Antimicrob Agents Chemother. 2024 Aug 28:e0034424. doi: 10.1128/aac.00344-24. Online ahead of print.

ABSTRACT

Limited treatment options and multidrug-resistant (MDR) Klebsiella pneumoniae present a significant therapeutic challenge, underscoring the need for novel approaches. Drug repurposing is a promising tool for augmenting the activity of many antibiotics. This study aimed to identify novel synergistic drug combinations against K. pneumoniae based on drug repurposing. We used the clinically isolated GN 172867 MDR strain of K. pneumoniae to determine the reversal resistance activity of zidovudine (AZT). The combined effects of AZT and various antibiotics, including nitrofurantoin (NIT) and omadacycline (OMC), were examined using the checkerboard method, growth curves, and crystal violet assays to assess biofilms. An in vitro combination activity testing was carried out in 12 isolates of K. pneumoniae. In vivo murine urinary tract and lung infection models were used to evaluate the therapeutic effects of AZT + NIT and AZT + OMC, respectively. The fractional inhibitory concentration index and growth curve demonstrated that AZT synergized with NIT or OMC against K. pneumoniae strains. In addition, AZT + NIT inhibited biofilm formation and cleared mature biofilms. In vivo, compared with untreated GN 172867-infected mice, AZT + NIT and AZT + OMC treatment decreased colony counts in multiple tissues (P < 0.05) and pathological scores in the bladder and kidneys (P < 0.05) and increased the survival rate by 60% (P < 0.05). This study evaluated the combination of AZT and antibiotics to treat drug-resistant K. pneumoniae infections and found novel drug combinations for the treatment of acute urinary tract infections. These findings suggest that AZT may exert significant anti-resistance activity.

PMID:39194261 | DOI:10.1128/aac.00344-24

EBioMedicine. 2024 Aug 26;107:105314. doi: 10.1016/j.ebiom.2024.105314. Online ahead of print.

ABSTRACT

BACKGROUND: Medications prescribed for chronic diseases can lead to short-term neuropsychiatric symptoms, but their long-term effects on brain structures and psychiatric conditions remain unclear.

METHODS: We comprehensively analyzed the FDA Adverse Event Reporting System database and conducted drug target Mendelian Randomization (MR) studies on six categories of common drugs, 477 brain imaging-derived phenotypes (IDPs) and eight psychiatric disorders. Genetic instruments were extracted from expression quantitative trait loci (eQTLs) in blood, brain, and other target tissues, protein quantitative trait loci (pQTLs) in blood, and genome-wide association studies (GWAS) of hemoglobin and cholesterol. Summary statistics for brain IDPs, psychiatric disorders, and gut microbiome were obtained from the BIG40, Psychiatric Genomics Consortium, and MiBioGen. A two-step MR and mediation analysis were employed to screen possible mediators of drug-IDP effects from 119 gut microbiota genera and identify their mediation proportions.

FINDINGS: Among 19 drug classes, six drugs were found to be associated with higher risks of psychiatric adverse events, while 11 drugs were associated with higher risks of gastrointestinal adverse events in the FAERS analysis. We identified ten drug-psychiatric disorder associations, 202 drug-IDP associations, 16 drug-microbiota associations, and four drug-microbiota-IDP causal links. For example, PPARG activation mediated HbA1c reduction caused a higher risk of bipolar disorder (BD) II. Genetically proxied GLP-1R agonists were significantly associated with an increase in the volume of the CA3-head of the right hippocampus and the area of the left precuneus cortex, both of which have been shown to correlate with cognition in previous studies.

INTERPRETATION: Common drugs may affect brain structure and risk of psychiatric disorder. Oral medications in particular may exert some of these effects by influencing gut microbiota. This study calls for greater attention to be paid to the neuropsychiatric adverse effects of drugs and encourages drug repurposing.

FUNDING: National Natural Science Foundation of China (grant No. 82330035, 82130043, 82172685, and 82001223), National Natural Science Foundation of Hunan Province (grant No. 2021SK1010), and the Science Foundation for Distinguished Young Scholars of Changsha (grant No. kq2209006).

PMID:39191171 | DOI:10.1016/j.ebiom.2024.105314

Inflammopharmacology. 2024 Aug 27. doi: 10.1007/s10787-024-01553-5. Online ahead of print.

ABSTRACT

Fluoxetine, being a selective serotonin uptake inhibitor, has been broadly used to modulate the neurotransmission of serotonin in the central nervous system. Fluoxetine performs a number of crucial central nervous system-related tasks, including neuroprotective effects against microglial neurotoxicity and protecting oxidative cell damage produced by stress in a variety of stress-related unfavourable health disorders. Studies have shown that the drug (fluoxetine) also has analgesic and anti-inflammatory characteristics in addition to its other basic benefits. Furthermore, existing treatment approaches (NSAIDs, DMARDs, corticosteroids and other immunosuppressants) for RA have limited effects on chronic immunological models. These facts served as the basis for carrying out a study on fluoxetine to explore its therapeutics in a chronic inflammatory rat model called Freund's complete adjuvant (FCA)-induced arthritis. The therapeutic effect of the fluoxetine in FCA-induced arthritic rats was assessed by paw volume, paw diameter, arthritic index and body weight at specific days through the experiment of 28 days. These findings were further co-investigated by haematological, biochemical parameters and radiographic imaging at the end of experiment. Furthermore, the modulatory effects on gene expression (NF-κB, PGE2, COX2, INF-γ, IL-4 and IL-10) and antioxidant properties were gritty using qRT-PCR and ELISA kits, respectively, in experimental arthritic rats. Fluoxetine at 10, 20 and 40 mg/kg doses reduced (p < 0.001) the serum concentration of C-reactive protein and rheumatoid factor as well as suppressed the expression of PGE2, NF-kB, COX2 and INF-γ when compared to arthritic control. Moreover, fluoxetine (at higher doses) caused significant rise of IL-4 and IL-10. These findings supported the anti-inflammatory and antioxidant potential of fluoxetine in chronic inflammatory model and endorsed it for clinical trials.

PMID:39192161 | DOI:10.1007/s10787-024-01553-5

World J Pediatr. 2024 Aug 28. doi: 10.1007/s12519-024-00834-x. Online ahead of print.

ABSTRACT

BACKGROUND: Global pediatric healthcare reveals significant morbidity and mortality rates linked to respiratory, cardiac, and gastrointestinal disorders in children and newborns, mostly due to the complexity of therapeutic management in pediatrics and neonatology, owing to the lack of suitable dosage forms for these patients, often rendering them "therapeutic orphans". The development and application of pediatric drug formulations encounter numerous challenges, including physiological heterogeneity within age groups, limited profitability for the pharmaceutical industry, and ethical and clinical constraints. Many drugs are used unlicensed or off-label, posing a high risk of toxicity and reduced efficacy. Despite these circumstances, some regulatory changes are being performed, thus thrusting research innovation in this field.

DATA SOURCES: Up-to-date peer-reviewed journal articles, books, government and institutional reports, data repositories and databases were used as main data sources.

RESULTS: Among the main strategies proposed to address the current pediatric care situation, nanotechnology is specially promising for pediatric respiratory diseases since they offer a non-invasive, versatile, tunable, site-specific drug release. Tissue engineering is in the spotlight as strategy to address pediatric cardiac diseases, together with theragnostic systems. The integration of nanotechnology and theragnostic stands poised to refine and propel nanomedicine approaches, ushering in an era of innovative and personalized drug delivery for pediatric patients. Finally, the intersection of drug repurposing and artificial intelligence tools in pediatric healthcare holds great potential. This promises not only to enhance efficiency in drug development in general, but also in the pediatric field, hopefully boosting clinical trials for this population.

CONCLUSIONS: Despite the long road ahead, the deepening of nanotechnology, the evolution of tissue engineering, and the combination of traditional techniques with artificial intelligence are the most recently reported strategies in the specific field of pediatric therapeutics.

PMID:39192003 | DOI:10.1007/s12519-024-00834-x

Annu Rev Genomics Hum Genet. 2024 Aug;25(1):239-257. doi: 10.1146/annurev-genom-010423-095636.

ABSTRACT

Osteoarthritis is the most prevalent whole-joint degenerative disorder, and is characterized by the degradation of articular cartilage and the underlying bone structures. Almost 600 million people are affected by osteoarthritis worldwide. No curative treatments are available, and management strategies focus mostly on pain relief. Here, we provide a comprehensive overview of the available human genetic and functional genomics studies for osteoarthritis to date and delineate how these studies have helped shed light on disease etiopathology. We highlight genetic discoveries from genome-wide association studies and provide a detailed overview of molecular-level investigations in osteoarthritis tissues, including methylation-, transcriptomics-, and proteomics-level analyses. We review how functional genomics data from different molecular levels have helped to prioritize effector genes that can be used as drug targets or drug-repurposing opportunities. Finally, we discuss future directions with the potential to drive a step change in osteoarthritis research.

PMID:39190913 | DOI:10.1146/annurev-genom-010423-095636

Ageing Res Rev. 2024 Aug 24:102465. doi: 10.1016/j.arr.2024.102465. Online ahead of print.

ABSTRACT

Neurodegenerative diseases (NDDs) are identified by the progressive deterioration of neurons and a subsequent decline in cognitive function, creating an enormous burden on the healthcare system globally. Neuroinflammation is an intricate procedure that initiates the immune response in the central nervous system (CNS) and significantly impacts the expansion of NDDs. This study scrutinizes the complicated interaction between neuronal degeneration and neuroinflammation, with an appropriate emphasis on their reciprocal impacts. It also describes how neuroinflammatory reactions in NDDs are controlled by activating certain pro-inflammatory transcription factors, including p38 MAPK, FAF1, Toll-like receptors (TLRs), and STAT3. Alternatively, it evaluates the impact of pro-survival transcription factors, such as the SOCS pathway, YY1, SIRT1, and MEF2, which provide neuroprotective protection against damage triggered by neuroinflammation. Moreover, we study the feasibility of accommodating drug repositioning as a therapeutic approach for treating neuroinflammatory disorders. This suggests the use of existing medications for novel utilization in the treatment of NDDs. Furthermore, the study intends to reveal novel biomarkers of neuroinflammation that contribute fundamental observation for the initial detection and diagnosis of these disorders. This study aims to strengthen therapy interference and augment patient outcomes by combining ongoing data and evaluating novel therapeutic and diagnostic approaches. The goal is to devote the growth of an effective strategy to reducing the impact of neuroinflammation on neuronal protection in NDDs.

PMID:39187022 | DOI:10.1016/j.arr.2024.102465

Eur J Pharm Biopharm. 2024 Aug 24:114473. doi: 10.1016/j.ejpb.2024.114473. Online ahead of print.

ABSTRACT

Hydroxychloroquine sulfate (HCQ) is currently being repurposed for cancer treatment. The antitumor mechanism of HCQ is inhibition of cellular autophagy, but its therapeutic potential is severely limited by poor solubility, lack of tumor targeting and lower cellular uptake. Therefore, utilization of human H-chain apoferritin (HFn) composed only of heavy subunits is an attractive approach for tumor targeting drug delivery. This study focused on pH-triggered encapsulation of HCQ within the inner cavity of HFn to form HFn@HCQ nanoparticles for tumor-targeted drug delivery. Characterization using a range of techniques has been used to confirm the successful establishment of HFn@HCQ. HFn@HCQ exhibited pH-responsive release behavior, with almost no drug release at pH 7.4, but 80% release at pH 5.0. Owing to its intrinsic binding to transferrin receptor 1 (TfR1), HFn@HCQ was significantly internalized through TfR1-mediated endocytosis, with a 4.4-fold difference of internalization amount across cell lines. Additionally, HFn@HCQ enhanced the antitumor effect against four different cancer cell lines when compared against HCQ alone, especially in TfR1 high-expressing cells, where the inhibitory effect was 3-fold higher than free HCQ. The autophagy inhibition of HFn@HCQ has been demonstrated, which is a major pathway to induce cancer cell death. According to current findings, HFn based drug delivery is a promising strategy to target and kill TfR1 overexpressing tumor cells.

PMID:39186959 | DOI:10.1016/j.ejpb.2024.114473

Front Immunol. 2024 Aug 9;15:1406041. doi: 10.3389/fimmu.2024.1406041. eCollection 2024.

ABSTRACT

BACKGROUND: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the spine and sacroiliac joints. Recent genetic studies suggest certain plasma proteins may play a causal role in AS development. This study aims to identify and characterize these proteins using Mendelian randomization (MR) and colocalization analyses.

METHODS: Plasma protein data were obtained from recent publications in Nature Genetics, integrating data from five previous GWAS datasets, including 738 cis-pQTLs for 734 plasma proteins. GWAS summary data for AS were sourced from IGAS and other European cohorts. MR analyses were conducted using "TwoSampleMR" to assess causal links between plasma protein levels and AS. Colocalization analysis was performed with the coloc R package to identify shared genetic variants. Sensitivity analyses and protein-protein interaction (PPI) network analyses were conducted to validate findings and explore therapeutic targets. We performed Phenome-wide association study (PheWAS) to examine the potential side effects of drug protein on AS treatment.

RESULTS: After FDR correction, eight significant proteins were identified: IL7R, TYMP, IL12B, CCL8, TNFAIP6, IL18R1, IL23R, and ERAP1. Elevated levels of IL7R, IL12B, CCL8, IL18R1, IL23R, and ERAP1 increased AS risk, whereas elevated TYMP and TNFAIP6 levels decreased AS risk. Colocalization analysis indicated that IL23R, IL7R, and TYMP likely share causal variants with AS. PPI network analysis identified IL23R and IL7R as potential new therapeutic targets.

CONCLUSIONS: This study identified eight plasma proteins with significant associations with AS risk, suggesting IL23R, IL7R, and TYMP as promising therapeutic targets. Further research is needed to explore underlying mechanisms and potential for drug repurposing.

PMID:39185422 | PMC:PMC11341372 | DOI:10.3389/fimmu.2024.1406041

Res Sq [Preprint]. 2024 Aug 17:rs.3.rs-4750719. doi: 10.21203/rs.3.rs-4750719/v1.

ABSTRACT

Neurodegenerative pathologies such as Alzheimer's disease, Parkinson's disease, Huntington's disease, Amyotrophic lateral sclerosis, Multiple sclerosis, HIV-associated neurocognitive disorder, and others significantly affect individuals, their families, caregivers, and healthcare systems. While there are no cures yet, researchers worldwide are actively working on the development of novel treatments that have the potential to slow disease progression, alleviate symptoms, and ultimately improve the overall health of patients. Huge volumes of new scientific information necessitate new analytical approaches for meaningful hypothesis generation. To enable the automatic analysis of biomedical data we introduced AGATHA, an effective AI-based literature mining tool that can navigate massive scientific literature databases, such as PubMed. The overarching goal of this effort is to adapt AGATHA for drug repurposing by revealing hidden connections between FDA-approved medications and a health condition of interest. Our tool converts the abstracts of peer-reviewed papers from PubMed into multidimensional space where each gene and health condition are represented by specific metrics. We implemented advanced statistical analysis to reveal distinct clusters of scientific terms within the virtual space created using AGATHA-calculated parameters for selected health conditions and genes. Partial Least Squares Discriminant Analysis was employed for categorizing and predicting samples (122 diseases and 20889 genes) fitted to specific classes. Advanced statistics were employed to build a discrimination model and extract lists of genes specific to each disease class. Here we focus on drugs that can be repurposed for dementia treatment as an outcome of neurodegenerative diseases. Therefore, we determined dementia-associated genes statistically highly ranked in other disease classes. Additionally, we report a mechanism for detecting genes common to multiple health conditions. These sets of genes were classified based on their presence in biological pathways, aiding in selecting candidates and biological processes that are exploitable with drug repurposing.

PMID:39184100 | PMC:PMC11343300 | DOI:10.21203/rs.3.rs-4750719/v1

Microbiol Res. 2024 Aug 15;288:127879. doi: 10.1016/j.micres.2024.127879. Online ahead of print.

ABSTRACT

The emergence of plasmid-encoded colistin resistance mechanisms, MCR-1, a phosphoethanolamine transferase, rendered colistin ineffective as last resort antibiotic against severe infections caused by clinical Gram-negative bacterial pathogens. Through screening FDA-approved drug library, we identified two structurally similar compounds, namely cetylpyridinium chloride (CET) and domiphen bromide (DOM), which potentiated colistin activity in both colistin-resistant and susceptible Enterobacterales. These compounds were found to insert their long carbon chain to a hydrophobic pocket of bacterial phosphoethanolamine transferases including MCR-1, competitively blocking the binding of lipid A tail for substrate recognition and modification, resulting in the increase of bacterial sensitivity to colistin. In addition, these compounds were also found to dissipate bacterial membrane potential leading to the increase of bacterial sensitivity to colistin. Importantly, combinational use of DOM with colistin exhibited remarkable protection of test animals against infections by colistin-resistant bacteria in both mouse thigh infection and sepsis models. For mice infected by colistin-susceptible bacteria, the combinational use of DOM and colistin enable us to use lower dose of colistin to for efficient treatment. These properties render DOM excellent adjuvant candidates that help transform colistin into a highly potent antimicrobial agent for treatment of colistin-resistant Gram-negative bacterial infections and allowed us to use of a much lower dosage of colistin to reduce its toxicity against colistin-susceptible bacterial infection such as carbapenem-resistant Enterobacterales.

PMID:39182419 | DOI:10.1016/j.micres.2024.127879

Sci Rep. 2024 Aug 24;14(1):19670. doi: 10.1038/s41598-024-70758-z.

ABSTRACT

Observational studies have suggested the potential benefits of several medications for Parkinson's disease (PD) and their potential for repurposing. However, the conclusions drawn from these studies are not entirely consistent. To address this inconsistency, we used the two-sample Mendelian randomization (MR) method to explore the putative causal relationships between 23 medications and the risk and progression of PD. We applied inverse-variance weighted meta-analysis (IVW) to combine MR estimates. Additionally, sensitivity analyses were conducted to evaluate the robustness of the results. Our genetic evidence suggests that thyroid preparations and calcium channel blockers reduce the risk of PD, and salicylic acid and derivatives slow the progression of PD motor symptoms. Additionally, genetic evidence also suggests that four medications were associated with PD risk or progression, but the sensitivity analysis revealed that three of the medications may have interference caused by reverse causality. Our findings suggest that there are weak causal relationships between several medications and the risk or progression of PD. Though further replication studies are needed to verify these findings, these new insights may help in understanding the etiology of the disease, generate new clues related to drug discovery, and quantify the risk of future drug intake.

PMID:39181920 | DOI:10.1038/s41598-024-70758-z

J Cheminform. 2024 Aug 23;16(1):103. doi: 10.1186/s13321-024-00897-y.

ABSTRACT

MOTIVATION: Computational techniques for drug-disease prediction are essential in enhancing drug discovery and repositioning. While many methods utilize multimodal networks from various biological databases, few integrate comprehensive multi-omics data, including transcriptomes, proteomes, and metabolomes. We introduce STRGNN, a novel graph deep learning approach that predicts drug-disease relationships using extensive multimodal networks comprising proteins, RNAs, metabolites, and compounds. We have constructed a detailed dataset incorporating multi-omics data and developed a learning algorithm with topological regularization. This algorithm selectively leverages informative modalities while filtering out redundancies.

RESULTS: STRGNN demonstrates superior accuracy compared to existing methods and has identified several novel drug effects, corroborating existing literature. STRGNN emerges as a powerful tool for drug prediction and discovery. The source code for STRGNN, along with the dataset for performance evaluation, is available at https://github.com/yuto-ohnuki/STRGNN.git .

PMID:39180095 | DOI:10.1186/s13321-024-00897-y

Nat Commun. 2024 Aug 24;15(1):7288. doi: 10.1038/s41467-024-51859-9.

ABSTRACT

Correctly identifying perturbed biological pathways is a critical step in uncovering basic disease mechanisms and developing much-needed therapeutic strategies. However, whether current tools are optimal for unbiased discovery of relevant pathways remains unclear. Here, we create "Benchmark" to critically evaluate existing tools and find that most function sub-optimally. We thus develop the "Pathway Ensemble Tool" (PET), which outperforms existing methods. Deploying PET, we identify prognostic pathways across 12 cancer types. PET-identified prognostic pathways offer additional insights, with genes within these pathways serving as reliable biomarkers for clinical outcomes. Additionally, normalizing these pathways using drug repurposing strategies represents therapeutic opportunities. For example, the top predicted repurposed drug for bladder cancer, a CDK2/9 inhibitor, represses cell growth in vitro and in vivo. We anticipate that using Benchmark and PET for unbiased pathway discovery will offer additional insights into disease mechanisms across a spectrum of diseases, enabling biomarker discovery and therapeutic strategies.

PMID:39179644 | DOI:10.1038/s41467-024-51859-9

Acta Crystallogr F Struct Biol Commun. 2024 Sep 1. doi: 10.1107/S2053230X24007039. Online ahead of print.

ABSTRACT

Crystallographic fragment screening has become a pivotal technique in structure-based drug design, particularly for bacterial targets with a crucial role in infectious disease mechanisms. The enzyme CdaA, which synthesizes an essential second messenger cyclic di-AMP (c-di-AMP) in many pathogenic bacteria, has emerged as a promising candidate for the development of novel antibiotics. To identify crystals suitable for fragment screening, CdaA enzymes from Streptococcus pneumoniae, Bacillus subtilis and Enterococcus faecium were purified and crystallized. Crystals of B. subtilis CdaA, which diffracted to the highest resolution of 1.1 Å, were used to perform the screening of 96 fragments, yielding data sets with resolutions spanning from 1.08 to 1.87 Å. A total of 24 structural hits across eight different sites were identified. Four fragments bind to regions that are highly conserved among pathogenic bacteria, specifically the active site (three fragments) and the dimerization interface (one fragment). The coordinates of the three active-site fragments were used to perform an in silico drug-repurposing screen using the OpenEye suite and the DrugBank database. This screen identified tenofovir, an approved drug, that is predicted to interact with the ATP-binding region of CdaA. Its inhibitory potential against pathogenic E. faecium CdaA has been confirmed by ITC measurements. These findings not only demonstrate the feasibility of this approach for identifying lead compounds for the design of novel antibacterial agents, but also pave the way for further fragment-based lead-optimization efforts targeting CdaA.

PMID:39177700 | DOI:10.1107/S2053230X24007039

Acta Crystallogr F Struct Biol Commun. 2024 Sep 1. doi: 10.1107/S2053230X24007027. Online ahead of print.

ABSTRACT

Brucella ovis is an etiologic agent of ovine epididymitis and brucellosis that causes global devastation in sheep, rams, goats, small ruminants and deer. There are no cost-effective methods for the worldwide eradication of ovine brucellosis. B. ovis and other protein targets from various Brucella species are currently in the pipeline for high-throughput structural analysis at the Seattle Structural Genomics Center for Infectious Disease (SSGCID), with the aim of identifying new therapeutic targets. Furthermore, the wealth of structures generated are effective tools for teaching scientific communication, structural science and biochemistry. One of these structures, B. ovis leucine-, isoleucine-, valine-, threonine- and alanine-binding protein (BoLBP), is a putative periplasmic amino acid-binding protein. BoLBP shares less than 29% sequence identity with any other structure in the Protein Data Bank. The production, crystallization and high-resolution structures of BoLBP are reported. BoLBP is a prototypical bacterial periplasmic amino acid-binding protein with the characteristic Venus flytrap topology of two globular domains encapsulating a large central cavity containing the peptide-binding region. The central cavity contains small molecules usurped from the crystallization milieu. The reported structures reveal the conformational flexibility of the central cavity in the absence of bound peptides. The structural similarity to other LBPs can be exploited to accelerate drug repurposing.

PMID:39177244 | DOI:10.1107/S2053230X24007027

Front Chem. 2024 Aug 8;12:1410882. doi: 10.3389/fchem.2024.1410882. eCollection 2024.

ABSTRACT

The exploration of non-cancer medications with potential anti-cancer activity offers a promising avenue for drug repurposing, accelerating the development of new oncological therapies. This study employs Quantitative Structure-Property Relationship (QSPR) modeling to identify and predict the anti-cancer efficacy of various non-cancer drugs, utilizing topological indices as key descriptors. Topological indices, which capture the molecular structure's geometric and topological characteristics, provide critical insights into the pharmacological interactions relevant to anti-cancer activity. By analyzing a comprehensive dataset of non-cancer medications, this research establishes robust QSPR models that correlate topological indices with anti-cancer activity. The models demonstrate significant predictive power, highlighting several non-cancer drugs with potential anti-cancer properties. Further, we will use linear, quadratic and logarithmic regression to understand the structures of anti-cancer drugs and strengthen our ability to manipulate the molecular structures. The findings underscore the utility of topological indices in drug repurposing strategies and pave the way for further experimental validation and clinical trials. This integrative approach enhances our understanding of drug action mechanisms and offers a cost-effective strategy for expanding the repertoire of anti-cancer agents.

PMID:39176073 | PMC:PMC11338857 | DOI:10.3389/fchem.2024.1410882

Life Sci. 2024 Aug 20:123001. doi: 10.1016/j.lfs.2024.123001. Online ahead of print.

ABSTRACT

Repurposing antidiabetic drugs for the treatment of Alzheimer's disease (AD) has emerged as a promising therapeutic strategy. This review examines the potential of repurposing antidiabetic drugs for AD treatment, focusing on preclinical evidence, clinical trials, and observational studies. In addition, the review aims to explore challenges and opportunities in repurposing antidiabetic drugs for AD, emphasizing the importance of well-designed clinical trials that consider patient selection criteria, refined outcome measures, adverse effects, and combination therapies to enhance therapeutic efficacy. Preclinical evidence suggests that glucagon-like peptide-1 (GLP-1) analogs, dipeptidyl peptidase-4 (DPP4) inhibitors, metformin, thiazolidinediones, and sodium-glucose co-transporter-2 (SGLT2) inhibitors exhibit neuroprotective effects in AD preclinical models. In preclinical studies, antidiabetic drugs have demonstrated neuroprotective effects by reducing amyloid beta (Aβ) plaques, tau hyperphosphorylation, neuroinflammation, and cognitive impairment. Antidiabetic drug classes, notably GLP-1 analogs and SGLT2 inhibitors, and a reduced risk of dementia in patients with diabetes mellitus. While the evidence for DPP4 inhibitors is mixed, some studies suggest a potential protective effect. On the other hand, alpha-glucosidase inhibitors (AGIs) and sulfonylureas may potentially increase the risk, especially in those experiencing recurrent hypoglycemic events. Repurposing antidiabetic drugs for AD is a promising therapeutic strategy, but challenges such as disease heterogeneity, limited biomarkers, and benefits versus risk evaluation need to be addressed. Ongoing clinical trials in mild cognitive impairment (MCI) and early AD patients without diabetes will be crucial in determining the clinical efficacy and safety of the antidiabetic drugs, paving the way for potential treatments for AD.

PMID:39173996 | DOI:10.1016/j.lfs.2024.123001

Int J Biol Macromol. 2024 Aug 20:134652. doi: 10.1016/j.ijbiomac.2024.134652. Online ahead of print.

ABSTRACT

Despite the WHO's recommended treatment regimen, challenges such as patient non-adherence and the emergence of drug-resistant strains persist with TB claiming 1.5 million lives annually. In this study, we propose a novel approach by targeting the DNA replication-machinery of M.tb through drug-repurposing. The β2-Sliding clamp (DnaN), a key component of this complex, emerges as a potentially vulnerable target due to its distinct structure and lack of human homology. Leveraging TBVS, we screened ~2600 FDA-approved drugs, identifying five potential DnaN inhibitors, by employing computational studies, including molecular-docking and molecular-dynamics simulations. The shortlisted compounds were subjected to in-vitro and ex-vivo studies, evaluating their anti-mycobacterial potential. Notably, Dicoumarol, Paromomycin, and Posaconazole exhibited anti-TB properties with a MIC value of 6.25, 3.12 and 50 μg/ml respectively, with Dicoumarol and Paromomycin, demonstrating efficacy in reducing live M.tb within macrophages. Biophysical analyses confirmed the strong binding-affinity of DnaNdrug complexes, validating our in-silico predictions. Moreover, RNA-Seq data revealed the upregulation of proteins associated with DNA repair and replication mechanisms upon Paromomycin treatment. This study explores repurposing FDA-approved drugs to target TB via the mycobacterial DNA replication-machinery, showing promising inhibitory effects. It sets the stage for further clinical research, demonstrating the potential of drug repurposing in TB treatment.

PMID:39173789 | DOI:10.1016/j.ijbiomac.2024.134652

Best Pract Res Clin Rheumatol. 2024 Aug 22:101988. doi: 10.1016/j.berh.2024.101988. Online ahead of print.

ABSTRACT

Rheumatic diseases, those that affect the musculoskeletal system, cause significant morbidity. Among risk factors of these diseases is a significant genetic component. Recent advances in high-throughput omics techniques now allow a comprehensive profiling of patients at a genetic level through genome-wide association studies. Without functional interpretation of variants identified through these studies, clinical insight remains limited. Strategies include statistical fine-mapping that refine the list of variants in loci associated with disease, whilst colocalization techniques attempt to attribute function to variants that overlap a genetically active chromatin annotation. Functional validation using genome editing techniques can be used to further refine genetic signals and identify key pathways in cell types relevant to rheumatic disease biology. Insight gained from the combination of genetic studies and functional validation can be used to improve precision medicine in rheumatic diseases by allowing risk prediction and drug repositioning.

PMID:39174375 | DOI:10.1016/j.berh.2024.101988

Med Res Rev. 2024 Aug 22. doi: 10.1002/med.22079. Online ahead of print.

ABSTRACT

Fenamates as classical nonsteroidal anti-inflammatory agents are widely used for relieving pain. Preclinical studies and epidemiological data highlight their chemo-preventive and chemotherapeutic potential for cancer. However, comprehensive reviews of fenamates in cancer are limited. To accelerate the repurposing of fenamates, this review summarizes the results of fenamates alone or in combination with existing chemotherapeutic agents. This paper also explores targets of fenamates in cancer therapy, including COX, AKR family, AR, gap junction, FTO, TEAD, DHODH, TAS2R14, ion channels, and DNA. Besides, this paper discusses other mechanisms, such as regulating Wnt/β-catenin, TGF-β, p38 MAPK, and NF-κB pathway, and the regulation of the expressions of Sp, EGR-1, NAG-1, ATF-3, ErbB2, AR, as well as the modulation of the tumor immune microenvironment. Furthermore, this paper outlined the structural modifications of fenamates, highlighting their potential as promising leads for anticancer drugs.

PMID:39171404 | DOI:10.1002/med.22079