽  
Author(s):  
Masha G. Savelieff ◽  
Yuzhong Liu ◽  
Russell R. P. Senthamarai ◽  
Kyle J. Korshavn ◽  
Hyuck Jin Lee ◽  
...  

A small molecule was designed for reactivity toward Cu(ii)–amyloid-β over Zn(ii)–amyloid-β, which will expand on the development of chemical tools to uncover the role of metal–Aβ species in Alzheimer's disease.


2014 ◽  
Vol 11 (92) ◽  
pp. 20131057 ◽  
Author(s):  
Fanlin Meng ◽  
Enyu Dai ◽  
Xuexin Yu ◽  
Yan Zhang ◽  
Xiaowen Chen ◽  
...  

Alzheimer's disease (AD) is an incurable neurodegenerative disorder. Much effort has been devoted to developing effective therapeutic agents. Recently, targeting microRNAs (miRNAs) with small molecules has become a novel therapy for human diseases. In this study, we present a systematic computational approach to construct a bioactive Small molecule and miRNA association Network in AD (SmiRN-AD), which is based on the gene expression signatures of bioactive small molecule perturbation and AD-related miRNA regulation. We also performed topological and functional analysis of the SmiRN-AD from multiple perspectives. At the significance level of p ≤ 0.01, 496 small molecule–miRNA associations, including 25 AD-related miRNAs and 275 small molecules, were recognized and used to construct the SmiRN-AD. The drugs that were connected with the same miRNA tended to share common drug targets ( p = 1.72 × 10 −4 ) and belong to the same therapeutic category ( p = 4.22 × 10 −8 ). The miRNAs that were linked to the same small molecule regulated more common miRNA targets ( p = 6.07 × 10 −3 ). Further analysis of the positive connections (quinostatin and miR-148b, amantadine and miR-15a) and the negative connections (melatonin and miR-30e-5p) indicated that our large-scale predictions afforded specific biological insights into AD pathogenesis and therapy. This study proposes a holistic strategy for deciphering the associations between small molecules and miRNAs in AD, which may be helpful for developing a novel effective miRNA-associated therapeutic strategy for AD. A comprehensive database for the SmiRN-AD and the differential expression patterns of the miRNA targets in AD is freely available at http://bioinfo.hrbmu.edu.cn/SmiRN-AD/ .


2019 ◽  
Vol 16 (3) ◽  
pp. 193-208 ◽  
Author(s):  
Yan Hu ◽  
Guangya Zhou ◽  
Chi Zhang ◽  
Mengying Zhang ◽  
Qin Chen ◽  
...  

Background: Alzheimer's disease swept every corner of the globe and the number of patients worldwide has been rising. At present, there are as many as 30 million people with Alzheimer's disease in the world, and it is expected to exceed 80 million people by 2050. Consequently, the study of Alzheimer’s drugs has become one of the most popular medical topics. Methods: In this study, in order to build a predicting model for Alzheimer’s drugs and targets, the attribute discriminators CfsSubsetEval, ConsistencySubsetEval and FilteredSubsetEval are combined with search methods such as BestFirst, GeneticSearch and Greedystepwise to filter the molecular descriptors. Then the machine learning algorithms such as BayesNet, SVM, KNN and C4.5 are used to construct the 2D-Structure Activity Relationship(2D-SAR) model. Its modeling results are utilized for Receiver Operating Characteristic curve(ROC) analysis. Results: The prediction rates of correctness using Randomforest for AChE, BChE, MAO-B, BACE1, Tau protein and Non-inhibitor are 77.0%, 79.1%, 100.0%, 94.2%, 93.2% and 94.9%, respectively, which are overwhelming as compared to those of BayesNet, BP, SVM, KNN, AdaBoost and C4.5. Conclusion: In this paper, we conclude that Random Forest is the best learner model for the prediction of Alzheimer’s drugs and targets. Besides, we set up an online server to predict whether a small molecule is the inhibitor of Alzheimer's target at http://47.106.158.30:8080/AD/. Furthermore, it can distinguish the target protein of a small molecule.


2015 ◽  
Vol 12 (5) ◽  
pp. 445-461 ◽  
Author(s):  
Viharkumar Patel ◽  
Xueli Zhang ◽  
Nicolas Tautiva ◽  
Akwe Nyabera ◽  
Opeyemi Owa ◽  
...  

2020 ◽  
Vol 13 (4) ◽  
pp. 273-294 ◽  
Author(s):  
Elahe Zarini-Gakiye ◽  
Javad Amini ◽  
Nima Sanadgol ◽  
Gholamhassan Vaezi ◽  
Kazem Parivar

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.


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