Current Drug Repurposing Strategies for Rare Neurodegenerative Disorders

Current Small Molecule-Based Medicinal Chemistry Approaches for Neurodegeneration Therapeutics

Neurodegenerative diseases (NDDs) like Alzheimer's disease (AD), Parkinson's disease (PD), and Amyotrophic lateral sclerosis (ALS) possess multifactorial aetiologies. In recent years, our understanding of the biochemical and molecular pathways across NDDs has increased, however, new advances in small molecule-based therapeutic strategies targeting NDDs are obscure and scarce. Moreover, NDDs have been studied for more than five decades, however, there is a paucity of drugs that can treat NDDs. Further, the highly lipoidal blood-brain barrier (BBB) limits the uptake of many therapeutic molecules into the brain and is a complicating factor in the development of new agents to treat neurodegeneration. Considering the highly complex nature of NDDs, the association of multiple risk factors, and the challenges to overcome the BBB junction, medicinal chemists have developed small organic molecule-based novel approaches to target NDDs over the last few decades, such as designing lipophilic molecules and applying prodrug strategies. Attempts have been made to utilize a multitarget approach to modulate different biochemical molecular pathways involved in NDDs, in addition to, medicinal chemists making better decisions in identifying optimized drug candidates for the central nervous system (CNS) by using web-based computational tools. To increase the clinical success of these drug candidates, an in vitro assay modeling the BBB has been utilized by medicinal chemists in the pre-clinical phase as a further screening measure of small organic molecules. Herein, we examine some of the intriguing strategies taken by medicinal chemists to design small organic molecules to combat NDDs, with the intention of increasing our awareness of neurodegenerative therapeutics.

Phenotypic overlap between rare disease patients and variant carriers in a large population cohort informs biological mechanisms

The biological mechanisms giving rise to the extreme symptoms exhibited by rare disease patients are complex, heterogenous, and difficult to discern. Understanding these mechanisms is critical for developing treatments that address the underlying causes of diseases rather than merely the presenting symptoms. Moreover, the same dysfunctional biological mechanisms implicated in rare recessive diseases may also lead to milder and potentially preventable symptoms in carriers in the general population. Seizures are a common, extreme phenotype that can result from diverse and often elusive biological pathways in patients with ultrarare or undiagnosed disorders. In this pilot study, we present an approach to understand the biological pathways leading to seizures in patients from the Undiagnosed Diseases Network (UDN) by analyzing aggregated genotype and phenotype data from the UK Biobank (UKB). Specifically, we look for enriched phenotypes across UKB participants who harbor rare variants in the same gene known or suspected to be causally implicated in a UDN patient's recessively manifesting disorder. Analyzing these milder but related associated phenotypes in UKB participants can provide insight into the disease-causing molecular mechanisms at play in the rare disease UDN patient. We present six vignettes of undiagnosed patients experiencing seizures as part of their recessive genetic condition, and we discuss the potential mechanisms underlying the spectrum of symptoms associated with UKB participants to the severe presentations exhibited by UDN patients. We find that in our set of rare disease patients, seizures may result from diverse, multi-step pathways that involve multiple body systems. Analyses of large-scale population cohorts such as the UKB can be a critical tool to further our understanding of rare diseases in general.

Synergizing drug repurposing and target identification for neurodegenerative diseases

Despite dedicated research efforts, the absence of disease-curing remedies for neurodegenerative diseases (NDDs) continues to jeopardize human society and stands as a challenge. Drug repurposing is an attempt to find new functionality of existing drugs and take it as an opportunity to discourse the clinically unmet need to treat neurodegeneration. However, despite applying this approach to rediscover a drug, it can also be used to identify the target on which a drug could work. The primary objective of target identification is to unravel all the possibilities of detecting a new drug or repurposing an existing drug. Lately, scientists and researchers have been focusing on specific genes, a particular site in DNA, a protein, or a molecule that might be involved in the pathogenesis of the disease. However, the new era discusses directing the signaling mechanism involved in the disease progression, where receptors, ion channels, enzymes, and other carrier molecules play a huge role. This review aims to highlight how target identification can expedite the whole process of drug repurposing. Here, we first spot various target-identification methods and drug-repositioning studies, including drug-target and structure-based identification studies. Moreover, we emphasize various drug repurposing approaches in NDDs, namely, experimental-based, mechanism-based, and in silico approaches. Later, we draw attention to validation techniques and stress on drugs that are currently undergoing clinical trials in NDDs. Lastly, we underscore the future perspective of synergizing drug repurposing and target identification in NDDs and present an unresolved question to address the issue.

Mutant-Huntingtin Molecular Pathways Elucidate New Targets for Drug Repurposing

The spectrum of neurodegenerative diseases known today is quite extensive. The complexities of their research and treatment lie not only in their diversity. Even many years of struggle and narrowly focused research on common pathologies such as Alzheimer's, Parkinson's, and other brain diseases have not brought cures for these illnesses. What can be said about orphan diseases? In particular, Huntington's disease (HD), despite affecting a smaller part of the human population, still attracts many researchers. This disorder is known to result from a mutation in the HTT gene, but having this information still does not simplify the task of drug development and studying the mechanisms of disease progression. Nonetheless, the data accumulated over the years and their analysis provide a good basis for further research. Here, we review studies devoted to understanding the mechanisms of HD. We analyze genes and molecular pathways involved in HD pathogenesis to describe the action of repurposed drugs and try to find new therapeutic targets.

The Next Generation COVID-19 Antiviral; Niclosamide-Based Inorganic Nanohybrid System Kills SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic is a serious global threat with surging new variants of concern. Although global vaccinations have slowed the pandemic, their longevity is still unknown. Therefore, new orally administrable antiviral agents are highly demanded. Among various repurposed drugs, niclosamide (NIC) is the most potential one for various viral diseases such as COVID-19, SARS (severe acute respiratory syndrome), MERS (middle east respiratory syndrome), influenza, RSV (respiratory syncytial virus), etc. Since NIC cannot be effectively absorbed, a required plasma concentration for antiviral potency is hard to maintain, thereby restricting its entry into the infected cells. Such a 60-year-old bioavailability challenging issue has been overcome by engineering with MgO and hydroxypropyl methylcellulose (HPMC), forming hydrophilic NIC-MgO-HPMC, with improved intestinal permeability without altering NIC metabolism as confirmed by parallel artificial membrane permeability assay. The inhibitory effect on SARS-CoV-2  replication is confirmed in the Syrian hamster model to reduce lung injury. Clinical studies reveal that the bioavailability of NIC hybrid drug can go 4 times higher than the intact NIC. The phase II clinical trial shows a dose-dependent bioavailability of NIC from hybrid drug  suggesting its potential applicability as a game changer in achieving the much-anticipated endemic phase.

Elucidation of bioinformatic-guided high-prospect drug repositioning candidates for DMD via Swanson linking of target-focused latent knowledge from text-mined categorical metadata

Duchenne Muscular Dystrophy (DMD)'s complex multi-system pathophysiology, coupled with the cost-prohibitive logistics of multi-year drug screening and follow-up, has hampered the pursuit of new therapeutic approaches. Here we conducted a systematic historical and text mining-based pilot feasibility study to explore the potential of established or previously tested drugs as prospective DMD therapeutic agents. Our approach utilized a Swanson linking-inspired method to uncover meaningful yet largely hidden deep semantic connections between pharmacologically significant DMD targets and drugs developed for unrelated diseases. Specifically, we focused on molecular target-based MeSH terms and categories as high-yield bioinformatic proxies, effectively tagging relevant literature with categorical metadata. To identify promising leads, we comprehensively assembled published reports from 2011 and sampling from subsequent years. We then determined the earliest year when distinct MeSH terms or category labels of the relevant cellular target were referenced in conjunction with the drug, as well as when the pertinent target itself was first conclusively identified as holding therapeutic value for DMD. By comparing the earliest year when the drug was identifiable as a DMD treatment candidate with that of the first actual report confirming this, we computed an Index of Delayed Discovery (IDD), which serves as a metric of Swanson-linked latent knowledge. Using these findings, we identified data from previously unlinked articles subsetted via MeSH-derived Swanson linking or from target classes within the DrugBank repository. This enabled us to identify new but untested high-prospect small-molecule candidates that are of particular interest in repurposing for DMD and warrant further investigations.

GLP-1R agonists demonstrate potential to treat Wolfram syndrome in human preclinical models

AIMS/HYPOTHESIS

Wolfram syndrome is a rare autosomal recessive disorder caused by pathogenic variants in the WFS1 gene. It is characterised by insulin-dependent diabetes mellitus, optic nerve atrophy, diabetes insipidus, hearing loss and neurodegeneration. Considering the unmet treatment need for this orphan disease, this study aimed to evaluate the therapeutic potential of glucagon-like peptide 1 receptor (GLP-1R) agonists under wolframin (WFS1) deficiency with a particular focus on human beta cells and neurons.

METHODS

The effect of the GLP-1R agonists dulaglutide and exenatide was examined in Wfs1 knockout mice and in an array of human preclinical models of Wolfram syndrome, including WFS1-deficient human beta cells, human induced pluripotent stem cell (iPSC)-derived beta-like cells and neurons from control individuals and individuals affected by Wolfram syndrome, and humanised mice.

RESULTS

Our study shows that the long-lasting GLP-1R agonist dulaglutide reverses impaired glucose tolerance in WFS1-deficient mice, and that exenatide and dulaglutide improve beta cell function and prevent apoptosis in different human WFS1-deficient models including iPSC-derived beta cells from people with Wolfram syndrome. Exenatide improved mitochondrial function, reduced oxidative stress and prevented apoptosis in Wolfram syndrome iPSC-derived neural precursors and cerebellar neurons.

CONCLUSIONS/INTERPRETATION

Our study provides novel evidence for the beneficial effect of GLP-1R agonists on WFS1-deficient human pancreatic beta cells and neurons, suggesting that these drugs may be considered as a treatment for individuals with Wolfram syndrome.

Identification of Potential Parkinson's Disease Drugs Based on Multi-Source Data Fusion and Convolutional Neural Network

Parkinson’s disease (PD) is a serious neurodegenerative disease. Most of the current treatment can only alleviate symptoms, but not stop the progress of the disease. Therefore, it is crucial to find medicines to completely cure PD. Finding new indications of existing drugs through drug repositioning can not only reduce risk and cost, but also improve research and development efficiently. A drug repurposing method was proposed to identify potential Parkinson’s disease-related drugs based on multi-source data integration and convolutional neural network. Multi-source data were used to construct similarity networks, and topology information were utilized to characterize drugs and PD-associated proteins. Then, diffusion component analysis method was employed to reduce the feature dimension. Finally, a convolutional neural network model was constructed to identify potential associations between existing drugs and LProts (PD-associated proteins). Based on 10-fold cross-validation, the developed method achieved an accuracy of 91.57%, specificity of 87.24%, sensitivity of 95.27%, Matthews correlation coefficient of 0.8304, area under the receiver operating characteristic curve of 0.9731 and area under the precision–recall curve of 0.9727, respectively. Compared with the state-of-the-art approaches, the current method demonstrates superiority in some aspects, such as sensitivity, accuracy, robustness, etc. In addition, some of the predicted potential PD therapeutics through molecular docking further proved that they can exert their efficacy by acting on the known targets of PD, and may be potential PD therapeutic drugs for further experimental research. It is anticipated that the current method may be considered as a powerful tool for drug repurposing and pathological mechanism studies.

Neuronal Hyperexcitability and Free Radical Toxicity in Amyotrophic Lateral Sclerosis: Established and Future Targets

Amyotrophic lateral sclerosis (ALS) is a devastating disease with evidence of degeneration involving upper and lower motor neuron compartments of the nervous system. Presently, two drugs, riluzole and edaravone, have been established as being useful in slowing disease progression in ALS. Riluzole possesses anti-glutamatergic properties, while edaravone eliminates free radicals (FRs). Glutamate is the excitatory neurotransmitter in the brain and spinal cord and binds to several inotropic receptors. Excessive activation of these receptors generates FRs, inducing neurodegeneration via damage to intracellular organelles and upregulation of proinflammatory mediators. FRs bind to intracellular structures, leading to cellular impairment that contributes to neurodegeneration. As such, excitotoxicity and FR toxicities have been considered as key pathophysiological mechanisms that contribute to the cascade of degeneration that envelopes neurons in ALS. Recent advanced technologies, including neurophysiological, imaging, pathological and biochemical techniques, have concurrently identified evidence of increased excitability in ALS. This review focuses on the relationship between FRs and excitotoxicity in motor neuronal degeneration in ALS and introduces concepts linked to increased excitability across both compartments of the human nervous system. Within this cellular framework, future strategies to promote therapeutic development in ALS, from the perspective of neuronal excitability and function, will be critically appraised.