J Chem Inf Model. 2024 Jun 5. doi: 10.1021/acs.jcim.4c00737. Online ahead of print.

ABSTRACT

Drug repositioning is a strategy of repurposing approved drugs for treating new indications, which can accelerate the drug discovery process, reduce development costs, and lower the safety risk. The advancement of biotechnology has significantly accelerated the speed and scale of biological data generation, offering significant potential for drug repositioning through biomedical knowledge graphs that integrate diverse entities and relations from various biomedical sources. To fully learn the semantic information and topological structure information from the biological knowledge graph, we propose a knowledge graph convolutional network with a heuristic search, named KGCNH, which can effectively utilize the diversity of entities and relationships in biological knowledge graphs, as well as topological structure information, to predict the associations between drugs and diseases. Specifically, we design a relation-aware attention mechanism to compute the attention scores for each neighboring entity of a given entity under different relations. To address the challenge of randomness of the initial attention scores potentially impacting model performance and to expand the search scope of the model, we designed a heuristic search module based on Gumbel-Softmax, which uses attention scores as heuristic information and introduces randomness to assist the model in exploring more optimal embeddings of drugs and diseases. Following this module, we derive the relation weights, obtain the embeddings of drugs and diseases through neighborhood aggregation, and then predict drug-disease associations. Additionally, we employ feature-based augmented views to enhance model robustness and mitigate overfitting issues. We have implemented our method and conducted experiments on two data sets. The results demonstrate that KGCNH outperforms competing methods. In particular, case studies on lithium and quetiapine confirm that KGCNH can retrieve more actual drug-disease associations in the top prediction results.

PMID:38837744 | DOI:10.1021/acs.jcim.4c00737

Skin Res Technol. 2024 Jun;30(6):e13736. doi: 10.1111/srt.13736.

NO ABSTRACT

PMID:38837501 | DOI:10.1111/srt.13736

Bioinformatics. 2024 Jun 5:btae346. doi: 10.1093/bioinformatics/btae346. Online ahead of print.

ABSTRACT

MOTIVATION: Accurately identifying the drug-target interactions (DTIs) is one of the crucial steps in the drug discovery and drug repositioning process. Currently, many computational-based models have already been proposed for DTI prediction and achieved some significant improvement. However, these approaches pay little attention to fuse the multi-view similarity networks related to drugs and targets in an appropriate way. Besides, how to fully incorporate the known interaction relationships to accurately represent drugs and targets is not well investigated. Therefore, there is still a need to improve the accuracy of DTI prediction models.

RESULTS: In this study, we propose a novel approach that employs Multi-view similarity network fusion strategy and deep Interactive attention mechanism to predict Drug-Target Interactions (MIDTI). First, MIDTI constructs multi-view similarity networks of drugs and targets with their diverse information and integrates these similarity networks effectively in an unsupervised manner. Then, MIDTI obtains the embeddings of drugs and targets from multi-type networks simultaneously. After that, MIDTI adopts the deep interactive attention mechanism to further learn their discriminative embeddings comprehensively with the known DTI relationships. Finally, we feed the learned representations of drugs and targets to the multilayer perceptron (MLP) model and predict the underlying interactions. Extensive results indicate that MIDTI significantly outperforms other baseline methods on the DTI prediction task. The results of the ablation experiments also confirm the effectiveness of the attention mechanism in the multi-view similarity network fusion strategy and the deep interactive attention mechanism.

AVAILABILITY: https://github.com/XuLew/MIDTI.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:38837345 | DOI:10.1093/bioinformatics/btae346

Ann Hematol. 2024 Jun 5. doi: 10.1007/s00277-024-05821-w. Online ahead of print.

ABSTRACT

Acute lymphoblastic leukemia (ALL) is a hematological malignancy characterized by aberrant proliferation and accumulation of lymphoid precursor cells within the bone marrow. The tyrosine kinase inhibitor (TKI), imatinib mesylate, has played a significant role in the treatment of Philadelphia chromosome-positive ALL (Ph + ALL). However, the achievement of durable and sustained therapeutic success remains a challenge due to the development of TKI resistance during the clinical course.The primary objective of this investigation is to propose a novel and efficacious treatment approach through drug repositioning, targeting ALL and its Ph + subtype by identifying and addressing differentially expressed genes (DEGs). This study involves a comprehensive analysis of transcriptome datasets pertaining to ALL and Ph + ALL in order to identify DEGs associated with the progression of these diseases to identify possible repurposable drugs that target identified hub proteins.The outcomes of this research have unveiled 698 disease-related DEGs for ALL and 100 for Ph + ALL. Furthermore, a subset of drugs, specifically glipizide for Ph + ALL, and maytansine and isoprenaline for ALL, have been identified as potential candidates for therapeutic intervention. Subsequently, cytotoxicity assessments were performed to confirm the in vitro cytotoxic effects of these selected drugs on both ALL and Ph + ALL cell lines.In conclusion, this study offers a promising avenue for the management of ALL and Ph + ALL through drug repurposed drugs. Further investigations are necessary to elucidate the mechanisms underlying cell death, and clinical trials are recommended to validate the promising results obtained through drug repositioning strategies.

PMID:38836918 | DOI:10.1007/s00277-024-05821-w

Cancer Drug Resist. 2024 May 20;7:19. doi: 10.20517/cdr.2024.04. eCollection 2024.

ABSTRACT

Aim: Multidrug resistance (MDR) is frequent in non-small cell lung cancer (NSCLC) patients, which can be due to its fibrotic stroma. This work explores the combination of pentoxifylline, an anti-fibrotic and chitinase 3-like-1 (CHI3L1) inhibitor drug, with conventional chemotherapy to improve NSCLC treatment. Methods: The effect of pentoxifylline in the expression levels of P-glycoprotein (P-gp), CHI3L1 and its main downstream proteins, as well as on cell death, cell cycle profile, and P-gp activity was studied in two pairs of sensitive and MDR counterpart NSCLC cell lines (NCI-H460/NCI-H460/R and A549/A549-CDR2). Association studies between CHI3L1 gene expression and NSCLC patients' survival were performed using The Cancer Genome Atlas (TCGA) analysis. The sensitizing effect of pentoxifylline to different drug regimens was evaluated in both sensitive and MDR NSCLC cell lines. The cytotoxicity of the drug combinations was assessed in MCF10A non-tumorigenic cells. Results: Pentoxifylline slightly decreased the expression levels of CHI3L1, β-catenin and signal transducer and activator of transcription 3 (STAT3), and caused a significant increase in the G1 phase of the cell cycle in both pairs of NSCLC cell lines. A significant increase in the % of cell death was observed in the sensitive NCI-H460 cell line. TCGA analysis revealed that high levels of CHI3L1 are associated with low overall survival (OS) in NSCLC patients treated with vinorelbine. Moreover, pentoxifylline sensitized both pairs of sensitive and MDR NSCLC cell lines to the different drug regimens, without causing significant toxicity to non-tumorigenic cells. Conclusion: This study suggests the possibility of combining pentoxifylline with chemotherapy to increase NSCLC therapeutic response, even in cases of MDR.

PMID:38835347 | PMC:PMC11149106 | DOI:10.20517/cdr.2024.04

BMC Cancer. 2024 Jun 4;24(1):680. doi: 10.1186/s12885-024-12449-6.

ABSTRACT

BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for lung cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR).

METHODS: Summary-level data of gene expression quantitative trait loci (eQTLs) were sourced from the eQTLGen resource. We procured genetic associations with lung cancer and its subtypes from the TRICL, ILCCO studies (discovery) and the FinnGen study (replication). We implemented Summary-data-based Mendelian Randomization analysis to identify potential therapeutic targets for lung cancer. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant.

FINDINGS: In the main analysis dataset, we identified 55 genes that demonstrate a causal relationship with lung cancer and its subtypes. However, in the replication cohort, only three genes were found to have such a causal association with lung cancer and its subtypes, and of these, HYKK (also known as AGPHD1) was consistently present in both the primary analysis dataset and the replication cohort. Following HEIDI tests and colocalization analyses, it was revealed that HYKK (AGPHD1) is associated with an increased risk of squamous cell carcinoma of the lung, with an odds ratio and confidence interval of OR = 1.28,95%CI = 1.24 to 1.33.

INTERPRETATION: We have found that the HYKK (AGPHD1) gene is associated with an increased risk of squamous cell carcinoma of the lung, suggesting that this gene may represent a potential therapeutic target for both the prevention and treatment of lung squamous cell carcinoma.

PMID:38834983 | DOI:10.1186/s12885-024-12449-6

J Cheminform. 2024 May 30;16(1):63. doi: 10.1186/s13321-024-00856-7.

ABSTRACT

Drug discovery is an intricate and costly process. Repurposing existing drugs and active compounds offers a viable pathway to develop new therapies for various diseases. By leveraging publicly available biomedical information, it is possible to predict compounds' activity and identify their potential targets across diverse organisms. In this study, we aimed to assess the antiplasmodial activity of compounds from the Repurposing, Focused Rescue, and Accelerated Medchem (ReFRAME) library using in vitro and bioinformatics approaches. We assessed the in vitro antiplasmodial activity of the compounds using blood-stage and liver-stage drug susceptibility assays. We used protein sequences of known targets of the ReFRAME compounds with high antiplasmodial activity (EC50 < 10 uM) to conduct a protein-pairwise search to identify similar Plasmodium falciparum 3D7 proteins (from PlasmoDB) using NCBI protein BLAST. We further assessed the association between the compounds' in vitro antiplasmodial activity and level of similarity between their known and predicted P. falciparum target proteins using simple linear regression analyses. BLAST analyses revealed 735 P. falciparum proteins that were similar to the 226 known protein targets associated with the ReFRAME compounds. Antiplasmodial activity of the compounds was positively associated with the degree of similarity between the compounds' known targets and predicted P. falciparum protein targets (percentage identity, E value, and bit score), the number of the predicted P. falciparum targets, and their respective mutagenesis index and fitness scores (R2 between 0.066 and 0.92, P < 0.05). Compounds predicted to target essential P. falciparum proteins or those with a druggability index of 1 showed the highest antiplasmodial activity.

PMID:38831351 | DOI:10.1186/s13321-024-00856-7

Chembiochem. 2024 Jun 3:e202400081. doi: 10.1002/cbic.202400081. Online ahead of print.

ABSTRACT

Mucopolysaccharidosis type IIIB (MPS IIIB) is an autosomal inherited disease caused by mutations in gene encoding the lysosomal enzyme N-acetyl-alpha-glucosaminidase (NAGLU). These mutations result in reduced NAGLU activity, preventing it from catalyzing the hydrolysis of the glycosaminoglycan heparan sulfate (HS). There are currently no approved treatments for MPS IIIB. A novel approach in the treatment of lysosomal storage diseases is the use of pharmacological chaperones (PC). In this study, we used a drug repurposing approach to identify and characterize novel potential PCs for NAGLU enzyme. We modeled the interaction of natural and artificial substrates within the active cavity of NAGLU (orthosteric site) and predicted potential allosteric sites. We performed a virtual screening for both the orthosteric and the predicted allosteric site against a curated database of human tested molecules. Considering the binding affinity and predicted blood-brain barrier permeability and gastrointestinal absorption, we selected atovaquone and piperaquine as orthosteric and allosteric PCs. The PCs were evaluated by their capacity to bind NAGLU and the ability to restore the enzymatic activity in human MPS IIIB fibroblasts These results represent novel PCs described for MPS IIIB and demonstrate the potential to develop novel therapeutic alternatives for this and other protein deficiency diseases.

PMID:38830828 | DOI:10.1002/cbic.202400081

Acta Pharm Sin B. 2024 Jun;14(6):2698-2715. doi: 10.1016/j.apsb.2024.03.003. Epub 2024 Mar 15.

ABSTRACT

Drug repurposing offers a valuable strategy for identifying new therapeutic applications for existing drugs. Recently, disulfiram (DSF), a drug primarily used for alcohol addiction treatment, has emerged as a potential treatment for inflammatory diseases by inhibiting pyroptosis, a form of programmed cell death. The therapeutic activity of DSF can be further enhanced by the presence of Cu2+, although the underlying mechanism of this enhancement remains unclear. In this study, we investigated the mechanistic basis of Cu2+-induced enhancement and discovered that it is attributed to the formation of a novel copper ethylthiocarbamate (CuET) complex. CuET exhibited significantly stronger anti-pyroptotic activity compared to DSF and employed a distinct mechanism of action. However, despite its potent activity, CuET suffered from poor solubility and limited permeability, as revealed by our druggability studies. To overcome these intrinsic limitations, we developed a scalable method to prepare CuET nanocrystals (CuET NCs) using a metal coordination-driven self-assembly approach. Pharmacokinetic studies demonstrated that CuET NCs exhibited a 6-fold improvement in bioavailability. Notably, CuET NCs exhibited high biodistribution in the intestine, suggesting their potential application for the treatment of inflammatory bowel diseases (IBDs). To evaluate their therapeutic efficacy in vivo, we employed a murine model of DSS-induced colitis and observed that CuET NCs effectively attenuated inflammation and ameliorated colitis symptoms. Our findings highlight the discovery of CuET as a potent anti-pyroptotic agent, and the development of CuET NCs represents a novel approach to enhance the druggability of CuET.

PMID:38828135 | PMC:PMC11143773 | DOI:10.1016/j.apsb.2024.03.003

AMIA Jt Summits Transl Sci Proc. 2024 May 31;2024:623-631. eCollection 2024.

ABSTRACT

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide, with one in nine people over the age of 65 living with the disease in 2023. In this study, we used a phenome wide association study (PheWAS) approach to identify cross-phenotype between previously identified genetic associations for AD and electronic health record (EHR) diagnoses from the UK Biobank (UKBB) (n=361,194 of European ancestry) and the eMERGE Network (n=105,108 of diverse ancestry). Based on 497 previously identified AD-associated variants from the Alzheimer's Disease Variant Portal (ADVP), we found significant associations primarily in immune and cardiac related diseases in our PheWAS. Replicating variants have widespread impacts on immune genes in diverse tissue types. This study demonstrates the potential of using the PheWAS strategy to improve our understanding of AD progression as well as identify potential drug repurposing opportunities for new treatment and disease prevention strategies.

PMID:38827078 | PMC:PMC11141840

medRxiv [Preprint]. 2024 May 20:2024.05.20.24307621. doi: 10.1101/2024.05.20.24307621.

ABSTRACT

RATIONALE: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear.

OBJECTIVES: Define high-risk COPD subtypes using both genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

METHODS: We defined high-risk groups based on PRS and TRS quantiles by maximizing differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.

MEASUREMENTS AND MAIN RESULTS: We examined two high-risk omics-defined groups in non-overlapping test sets (n=1,133 NHW COPDGene, n=299 African American (AA) COPDGene, n=468 ECLIPSE). We defined "High activity" (low PRS/high TRS) and "severe risk" (high PRS/high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signaling processes compared to a low-risk (low PRS, low TRS) reference subgroup. "High activity" but not "severe risk" participants had greater prospective FEV 1 decline (COPDGene: -51 mL/year; ECLIPSE: - 40 mL/year) and their proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.

CONCLUSIONS: Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.

PMID:38826461 | PMC:PMC11142287 | DOI:10.1101/2024.05.20.24307621

Infect Genet Evol. 2024 May 30:105611. doi: 10.1016/j.meegid.2024.105611. Online ahead of print.

ABSTRACT

Shigellosis, induced by Shigella flexneri, constitutes a significant health burden in developing nations, particularly impacting socioeconomically disadvantaged communities. Designated as the second most prevalent cause of diarrheal illness by the World Health Organization (WHO), it precipitates an estimated 212,000 fatalities annually. Within the spectrum of S. flexneri strains, serotype X is notably pervasive and resilient, yet its comprehensive characterization remains deficient. The present investigation endeavors to discern potential pharmacological targets and repurpose existing drug compounds against S. flexneri serotype X. Employing the framework of subtractive genomics, the study interrogates the reference genome of S. flexneri Serotype X (strain 2,002,017; UP000001884) to delineate its proteome into categories of non-homologous, non-paralogous, essential, virulent, and resistant constituents, thereby facilitating the identification of therapeutic targets. Subsequently, a screening of approximately 9000 compounds from the FDA library against the identified drug target aims to delineate efficacious agents for combating S. flexneri serotype X infections. The application of subtractive genomics methodology yields prognostic insights, unveiling non-paralogous proteins (n = 4122), non-homologues (n = 1803), essential (n = 1246), drug-like (n = 389), resistant (n = 167), alongside 42 virulent proteins within the reference proteome. This iterative process culminates in the identification of Serine O-acetyltransferase as a viable drug target. Subsequent virtual screening endeavors to unearth FDA-approved medicinal compounds capable of inhibiting Serine O-acetyltransferase. Noteworthy candidates such as DB12983, DB15085, DB16098, DB16185, and DB16262 emerge, exhibiting potential for mitigating S. flexneri Serotype X. Despite the auspicious findings, diligent scrutiny is imperative to ascertain the efficacy and safety profile of the proposed drug candidates vis-à-vis S. flexneri.

PMID:38823431 | DOI:10.1016/j.meegid.2024.105611

Osteoarthritis Cartilage. 2024 May 29:S1063-4584(24)01207-X. doi: 10.1016/j.joca.2024.05.008. Online ahead of print.

ABSTRACT

OBJECTIVE: Currently, no disease-modifying therapies for osteoarthritis (OA) exist, and attempts to identify novel cellular targets have been challenging. Risk factors for OA include advanced age, obesity, and metabolic syndrome. This creates an attractive opportunity to repurpose existing drugs that are used to treat comorbidities commonly encountered in patients with OA, if those drugs possess OA disease modifying properties.

METHODS: This narrative review incorporates findings from knee or hand OA randomized clinical trials, post-hoc clinical trial analyses, prospective cohort studies, and observational data.

RESULTS: Drugs used for the treatment of rheumatoid arthritis (methotrexate; TNFa, IL-1, and IL-6 pathway inhibitors; hydroxychloroquine), atopic/allergic disease (anti-histamines), osteoporosis (bisphosphonates and vitamin D), type 2 diabetes (metformin and GLP-1 agonists), and cardiovascular disease (atorvastatin, fish oil, and beta blockers) were reviewed for their potential benefit in OA. This review outlines the successful attributes of repurposed drugs, the challenges in repurposing drugs, and strategies for future clinical trials to support OA drug repurposing. Potential drug candidates for OA may be identified through the use of existing datasets and via collaborations with researchers in other fields to include OA endpoints in future clinical trials.

CONCLUSION: Given the association of OA with several commonly treated comorbidities, drug repurposing is an appealing approach that could provide a favorable benefit-to-risk ratio for chronic OA treatment.

PMID:38821468 | DOI:10.1016/j.joca.2024.05.008

Eur J Pharmacol. 2024 May 29:176679. doi: 10.1016/j.ejphar.2024.176679. Online ahead of print.

ABSTRACT

To provide a comprehensive framework of the current information on the potency and efficacy of interaction between phyto- and synthetic cannabinoids and their respective receptors, an electronic search of the PubMed, Scopus, and EMBASE literature was performed. Experimental studies included reports of mechanistic data providing affinity, efficacy, and half-maximal effective concentration (EC50). Among the 108 included studies, 174 structures, and 16 targets were extracted. The most frequent ligands belonged to the miscellaneous category with 40.2% followed by phytocannabinoid-similar, indole-similar, and pyrrole-similar structures with an abundance of 17.8%, 16.6%, and 12% respectively. 64.8% of structures acted as agonists, 17.1 % appeared as inverse agonists, 10.8% as antagonists, and 7.2% of structures were reported with antagonist/ inverse agonist properties. Our outcomes identify the affinity, EC50, and efficacy of the interactions between cannabinoids and their corresponding receptors and the subsequent response, evaluated in the available evidence. Considering structures' significance and very important effects of on the activities, the obtained results also provide clues to drug repurposing.

PMID:38821167 | DOI:10.1016/j.ejphar.2024.176679

Virusdisease. 2024 Mar;35(1):27-33. doi: 10.1007/s13337-024-00860-3. Epub 2024 Apr 2.

ABSTRACT

The lockdown enforced amid the COVID-19 pandemic has affected the occurrence and trends of various respiratory virus infections, with a particular focus on influenza. Our study seeks to analyze the repercussions of the COVID-19 pandemic on the positivity of the influenza virus throughout a 4-year span, encompassing both the pre-COVID-19 era (2018 and 2019) and the COVID-19 period (2020 and 2021). Data collected from patients clinically diagnosed with Influenza-like Illness and Severe Acute Respiratory Illness (SARI) from January 2018 to December 2021 for influenza virus detection were acquired and analyzed through multiplex RT-qPCR. The statistical analysis was conducted using SPSS (Statistical Package for Social Sciences) Version 21.0 Software. A total of 4464 samples were tested over 4 years (2018-2021), with 3201 samples from the pre-COVID era and 1263 samples from the COVID era. Influenza A positivity dropped from 17.7 to 9.57% and Influenza B positivity decreased from 3.74 to 2.61%. Subtyping revealed changes in prevalence for both viruses. Seasonal variations showed more pronounced peaks in the pre-COVID-19 era with reduced activity during lockdown. Influenza A saw a resurgence in August 2021. Throughout the COVID-19 pandemic (2020-2021) SARI cases did not decrease. The positivity rate for Influenza A slightly rose to 7.79% from 4.23% in the COVID period (2020-2021). This increase correlates with heightened hospitalization rates during the pandemic, sparking concerns of potential coinfection with coronavirus and Influenza A. The notable drop in influenza cases in 2020-2021 is likely due to stringent precautions, lockdowns, drug repurposing, and prioritized testing, indicating no reduction in influenza transmission. Increased influenza positivity in SARI patients during COVID-19 highlights a heightened risk of coinfection. Emphasizing solely on COVID-19 may lead to underreporting of other respiratory pathogens, including influenza viruses.

PMID:38817401 | PMC:PMC11133273 | DOI:10.1007/s13337-024-00860-3

Immunopharmacol Immunotoxicol. 2024 May 30:1-14. doi: 10.1080/08923973.2024.2360043. Online ahead of print.

ABSTRACT

BACKGROUND: Intestinal mucosal immune cells, notably mast cells, are pivotal in ulcerative colitis (UC) pathophysiology. Its activation elevates tissue concentrations of histamine. Inhibiting colonic histamine release could be an effective therapeutic strategy for treating UC. Experimental model like 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced colitis in rats mimic human IBD, aiding treatment investigations. Drug repurposing is a promising strategy to explore new indications for established drugs. Desloratadine (DES) is second-generation antihistamine utilized for managing allergies by blocking histamine action in the body. It also has reported anti-inflammatory and antioxidant actions.

OBJECTIVE: DES was investigated for its repurposing potential in UC by preclinical screening in TNBS-induced colitis in Wistar rats.

METHODS: Therapeutic efficacy of DES was evaluated both individually and in combination with standard drug 5-aminosalicylicacid (5-ASA). Rats were orally administered DES (10 mg/kg), 5-ASA (25 mg/kg), and DES + 5-ASA (5 mg + 12.15 mg) following the induction of colitis. Parameters including disease activity score rate (DASR), colon/body weight ratio (CBWR), colon length, diameter, pH, histological injury, and scoring were evaluated. Inflammatory biomarkers such as IL-1β, TNF-α, along with reduced glutathione (GSH), and malondialdehyde (MDA) were assessed.

RESULTS: Significant protective effects of DES, especially in combination with 5-ASA, against TNBS-induced inflammation were observed as evidenced by reduced DASR, CBWR, and improved colon morphology. Drugs significantly lowered plasma and colon histamine and, cytokines levels. GSH restoration, and decreased MDA content were also observed.

CONCLUSION: DES and DES + 5-ASA demonstrated potential in alleviating colonic inflammation associated with TNBS-induced colitis in rats. The effect can be attributed to its antihistamine, anticytokine, and antioxidative properties.

PMID:38816915 | DOI:10.1080/08923973.2024.2360043

Mol Psychiatry. 2024 May 30. doi: 10.1038/s41380-024-02626-1. Online ahead of print.

ABSTRACT

As the most prescribed psychotropic drugs in current medical practice, antidepressant drugs (ADs) of the selective serotonin reuptake inhibitor (SSRI) class represent prime candidates for drug repurposing. The mechanisms underlying their mode of action, however, remain unclear. Here, we show that common SSRIs and selected representatives of other AD classes bidirectionally regulate fluid-phase uptake at therapeutic concentrations and below. We further characterize membrane trafficking induced by a canonical SSRI fluvoxamine to show that it involves enhancement of clathrin-mediated endocytosis, endosomal system, and exocytosis. RNA sequencing analysis showed few fluvoxamine-associated differences, consistent with the effect being independent of gene expression. Fluvoxamine-induced increase in membrane trafficking boosted transcytosis in cell-based blood-brain barrier models, while a single injection of fluvoxamine was sufficient to enable brain accumulation of a fluid-phase fluorescent tracer in vivo. These findings reveal modulation of membrane trafficking by ADs as a possible cellular mechanism of action and indicate their clinical repositioning potential for regulating drug delivery to the brain.

PMID:38816584 | DOI:10.1038/s41380-024-02626-1

Liver Int. 2024 May 30. doi: 10.1111/liv.15979. Online ahead of print.

ABSTRACT

Porphyrias are rare, mostly inherited disorders resulting from altered activity of specific enzymes in the haem synthesis pathway that lead to accumulation of pathway intermediates. Photocutaneous symptoms occur when excess amounts of photoreactive porphyrins circulate in the blood to the skin, whereas increases in potentially neurotoxic porphyrin precursors are associated with neurovisceral symptoms. Current therapies are suboptimal and their mechanisms are not well established. As described here, emerging therapies address underlying disease mechanisms by introducing a gene, RNA or other specific molecule with the potential to cure or slow progression of the disease. Recent progress in nanotechnology and nanoscience, particularly regarding particle design and formulation, is expanding disease targets. More secure and efficient drug delivery systems have extended our toolbox for transferring specific molecules, especially into hepatocytes, and led to proof-of-concept studies in animal models. Repurposing existing drugs as molecular chaperones or haem synthesis inhibitors is also promising. This review summarizes key examples of these emerging therapeutic approaches and their application for hepatic and erythropoietic porphyrias.

PMID:38813953 | DOI:10.1111/liv.15979

Bioinform Biol Insights. 2024 May 28;18:11779322241256459. doi: 10.1177/11779322241256459. eCollection 2024.

ABSTRACT

BACKGROUND: Ameloblastoma (AM) is a benign tumor locally originated from odontogenic epithelium that is commonly found in the jaw. This tumor makes aggressive invasions and has a high recurrence rate. This study aimed to investigate the differentially expressed genes (DEGs), biological function alterations, disease targets, and existing drugs for AM using bioinformatics analysis.

METHODS: The data set of AM was retrieved from the GEO database (GSE132474) and identified the DEGs using bioinformatics analysis. The biological alteration analysis was applied to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Protein-protein interaction (PPI) network analysis and hub gene identification were screened through NetworkAnalyst. The transcription factor-protein network was constructed via OmicsNet. We also identified candidate compounds from L1000CDS2 database. The target of AM and candidate compounds were verified using docking simulation.

RESULTS: Totally, 611 DEGs were identified. The biological function enrichment analysis revealed glycosaminoglycan and GABA (γ-aminobutyric acid) signaling were most significantly up-regulated and down-regulated in AM, respectively. Subsequently, hub genes and transcription factors were screened via the network and showed FOS protein was found in both networks. Furthermore, we evaluated FOS protein to be a therapeutic target in AMs. Candidate compounds were screened and verified using docking simulation. Tanespimycin showed the greatest affinity binding value to bind FOS protein.

CONCLUSIONS: This study presented the underlying molecular mechanisms of disease pathogenesis, biological alteration, and important pathways of AMs and provided a candidate compound, Tanespimycin, targeting FOS protein for the treatment of AMs.

PMID:38812739 | PMC:PMC11135093 | DOI:10.1177/11779322241256459

Drug Discov Today. 2024 May 27:104046. doi: 10.1016/j.drudis.2024.104046. Online ahead of print.

ABSTRACT

In the current era of biological big data, which are rapidly populating the biological chemical space, in silico polypharmacology drug design approaches help to decode structure-multiple activity relationships (SMARts). Current computational methods can predict or categorize multiple properties simultaneously, which aids the generation, identification, curation, prioritization, optimization, and repurposing of molecules. Computational methods have generated opportunities and challenges in medicinal chemistry, pharmacology, food chemistry, toxicology, bioinformatics, and chemoinformatics. It is anticipated that computer-guided SMARts could contribute to the full automatization of drug design and drug repurposing campaigns, facilitating the prediction of new biological targets, side and off-target effects, and drug-drug interactions.

PMID:38810721 | DOI:10.1016/j.drudis.2024.104046