EBioMedicine. 2022 Aug 2:104202. doi: 10.1016/j.ebiom.2022.104202. Online ahead of print.

ABSTRACT

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with heterogeneous aetiology and a complex genetic background. Effective therapies are therefore likely to act on convergent pathways such as dysregulated energy metabolism, linked to multiple neurodegenerative diseases including ALS.

METHODS: Activity of the glycolysis enzyme phosphoglycerate kinase 1 (PGK1) was increased genetically or pharmacologically using terazosin in zebrafish, mouse and ESC-derived motor neuron models of ALS. Multiple disease phenotypes were assessed to determine the therapeutic potential of this approach, including axon growth and motor behaviour, survival and cell death following oxidative stress.

FINDINGS: We have found that targeting a single bioenergetic protein, PGK1, modulates motor neuron vulnerability in vivo. In zebrafish models of ALS, overexpression of PGK1 rescued motor axon phenotypes and improved motor behaviour. Treatment with terazosin, an FDA-approved compound with a known non-canonical action of increasing PGK1 activity, also improved these phenotypes. Terazosin treatment extended survival, improved motor phenotypes and increased motor neuron number in Thy1-hTDP-43 mice. In ESC-derived motor neurons expressing TDP-43M337V, terazosin protected against oxidative stress-induced cell death and increased basal glycolysis rates, while rescuing stress granule assembly.

INTERPRETATION: Our data demonstrate that terazosin protects motor neurons via multiple pathways, including upregulating glycolysis and rescuing stress granule formation. Repurposing terazosin therefore has the potential to increase the limited therapeutic options across all forms of ALS, irrespective of disease cause.

FUNDING: This work was supported by project grant funding from MND Scotland, the My Name'5 Doddie Foundation, Medical Research Council Doctoral Student Training Fellowship [Ref: BST0010Z] and Academy of Medical Sciences grant [SGL023\1100].

PMID:35963713 | DOI:10.1016/j.ebiom.2022.104202

Biochim Biophys Acta Mol Cell Res. 2022 Aug 10:119331. doi: 10.1016/j.bbamcr.2022.119331. Online ahead of print.

ABSTRACT

Hearing loss in the elderly cause communication difficulties, decreased quality of life, isolation, loneliness and frustration. The aim of our study was to investigate the effect of drug repurposing candidates in aging mouse. The selected candidate drugs for age-related hearing loss (ARHL) included atorvastatin (AS) and sarpogrelate. Monotherapy or fixed dose combination (FDC) products were administered via oral gavage for 6 consecutive months. Auditory outcomes showed significant hearing preservation in AS-treated aging mice compared to aging control, especially in the early stages of ARHL in both 8 and 16 kHz frequencies. However, none of the FDC products were able to prevent ARHL regardless of AS involvement. In aging mice, damage and dysfunction of mitochondria was noted as well as reactive oxygen species overproduction leading to oxidative stress and intrinsic apoptosis. These processes of ARHL were significantly prevented with administration of AS. Normal structures of mitochondria were maintained, and antioxidant activity were proceeded by activation of HSF1/Sirt1 pathway. Our study suggests that AS is a promising drug repurposing candidate to delay the progression of ARHL.

PMID:35963547 | DOI:10.1016/j.bbamcr.2022.119331

J Control Release. 2022 Aug 10:S0168-3659(22)00514-4. doi: 10.1016/j.jconrel.2022.08.009. Online ahead of print.

ABSTRACT

Since the recent clinical approval of siRNA-based drugs and COVID-19 mRNA vaccines, the potential of RNA therapeutics for patient healthcare has become widely accepted. Lipid nanoparticles (LNPs) are currently the most advanced nanocarriers for RNA packaging and delivery. Nevertheless, the intracellular delivery efficiency of state-of-the-art LNPs remains relatively low and safety- and immunogenicity concerns with synthetic lipid components persist, altogether rationalizing the exploration of alternative LNP compositions. In addition, there is an interest in exploiting LNP technology for simultaneous encapsulation of small molecule drugs and RNA in a single nanocarrier. Here, we describe how well-known tricyclic cationic amphiphilic drugs (CADs) can be repurposed as both structural and functional components of lipid-based NPs for mRNA formulation, further referred to as CADosomes. We demonstrate that selected CADs, such as tricyclic antidepressants and antihistamines, self-assemble with the widely-used helper lipid DOPE to form cationic lipid vesicles for subsequent mRNA complexation and delivery, without the need for prior lipophilic derivatization. Selected CADosomes enabled efficient mRNA delivery in various in vitro cell models, including easy-to-transfect cancer cells (e.g. human cervical carcinoma HeLa cell line) as well as hard-to-transfect primary cells (e.g. primary bovine corneal epithelial cells), outperforming commercially available cationic liposomes and state-of-the-art LNPs. In addition, using the antidepressant nortriptyline as a model compound, we show that CADs can maintain their pharmacological activity upon CADosome incorporation. Furthermore, in vivo proof-of-concept was obtained, demonstrating CADosome-mediated mRNA delivery in the corneal epithelial cells of rabbit eyes, which could pave the way for future applications in ophthalmology. Based on our results, the co-formulation of CADs, helper lipids and mRNA into lipid-based nanocarriers is proposed as a versatile and straightforward approach for the rational development of drug combination therapies.

PMID:35963467 | DOI:10.1016/j.jconrel.2022.08.009

Infect Disord Drug Targets. 2022 Aug 11. doi: 10.2174/1871526522666220811114816. Online ahead of print.

ABSTRACT

BACKGROUND: COVID-19, caused by SARS-corona virus-2, is a global wide expanded public health risk at a bizarre level. In this current situation, COVID-19 became a serious emerging pandemic. Choosing drug reusing is a crucial step in identifying the new uses of old established drugs. To achieve a significant and healthy way of treatment in COVID patients within a short duration, drug repurposing is a novel method.

OBJECTIVE: The present study concentrated on the molecular docking of thalidomide and its analogues and Apremilast against Coronavirus infectious symptoms, evaluated on virus proteins (Spike Protein, 3cl Protease, Nucleocapsids).

METHODS: The present study explores the possibility of repurposing thalidomide for the treatment of SARS-COV-2 infection by assessing and confirming with docking affinity scores of thalidomide & its analogues and Apremilast, with spike protein, 3cl protease, and nucleocapsids.

RESULTS: From the study results, thalidomide, pomalidomide, lenalidomide, and Apremilast exhibited better binding affinity to N Protein (4KXJ), Protease (4WY3) and Spike Protein (5WRG). In comparison of targets, N Protein - 4KXJ is the best for the four ligands. It is finalized that all four ligands (Thalidomide - -8.6, Pomalidomide - -8.8, Lenalidomide,and - -8.2,and Apremilast - -8.1) have good docking scores with the target N Protein.

CONCLUSION: The present study shows confirmation that thalidomide and its analogues and apremilast as a better fit for treating high risk patients of COVID -19 viral infection which are supposed to promote beneficial effects for both respiratory illnesses like COVID-19 symptoms as well as improve the pathological state of condition.

PMID:35959615 | DOI:10.2174/1871526522666220811114816

MedComm (2020). 2022 Aug 9;3(3):e157. doi: 10.1002/mco2.157. eCollection 2022 Sep.

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS-CoV-2-induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID-19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS-CoV-2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID-19 metabolism. SARS-CoV-2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS-CoV-2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID-19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS-CoV-2-induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID-19 pandemic.

PMID:35958432 | PMC:PMC9363584 | DOI:10.1002/mco2.157

Int J Mol Sci. 2022 Aug 5;23(15):8725. doi: 10.3390/ijms23158725.

ABSTRACT

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders' views on AI for therapy discovery in CDG.

PMID:35955863 | DOI:10.3390/ijms23158725

Int J Mol Sci. 2022 Jul 28;23(15):8322. doi: 10.3390/ijms23158322.

ABSTRACT

Cell-penetrating peptides (CPP) have been shown to be efficient in the transport of cargoes into the cells, namely siRNA and DNA, proteins and peptides, and in some cases, small therapeutics. These peptides have emerged as a solution to increase drug concentrations in different tissues and various cell types, therefore having a relevant therapeutic relevance which led to clinical trials. One of them, MAP, is a model amphipathic peptide with an α-helical conformation and both hydrophilic and hydrophobic residues in opposite sides of the helix. It is composed of a mixture of alanines, leucines, and lysines (KLALKLALKALKAALKLA). The CPP MAP has the ability to translocate oligonucleotides, peptides and small proteins. However, taking advantage of its unique properties, in recent years innovative concepts were developed, such as in silico studies of modelling with receptors, coupling and repurposing drugs in the central nervous system and oncology, or involving the construction of dual-drug delivery systems using nanoparticles. In addition to designs of MAP-linked vehicles and strategies to achieve highly effective yet less toxic chemotherapy, this review will be focused on unique molecular structure and how it determines its cellular activity, and also intends to address the most recent and frankly motivating issues for the future.

PMID:35955457 | DOI:10.3390/ijms23158322

Cancers (Basel). 2022 Jul 29;14(15):3705. doi: 10.3390/cancers14153705.

ABSTRACT

Glioblastoma (GBM) remains one of the most difficult tumors to treat. The mean overall survival rate of 15 months and the 5-year survival rate of 5% have not significantly changed for almost 2 decades. Despite progress in understanding the pathophysiology of the disease, no new effective treatments to combine with radiation therapy after surgical tumor debulking have become available since the introduction of temozolomide in 1999. One of the main reasons for this is the scarcity of compounds that cross the blood-brain barrier (BBB) and reach the brain tumor tissue in therapeutically effective concentrations. In this review, we focus on the role of the BBB and its importance in developing brain tumor treatments. Moreover, we discuss drug repurposing, a drug discovery approach to identify potential effective candidates with optimal pharmacokinetic profiles for central nervous system (CNS) penetration and that allows rapid implementation in clinical trials. Additionally, we provide an overview of repurposed candidate drug currently being investigated in GBM at the preclinical and clinical levels. Finally, we highlight the importance of phase 0 trials to confirm tumor drug exposure and we discuss emerging drug delivery technologies as an alternative route to maximize therapeutic efficacy of repurposed candidate drug.

PMID:35954371 | DOI:10.3390/cancers14153705

Drug Res (Stuttg). 2022 Aug 11. doi: 10.1055/a-1886-2094. Online ahead of print.

ABSTRACT

BACKGROUND: Coronaviruses are emerging threats for human health, as demonstrated by the ongoing coronavirus disease 2019 (COVID-19) pandemic that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 is closely related to SARS-CoV-1, which was the cause of the 2002-2004 SARS outbreak, but SARS-CoV-1 has been the subject of a relatively limited number of studies. Understanding the potential pathways and molecular targets of SARS-CoV-1 will contribute to current drug repurposing strategies by helping to predict potential drug-disease associations.

METHODS: A microarray dataset, GSE1739, of 10 SARS patients and 4 healthy controls was downloaded from NCBI's GEO repository, and differential expression was identified using NCBI's GEO2R software. Pathway and enrichment analysis of the differentially expressed genes was carried out using Ingenuity Pathway Analysis and Gene Set Enrichment Analysis, respectively.

RESULTS: Our findings show that the drugs dexamethasone, filgrastim, interferon alfacon-1, and levodopa were among the most significant upstream regulators of differential gene expression in SARS patients, while neutrophil degranulation was the most significantly enriched pathway.

CONCLUSION: An enhanced understanding of the pathways and molecular targets of SARS-CoV-1 in humans will contribute to current and future drug repurposing strategies, which are an essential tool to combat rapidly emerging health threats.

PMID:35952682 | DOI:10.1055/a-1886-2094

PLoS Comput Biol. 2022 Aug 11;18(8):e1010367. doi: 10.1371/journal.pcbi.1010367. Online ahead of print.

ABSTRACT

Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-based compound screening and drug repurposing. State-of-the-art machine learning methods use a small number of fixed cell lines as a surrogate for predicting actual expressions in a new cell type or tissue, although it is well known that drug responses depend on a cellular context. Thus, the existing approach has limitations when applied to personalized medicine, especially for many understudied diseases whose molecular profiles are dramatically different from those characterized in the training data. Besides the gene expression, dose-dependent cell viability is another important phenotype readout and is more informative than conventional summary statistics (e.g., IC50) for characterizing clinical drug efficacy and toxicity. However, few computational methods can reliably predict the dose-dependent cell viability. To address the challenges mentioned above, we designed a new deep learning model, MultiDCP, to predict cellular context-dependent gene expressions and cell viability on a specific dosage. The novelties of MultiDCP include a knowledge-driven gene expression profile transformer that enables context-specific phenotypic response predictions of novel cells or tissues, integration of multiple diverse labeled and unlabeled omics data, the joint training of the multiple prediction tasks, and a teacher-student training procedure that allows us to utilize unreliable data effectively. Comprehensive benchmark studies suggest that MultiDCP outperforms state-of-the-art methods with unseen cell lines that are dissimilar from the cell lines in the supervised training in terms of gene expressions. The predicted drug-induced gene expressions demonstrate a stronger predictive power than noisy experimental data for downstream tasks. Thus, MultiDCP is a useful tool for transcriptomics-based drug repurposing and compound screening that currently rely on noisy high-throughput experimental data. We applied MultiDCP to repurpose individualized drugs for Alzheimer's disease in terms of efficacy and toxicity, suggesting that MultiDCP is a potentially powerful tool for personalized drug discovery.

PMID:35951653 | DOI:10.1371/journal.pcbi.1010367

Nat Commun. 2022 Aug 9;13(1):4678. doi: 10.1038/s41467-022-32205-3.

ABSTRACT

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.

PMID:35945222 | DOI:10.1038/s41467-022-32205-3

Brain. 2022 Aug 9:awac290. doi: 10.1093/brain/awac290. Online ahead of print.

ABSTRACT

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at approximately 450,000 CpG sites in 9,732 middle-aged to older adults from 14 community-based studies. Single-CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single-CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5), and colocalized with FOLH1 expression in brain (posterior probability =0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single-CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis, and multi-omics colocalization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug repositioning analysis indicated antihyperlipidemic agents, more specifically peroxisome proliferator-activated receptor alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood brain barrier disruption.

PMID:35943854 | DOI:10.1093/brain/awac290

Comput Chem Eng. 2022 Aug 4:107947. doi: 10.1016/j.compchemeng.2022.107947. Online ahead of print.

ABSTRACT

Given that the usual process of developing a new vaccine or drug for COVID-19 demands significant time and funds, drug repositioning has emerged as a promising therapeutic strategy. We propose a method named DRPADC to predict novel drug-disease associations effectively from the original sparse drug-disease association adjacency matrix. Specifically, DRPADC processes the original association matrix with the WKNKN algorithm to reduce its sparsity. Furthermore, multiple types of similarity information are fused by a CKA-MKL algorithm. Finally, a compressed sensing algorithm is used to predict the potential drug-disease (virus) association scores. Experimental results show that DRPADC has superior performance than several competitive methods in terms of AUC values and case studies. DRPADC achieved the AUC value of 0.941, 0.955 and 0.876 in Fdataset, Cdataset and HDVD dataset, respectively. In addition, the conducted case studies of COVID-19 show that DRPADC can predict drug candidates accurately.

PMID:35942213 | PMC:PMC9349049 | DOI:10.1016/j.compchemeng.2022.107947

J Biol Eng. 2022 Aug 8;16(1):21. doi: 10.1186/s13036-022-00296-7.

ABSTRACT

BACKGROUND: Recently, drug repositioning has received considerable attention for its advantage to pharmaceutical industries in drug development. Artificial intelligence techniques have greatly enhanced drug reproduction by discovering therapeutic drug profiles, side effects, and new target proteins. However, as the number of drugs increases, their targets and enormous interactions produce imbalanced data that might not be preferable as an input to a prediction model immediately.

METHODS: This paper proposes a novel scheme for predicting drug-target interactions (DTIs) based on drug chemical structures and protein sequences. The drug Morgan fingerprint, drug constitutional descriptors, protein amino acid composition, and protein dipeptide composition were employed to extract the drugs and protein's characteristics. Then, the proposed approach for extracting negative samples using a support vector machine one-class classifier was developed to tackle the imbalanced data problem feature sets from the drug-target dataset. Negative and positive samplings were constructed and fed into different prediction algorithms to identify DTIs. A 10-fold CV validation test procedure was applied to assess the predictability of the proposed method, in addition to the study of the effectiveness of the chemical and physical features in the evaluation and discovery of the drug-target interactions.

RESULTS: Our experimental model outperformed existing techniques concerning the curve for receiver operating characteristic (AUC), accuracy, precision, recall F-score, mean square error, and MCC. The results obtained by the AdaBoost classifier enhanced prediction accuracy by 2.74%, precision by 1.98%, AUC by 1.14%, F-score by 3.53%, and MCC by 4.54% over existing methods.

PMID:35941686 | DOI:10.1186/s13036-022-00296-7

Struct Chem. 2022 Aug 3:1-24. doi: 10.1007/s11224-022-02020-z. Online ahead of print.

ABSTRACT

The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing.

PMID:35938064 | PMC:PMC9346052 | DOI:10.1007/s11224-022-02020-z

Front Genet. 2022 Jul 22;13:935286. doi: 10.3389/fgene.2022.935286. eCollection 2022.

ABSTRACT

This study explored the prognostic and therapeutic potentials of multiple Proteasome 26S Subunit, ATPase (PSMC) family of genes (PSMC1-5) in lung adenocarcinoma (LUAD) diagnosis and treatment. All the PSMCs were found to be differentially expressed (upregulated) at the mRNA and protein levels in LUAD tissues. The promoter and multiple coding regions of PSMCs were reported to be differentially and distinctly methylated, which may serve in the methylation-sensitive diagnosis of LUAD patients. Multiple somatic mutations (alteration frequency: 0.6-2%) were observed along the PSMC coding regions in LUAD tissues that could assist in the high-throughput screening of LUAD patients. A significant association between the PSMC overexpression and LUAD patients' poor overall and relapse-free survival (p < 0.05; HR: >1.3) and individual cancer stages (p < 0.001) was discovered, which justifies PSMCs as the ideal targets for LUAD diagnosis. Multiple immune cells and modulators (i.e., CD274 and IDO1) were found to be associated with the expression levels of PSMCs in LUAD tissues that could aid in formulating PSMC-based diagnostic measures and therapeutic interventions for LUAD. Functional enrichment analysis of neighbor genes of PSMCs in LUAD tissues revealed different genes (i.e., SLIRP, PSMA2, and NUDSF3) previously known to be involved in oncogenic processes and metastasis are co-expressed with PSMCs, which could also be investigated further. Overall, this study recommends that PSMCs and their transcriptional and translational products are potential candidates for LUAD diagnostic and therapeutic measure discovery.

PMID:35938038 | PMC:PMC9353525 | DOI:10.3389/fgene.2022.935286

Front Neurol. 2022 Jul 22;13:920408. doi: 10.3389/fneur.2022.920408. eCollection 2022.

ABSTRACT

Investigation of neuroimmune interactions is one of the most developing areas in the study of multiple sclerosis pathogenesis. Recent evidence suggests the possibility of modulating neuroinflammation by targeting biogenic amine receptors. It has been shown that selective serotonin reuptake inhibitor fluoxetine modulates innate and adaptive immune system cells' function and can reduce experimental autoimmune encephalomyelitis and multiple sclerosis severity. This brief report discusses the immune mechanisms underlying the multiple sclerosis pathogenesis and the influence of fluoxetine on them. The retrospective data on the impact of fluoxetine treatment on the course of multiple sclerosis are also presented. The results of this and other studies suggest that fluoxetine could be considered an additional therapy to the standard first-line disease-modifying treatment for relapsing-remitting multiple sclerosis.

PMID:35937048 | PMC:PMC9355384 | DOI:10.3389/fneur.2022.920408

Front Pharmacol. 2022 Jul 22;13:898067. doi: 10.3389/fphar.2022.898067. eCollection 2022.

ABSTRACT

Gastrointestinal disorders in Parkinson's disease (PD) have been associated with neuronal alteration in the plexus of the gut. We previously demonstrated the immunomodulatory effect of female hormones to treat enteric neurodegeneration in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of PD. This study made the hypothesis of obtaining similar neuroprotection as with hormone treatments by affecting steroidogenesis with two 5α-reductase inhibitors, finasteride and dutasteride. These drugs are approved to treat benign prostatic hyperplasia and alopecia and display mitochondrial effects. In MPTP-treated mice, the dopaminergic and vasoactive intestinal peptide (VIP) neurons alteration was prevented by finasteride and dutasteride, while the increase in proinflammatory macrophages density was inhibited by dutasteride treatment but not finasteride. NF-κB response, oxidative stress, and nitric oxide and proinflammatory cytokines production in vitro were only prevented by dutasteride. In addition, mitochondrial production of free radicals, membrane depolarization, decreased basal respiration, and ATP production were inhibited by dutasteride, while finasteride had no effect. In conclusion, the present results indicate that dutasteride treatment prevents enteric neuronal damages in the MPTP mouse model, at least in part through anti-inflammatory and mitochondrial effects. This suggests that drug repurposing of dutasteride might be a promising avenue to treat enteric neuroinflammation in early PD.

PMID:35935876 | PMC:PMC9355275 | DOI:10.3389/fphar.2022.898067

Front Pharmacol. 2022 Jul 22;13:909460. doi: 10.3389/fphar.2022.909460. eCollection 2022.

ABSTRACT

GHB and GBL are highly accessible recreational drugs of abuse with a high risk of adverse effects and mortality while no specific antidotes exist. These components can also be found in the clinical setting, beverages, and cosmetic products, leading to unwanted exposures and further intoxications. As the structural analogue of GABA, GHB is suggested as the primary mediator of GHB/GBL effects. We further suggest that GBL might be as critical as GHB in this process, acting through PPARγ as its receptor. Moreover, PPARγ and PON (i.e., the GHB-GBL converting enzyme) can be targeted for GHB/GBL addiction and intoxication, leading to modulation of the GHB-GBL balance and blockage of their effects. We suggest that repurposing substances with lactone moiety such as bacterial lactones, sesquiterpene lactones, and statins might lead to potential therapeutic options as they occupy the active sites of PPARγ and PON and interfere with the GHB-GBL balance. In conclusion, this hypothesis improves the GHB/GBL mechanism of action, suggests potential therapeutic options, and highlights the necessity of classifying GBL as a controlled substance.

PMID:35935832 | PMC:PMC9354891 | DOI:10.3389/fphar.2022.909460

Curr Res Microb Sci. 2022;3:100158. doi: 10.1016/j.crmicr.2022.100158. Epub 2022 Jul 30.

ABSTRACT

Sublineages of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) Omicron variants continue to amass mutations in the spike (S) glycoprotein, which leads to immune evasion and rapid spread of the virus across the human population. Here we demonstrate the susceptibility of the Omicron variant BA.1 (B.1.1.529.1) to four repurposable drugs, Methylene blue (MB), Mycophenolic acid (MPA), Posaconazole (POS), and Niclosamide (Niclo) in post-exposure treatments of primary human airway cell cultures. MB, MPA, POS, and Niclo are known to block infection of human nasal and bronchial airway epithelial explant cultures (HAEEC) with the Wuhan strain, and four variants of concern (VoC), Alpha (B.1.1.7), Beta (B.1.351), Gamma (B.1.1.28), Delta (B.1.617.2) (Weiss et al., 2021, Murer et al., 2022). Our results here not only reinforce the broad anti-coronavirus effects of MB, MPA, POS and Niclo, but also demonstrate that the Omicron variant BA.1 (B.1.1.529.1) sheds infectious virus from HAEEC over at least 15 d, and maintains both intracellular and extracellular viral genomic RNA without overt toxicity, suggesting viral persistence. The data emphasize the potential of repurposable drugs against COVID-19.

PMID:35935678 | PMC:PMC9338451 | DOI:10.1016/j.crmicr.2022.100158