J Adv Res. 2024 Jul 30:S2090-1232(24)00310-2. doi: 10.1016/j.jare.2024.07.026. Online ahead of print.

ABSTRACT

BACKGROUND: Neutrophilic inflammation, characterized by dysregulated neutrophil activation, triggers a variety of inflammatory responses such as chemotactic infiltration, oxidative bursts, degranulation, neutrophil extracellular traps (NETs) formation, and delayed turnover. This type of inflammation is pivotal in the pathogenesis of acute respiratory distress syndrome (ARDS) and psoriasis. Despite current treatments, managing neutrophil-associated inflammatory symptoms remains a significant challenge.

AIM OF REVIEW: This review emphasizes the role of cyclin-dependent kinases (CDKs) in neutrophil activation and inflammation. It aims to highlight the therapeutic potential of repurposing CDK inhibitors to manage neutrophilic inflammation, particularly in ARDS and psoriasis. Additionally, it discusses the necessary precautions for the clinical application of these inhibitors due to potential off-target effects and the need for dose optimization.

KEY SCIENTIFIC CONCEPTS OF REVIEW: CDKs regulate key neutrophilic functions, including chemotactic responses, degranulation, NET formation, and apoptosis. Repurposing CDK inhibitors, originally developed for cancer treatment, shows promise in controlling neutrophilic inflammation. Clinical anticancer drugs, palbociclib and ribociclib, have demonstrated efficacy in treating neutrophilic ARDS and psoriasis by targeting off-label pathways, phosphoinositide 3-kinase (PI3K) and phosphodiesterase 4 (PDE4), respectively. While CDK inhibitors offer promising therapeutic benefits, their clinical repurposing requires careful consideration of off-target effects and dose optimization. Further exploration and clinical trials are necessary to ensure their safety and efficacy in treating inflammatory conditions.

PMID:39089617 | DOI:10.1016/j.jare.2024.07.026

Cutan Ocul Toxicol. 2024 Jul 31:1-5. doi: 10.1080/15569527.2024.2381207. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the safety and tolerability of pooled human immune globulins, Flebogamma® 5% DIF and Flebogamma® 10% DIF, administered by topical ophthalmic instillation to New Zealand White (NZW) rabbits.

METHODS: Male NZW rabbits were used in this study. In the acute single dose tolerability study, rabbits (n = 12) received a single topical dose of Flebogamma® 5% DIF. In the two-week repeated-dose tolerability study, rabbits (n = 5 for each group) were administered either Flebogamma® 5% DIF or Flebogamma® 10% DIF by topical bilateral administration four times daily (q.i.d.) between 8 am and 6 pm for a period of two weeks. Full ophthalmic examinations were conducted to evaluate ocular tolerability at baseline, Day 7, and Day 14.

RESULTS: In the acute single dose study, mild hyperaemia was observed in 1 out of 4 eyes at each 4 h and 24 h post-instillation of Flebogamma® 5% DIF. In the repeated dose study, no ocular signs were detected after q.i.d. topical instillation of Flebogamma® 5% DIF, while Flebogamma® 10% DIF resulted in mild hyperaemia in 8 out of 10 eyes on Day 7, and 5 out of 10 eyes on Day 14. No positive corneal fluorescein staining was detected. Schirmer tear test results were unremarkable. No other ocular signs were observed. Administration of immune globulins had no effect on intraocular pressure.

CONCLUSIONS: Flebogamma® 5% DIF and Flebogamma® 10% DIF were well-tolerated by NZW rabbits following single and repeat dose topical ophthalmic administration, supporting the future development of topical pooled human immune globulins for the treatment of ocular surface disease.

PMID:39086095 | DOI:10.1080/15569527.2024.2381207

Acta Trop. 2024 Jul 29:107338. doi: 10.1016/j.actatropica.2024.107338. Online ahead of print.

ABSTRACT

Leishmaniasis is a disease caused by the parasite Leishmania donovani affecting populations belonging to developing countries. The present study explores drug repurposing as an innovative strategy to identify new uses for approved clinical drugs, reducing the time and cost required for drug discovery. The three-dimensional structure of Leishmania donovani Sterol C-24 methyltransferase (LdSMT) was modeled and 1615 FDA-approved drugs from the ZINC database were computationally screened to identify the potent leads. Fulvestrant, docetaxel, indocyanine green, and iohexol were shortlisted as potential leads with the highest binding affinity and fitness scores for the concerned pathogenic receptor. Molecular dynamic simulation studies showed that the macromolecular complexes of indocyanine green and iohexol with LdSMT remained stable throughout the simulation and can be further evaluated experimentally for developing an effective drug. The proposed leads have further demonstrated promising safety profiles during cytotoxicity analysis on the J774.A1 macrophage cell line. Mechanistic analysis with these two drugs also revealed significant morphological alterations in the parasite, along with reduced intracellular parasitic load. Overall, this study demonstrates the potential of drug repurposing in identifying new treatments for leishmaniasis and other diseases affecting developing countries, highlighting the importance of considering approved clinical drugs for new applications.

PMID:39084482 | DOI:10.1016/j.actatropica.2024.107338

Nat Rev Nephrol. 2024 Jul 31. doi: 10.1038/s41581-024-00864-8. Online ahead of print.

ABSTRACT

Drug repurposing in glomerular disease can deliver opportunities for steroid-free regimens, enable personalized multi-target options for resistant or relapsing disease and enhance treatment options for understudied populations (for example, children) and in resource-limited settings. Identification of drug-repurposing candidates can be data driven, which utilizes existing data on disease pathobiology, drug features and clinical outcomes, or experimental, which involves high-throughput drug screens. Information from databases of approved drugs, clinical trials and PubMed registries suggests that at least 96 drugs on the market cover 49 targets with immunosuppressive potential that could be candidates for drug repurposing in glomerular disease. Furthermore, evidence to support drug repurposing is available for 191 immune drug target-glomerular disease pairs. Non-immunological drug repurposing includes strategies to reduce haemodynamic overload, podocyte injury and kidney fibrosis. Recommended strategies to expand drug-repurposing capacity in glomerular disease include enriching drug databases with glomeruli-specific information, enhancing the accessibility of primary clinical trial data, biomarker discovery to improve participant selection into clinical trials and improve surrogate outcomes and initiatives to reduce patent, regulatory and organizational hurdles.

PMID:39085415 | DOI:10.1038/s41581-024-00864-8

J Mol Model. 2024 Jul 31;30(8):296. doi: 10.1007/s00894-024-06087-9.

ABSTRACT

CONTEXT: Computational drug repurposing methods have been continuously developed in recent years to alleviate the high costs associated with drug development. As drug targets or the products of disease-related genes, proteins play an important role in drug repurposing. Although the potential has been demonstrated, heterogeneous graphs with proteins as independent nodes have yet to be studied, where extracting high-quality protein features from heterogeneous graphs poses a significant challenge. A novel drug repurposing model based on the feature construction of multi-layer ensemble (DRML-Ensemble) is proposed in this study. The performance of DRML-Ensemble, as evaluated on publicly available datasets, achieves an AUPR value of 0.93 and an AUROC value of 0.92, surpassing those of existing state-of-the-art methods. Additionally, DRML-Ensemble demonstrates its notable ability for drug repurposing in Alzheimer's disease.

METHODS: DRML-Ensemble is primarily composed of multiple layers of heterogeneous graph feature construction (HGFC). Each HGFC can extract protein features by leveraging the relationships between drugs, diseases, and proteins. These protein features are then utilized in subsequent layers to build drug and disease features, facilitating drug repurposing. By stacking multiple layers, optimal protein features can be obtained from the heterogeneous graph, consequently improving the accuracy of drug repurposing. However, an excessive· stacking of layers usually affect the model's training process, for example, causing problems such as overfitting; a multi-layer ensemble prediction module is designed to further improve the model's performance.

PMID:39083073 | DOI:10.1007/s00894-024-06087-9

Chem Biodivers. 2024 Jul 31:e202400895. doi: 10.1002/cbdv.202400895. Online ahead of print.

ABSTRACT

The emergence of the human monkeypox virus (MPXV) and the lack of effective medications have necessitated the exploration of various strategies to combat its infection. This study employs a network-based approach to drug discovery, utilizing the BLASTn and phylogenetic analysis to compare the MPXV genome with those of 18 related orthopoxviruses, revealing over 75% genomic similarity. Through a literature review, 160 human-host proteins linked to MPXV and its relatives were identified, leading to the construction of a human-host protein interactome. Analysis of this interactome highlighted 39 central hub proteins, which were then examined for potential drug targets. The process successfully revealed 15 targets already approved for use with medications. Additionally, the functional enrichment analysis provided insights into potential pathways and disorders connected with these targets. Four medications, namely Baricitinib, Infliximab, Adalimumab, and Etanercept, have been identified as potential candidates for repurposing to combat MPXV. In addition, the pharmacophore-based screening identified a molecule that is comparable to Baricitinib and has the potential to be effective against MPXV. The findings of the study suggest that ZINC22060520 is a promising medication for treating MPXV infection and proposes these medications as potential options for additional experimental and clinical assessment in the battle against MPXV.

PMID:39082609 | DOI:10.1002/cbdv.202400895

Front Biosci (Landmark Ed). 2024 Jul 2;29(7):242. doi: 10.31083/j.fbl2907242.

ABSTRACT

Autophagy is an evolutionarily conserved process in which intracellular macromolecules are degraded in a lysosomal-dependent manner. It is central to cellular energy homeostasis and to quality control of intracellular components. A decline in autophagic activity is associated with aging, and contributes to the development of various age-associated pathologies, including cancer. There is an ongoing need to develop chemotherapeutic agents to improve morbidity and mortality for those diagnosed with cancer, as well as to decrease the cost of cancer care. Autophagic programs are altered in cancer cells to support survival in genetically and metabolically unstable environments, making autophagy an attractive target for new chemotherapy. Antiretroviral drugs, which have dramatically increased the life- and health spans of people with human immunodeficiency virus (HIV) (PWH), have offered promise in the treatment of cancer. One mechanism underlying the antineoplastic effects of antiretroviral drugs is the alteration of cancer cell autophagy that can potentiate cell death. Antiretroviral drugs could be repurposed into the cancer chemotherapy arsenal. A more complete understanding of the impact of antiretroviral drugs on autophagy is essential for effective repurposing. This review summarizes our knowledge of the effects of antiretroviral drugs on autophagy as potential adjunctive chemotherapeutic agents, and highlights gaps to be addressed to reposition antiretroviral drugs into the antineoplastic arsenal successfully.

PMID:39082334 | DOI:10.31083/j.fbl2907242

Bioinform Biol Insights. 2024 Jul 29;18:11779322241267056. doi: 10.1177/11779322241267056. eCollection 2024.

ABSTRACT

MYC is a transcription factor crucial for maintaining cellular homeostasis, and its dysregulation is associated with highly aggressive cancers. Despite being considered "undruggable" due to its unstable protein structure, MYC gains stability through its interaction with its partner protein, MAX. The MYC-MAX heterodimer orchestrates the expression of numerous genes that contribute to an oncogenic phenotype. Previous efforts to develop small molecules, disrupting the MYC-MAX interaction, have shown promise in vitro but none have gained clinical approval. Our current computer-aided study utilizes an approach to explore drug repurposing as a strategy for inhibiting the c-MYC-MAX interaction. We have focused on compounds from DrugBank library, including Food and Drug Administration-approved drugs or those under investigation for other medical conditions. First, we identified a potential druggable site on flat interface of the c-MYC protein, which served as the target for virtual screening. Using both activity-based and structure-based screening, we comprehensively assessed the entire DrugBank library. Structure-based virtual screening was performed on AutoDock Vina and Glide docking tools, while activity-based screening was performed on two independent quantitative structure-activity relationship models. We focused on the top 2% of hit molecules from all screening methods. Ultimately, we selected consensus molecules from these screenings-those that exhibited both a stable interaction with c-MYC and superior inhibitory activity against c-MYC-MAX interaction. Among the evaluated molecules, we identified a protein kinase inhibitor (tyrosine kinase inhibitor [TKI]) known as nilotinib as a promising candidate targeting c-MYC-MAX dimer. Molecular dynamic simulations demonstrated a stable interaction between MYC and nilotinib. The interaction with nilotinib led to the stabilization of a region of the MYC protein that is distorted in apo-MYC and is important for MAX binding. Further analysis of differentially expressed gene revealed that nilotinib, uniquely among the tested TKIs, induced a gene expression program in which half of the genes were known to be responsive to c-MYC. Our findings provide the foundation for subsequent in vitro and in vivo investigations aimed at evaluating the efficacy of nilotinib in managing MYC oncogenic activity.

PMID:39081669 | PMC:PMC11287739 | DOI:10.1177/11779322241267056

Comput Biol Med. 2024 Jul 29;180:108912. doi: 10.1016/j.compbiomed.2024.108912. Online ahead of print.

ABSTRACT

BACKGROUND: Rheumatoid arthritis (RA) and osteoporosis (OP) are considered to be complex diseases. In recent studies, a positive association between RA and OP has been reported triggering growing research interest. This study aims to investigate the drugs related to critical genes in RA and OP, using bioinformatics approaches, toward drug repurposing.

METHOD: RA and OP genes were identified. The RA-OP PPI network was constructed and analyzed using the STRING and Cytoscape, respectively. Hub genes and modules were extracted and enriched Gene Ontology, through the WebGestalt and g:Profiler. The identification of the drugs related to critical genes using the DGIDB, and extracted the miRNAs using miRWalk and miRNet.

RESULTS: By network clustering, five significant modules were obtained that have important roles in the immune system. IL6, TNF, IL1B, STAT3, TGFB1, TP53, HIF1A, CCL2, IL10, and MMP9 were found as the top 10 hub genes in the RA-OP network. Hub genes were shown to have implications in inflammatory response, significant functions in cytokine receptor binding, and localized mostly in extracellular space. By investigating the drugs related to hub genes, 16 drugs were identified as repurposing candidate drugs. The 10 drugs included Hydroxychloroquine, Infliximab, Adalimumab, Etanercept, Certolizumab, Cyclosporine, Diacerein, Gevokizumab, Canakinumab, and Olokizumab proposed for OP. Also, six drugs including Pirfenidone, Pentoxifylline, Vadimezan, Rilonacept, Metelimumab, and Siltuximab have important roles in inflammatory control and were proposed for both RA and OP.

CONCLUSIONS: The results of the present study can provide novel insights into the pathogenesis and treatment of RA and OP.

PMID:39079412 | DOI:10.1016/j.compbiomed.2024.108912

Comput Biol Chem. 2024 Jul 25;112:108137. doi: 10.1016/j.compbiolchem.2024.108137. Online ahead of print.

ABSTRACT

MOTIVATION: Compound-protein interaction (CPI) prediction plays a crucial role in drug discovery and drug repositioning. Early researchers relied on time-consuming and labor-intensive wet laboratory experiments. However, the advent of deep learning has significantly accelerated this progress. Most existing deep learning methods utilize deep neural networks to extract compound features from sequences and graphs, either separately or in combination. Our team's previous research has demonstrated that compound images contain valuable information that can be leveraged for CPI task. However, there is a scarcity of multimodal methods that effectively combine sequence and image representations of compounds in CPI. Currently, the use of text-image pairs for contrastive language-image pre-training is a popular approach in the multimodal field. Further research is needed to explore how the integration of sequence and image representations can enhance the accuracy of CPI task.

RESULTS: This paper presents a novel method called MMCL-CPI, which encompasses two key highlights: 1) Firstly, we propose extracting compound features from two modalities: one-dimensional SMILES and two-dimensional images. This approach enables us to capture both sequence and spatial features, enhancing the prediction accuracy for CPI. Based on this, we design a novel multimodal model. 2) Secondly, we introduce a multimodal pre-training strategy that leverages comparative learning on a large-scale unlabeled dataset to establish the correspondence between SMILES string and compound's image. This pre-training approach significantly improves compound feature representations for downstream CPI task. Our method has shown competitive results on multiple datasets.

PMID:39079285 | DOI:10.1016/j.compbiolchem.2024.108137

Biomed Pharmacother. 2024 Jul 29;178:117191. doi: 10.1016/j.biopha.2024.117191. Online ahead of print.

ABSTRACT

Casein kinase II (CK2) has recently emerged as a pivotal mediator in the propagation of inflammation across various diseases. Nevertheless, its role in the pathogenesis of sepsis remains unexplored. Here, we investigated the involvement of CK2 in sepsis progression and the potential beneficial effects of silmitasertib, a selective and potent CK2α inhibitor, currently under clinical trials for COVID-19 and cancer. Sepsis was induced by caecal ligation and puncture (CLP) in four-month-old C57BL/6OlaHsd mice. One hour after the CLP/Sham procedure, animals were assigned to receive silmitasertib (50 mg/kg/i.v.) or vehicle. Plasma/organs were collected at 24 h for analysis. A second set of experiments was performed for survival rate over 120 h. Septic mice developed multiorgan failure, including renal dysfunction due to hypoperfusion (reduced renal blood flow) and increased plasma levels of creatinine. Renal derangements were associated with local overactivation of CK2, and downstream activation of the NF-ĸB-iNOS-NO axis, paralleled by a systemic cytokine storm. Interestingly, all markers of injury/inflammation were mitigated following silmitasertib administration. Additionally, when compared to sham-operated mice, sepsis led to vascular hyporesponsiveness due to an aberrant systemic and local release of NO. Silmitasertib restored sepsis-induced vascular abnormalities. Overall, these pharmacological effects of silmitasertib significantly reduced sepsis mortality. Our findings reveal, for the first time, the potential benefits of a selective and potent CK2 inhibitor to counteract sepsis-induced hyperinflammatory storm, vasoplegia, and ultimately prolonging the survival of septic mice, thus suggesting a pivotal role of CK2 in sepsis and silmitasertib as a novel powerful pharmacological tool for drug repurposing in sepsis.

PMID:39079263 | DOI:10.1016/j.biopha.2024.117191

Arch Virol. 2024 Jul 30;169(8):169. doi: 10.1007/s00705-024-06097-1.

ABSTRACT

Enteroviruses cause viral diseases that are harmful to children. Hand, foot, and mouth disease (HFMD) with neurological complications is mainly caused by enterovirus 71 (EV71). Despite its clinical importance, there is no effective antiviral drug against EV71. However, several repurposed drugs have been shown to have antiviral activity against related viruses. Treatments with single drugs and two-drug combinations were performed in vitro to assess anti-EV71 activity. Three repurposed drug candidates with broad-spectrum antiviral activity were found to demonstrate potent anti-EV71 activity: prochlorperazine, niclosamide, and itraconazole. To improve antiviral activity, combinations of two drugs were tested. Niclosamide and itraconazole showed synergistic antiviral activity in Vero cells, whereas combinations of niclosamide-prochlorperazine and itraconazole-prochlorperazine showed only additive effects. Furthermore, the combination of itraconazole and prochlorperazine showed an additive effect in neuroblastoma cells. Itraconazole and prochlorperazine exert their antiviral activities by inhibiting Akt phosphorylation. Repurposing of drugs can provide a treatment solution for HFMD, and our data suggest that combining these drugs can enhance that efficacy.

PMID:39078431 | DOI:10.1007/s00705-024-06097-1

mSystems. 2024 Jul 30:e0029524. doi: 10.1128/msystems.00295-24. Online ahead of print.

ABSTRACT

Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings, detected by our pipeline, provide valuable insights into these diseases.

IMPORTANCE: Assessing disease similarity is an essential initial step preceding a disease-based approach for drug repositioning. Our study provides a modest first step in underscoring the potential of integrating microbiome insights into the disease similarity assessment. Recent microbiome research has predominantly focused on analyzing individual diseases to understand their unique characteristics, which by design excludes comorbidities in individuals. We analyzed shotgun metagenomic data from existing studies and identified previously unknown similarities between diseases. Our research represents a pioneering effort that utilizes both interpretable machine learning and differential abundance analysis to assess microbial similarity between diseases.

PMID:39078158 | DOI:10.1128/msystems.00295-24

Expert Opin Drug Discov. 2024 Jul 30:1-19. doi: 10.1080/17460441.2024.2385598. Online ahead of print.

ABSTRACT

INTRODUCTION: Highly pathogenic coronaviruses (CoVs), such as severe acute respiratory syndrome CoV (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and the most recent SARS-CoV-2 responsible for the COVID-19 pandemic, pose significant threats to human populations over the past two decades. These CoVs have caused a broad spectrum of clinical manifestations ranging from asymptomatic to severe distress syndromes (ARDS), resulting in high morbidity and mortality.

AREAS COVERED: The accelerated advancements in antiviral drug discovery, spurred by the COVID-19 pandemic, have shed new light on the imperative to develop treatments effective against a broad spectrum of CoVs. This perspective discusses strategies and lessons learnt in targeting viral non-structural proteins, structural proteins, drug repurposing, and combinational approaches for the development of antivirals against CoVs.

EXPERT OPINION: Drawing lessons from the pandemic, it becomes evident that the absence of efficient broad-spectrum antiviral drugs increases the vulnerability of public health systems to the potential onslaught by highly pathogenic CoVs. The rapid and sustained spread of novel CoVs can have devastating consequences without effective and specifically targeted treatments. Prioritizing the effective development of broad-spectrum antivirals is imperative for bolstering the resilience of public health systems and mitigating the potential impact of future highly pathogenic CoVs.

PMID:39078037 | DOI:10.1080/17460441.2024.2385598

Arch Pharm (Weinheim). 2024 Jul 29:e2400492. doi: 10.1002/ardp.202400492. Online ahead of print.

ABSTRACT

Drug repurposing is defined as the use of approved therapeutic drugs for indications different from those for which they were originally designed. Repositioning diminishes both the time and cost for drug development by omitting the discovery stage, the analysis of absorption, distribution, metabolism, and excretion routes, as well as the studies of the biochemical and physiological effects of a new compound. Besides, drug repurposing takes advantage of the increased bioinformatics knowledge and availability of big data biology. There are many examples of drugs with repurposed indications evaluated in in vitro studies, and in pharmacological, preclinical, or retrospective clinical analyses. Here, we briefly review some of the experimental strategies and technical advances that may improve translational research in cardiovascular diseases. We also describe exhaustive research from basic science to clinical studies that culminated in the final approval of new drugs and provide examples of successful drug repurposing in the field of cardiology.

PMID:39074969 | DOI:10.1002/ardp.202400492

Arch Pharm (Weinheim). 2024 Jul 29:e2400343. doi: 10.1002/ardp.202400343. Online ahead of print.

ABSTRACT

Glioblastoma multiforme is a very combative and threatening type of cancer. The standard course of treatment involves excising the tumor surgically, then administering chemotherapy and radiation therapy. Because of the presence of the blood-brain barrier and the unique characteristics of the tumor microenvironment, chemotherapy is extremely difficult and has a high incidence of relapse. With their capacity to precisely target and transport therapeutic medications to the tumor while overcoming the challenges provided by invasive and infiltrative gliomas, nanocarriers offer a potentially beneficial treatment option for gliomas. Drug repositioning or, in other words, finding novel therapeutic uses for medications that have received approval for previous uses has also recently emerged to provide alternative treatments for many diseases, with glioblastoma being among them. In this article, our goal is to shed light on the pathogenesis of glioma and summarize the proposed treatment approaches in the last decade, highlighting how combining repositioned drugs and nanocarriers technology can reduce drug resistance and improve therapeutic efficacy in primary glioma.

PMID:39074966 | DOI:10.1002/ardp.202400343

IEEE J Biomed Health Inform. 2024 Jul 29;PP. doi: 10.1109/JBHI.2024.3434439. Online ahead of print.

ABSTRACT

Exploring simple and efficient computational methods for drug repositioning has emerged as a popular and compelling topic in the realm of comprehensive drug development. The crux of this technology lies in identifying potential drug-disease associations, which can effectively mitigate the burdens caused by the exorbitant costs and lengthy periods of conventional drugs development. However, current computational drug repositioning methods face challenges in accurately predicting drug-disease associations. These challenges include only considering drugs and diseases to construct a heterogeneous graph without including other biological nodes associated with the disease or drug for a more comprehensive heterogeneous graph, as well as not fully utilizing the local structure of heterogeneous graphs and rich semantic features. To address these problems, we propose a Multi-view Representation Learning method (MRLHGNN) with Heterogeneous Graph Neural Network for drug repositioning. This method is based on a collection of data from multiple biological entities associated with drugs or diseases. It consists of a view-specific feature aggregation module with meta-paths and auto multi-view fusion encoder. To better utilize local structural and semantic information from specific views in heterogeneous graph, MRLHGNN employs a feature aggregation model with variable-length meta-paths to expand the local receptive field. Additionally, it utilizes a transformerbased semantic aggregation module to aggregate semantic features across different view-specific graphs. Finally, potential drug-disease associations are obtained through a multi-view fusion decoder with an attention mechanism. Cross-validation experiments demonstrate the effectiveness and interpretability of the MRLHGNN in comparison to nine state-of-the-art approaches. Case studies further reveal that MRLHGNN can serve as a powerful tool for drug repositioning.

PMID:39074005 | DOI:10.1109/JBHI.2024.3434439

JAMA Pediatr. 2024 Jul 29. doi: 10.1001/jamapediatrics.2024.2287. Online ahead of print.

NO ABSTRACT

PMID:39073790 | DOI:10.1001/jamapediatrics.2024.2287

Future Med Chem. 2024 Jul 29:1-9. doi: 10.1080/17568919.2024.2379231. Online ahead of print.

ABSTRACT

Aim: To identify potential antischistosomal agents through 3D pharmacophore-based virtual screening of US FDA approved drugs. Materials & methods: A comprehensive virtual screening was conducted on a dataset of 10,000 FDA approved drugs, employing praziquantel as a template. Promising candidates were selected and assessed for their impact on Schistosoma mansoni viability in vitro and in vivo using S. mansoni infected mice. Results & conclusion: Among the selected drugs, betamethasone and doxazosin demonstrated in vitro efficacy, with effective concentration 50% (EC50) values ranging from 35 to 60 μM. In vivo studies revealed significant (>50%) reductions in worm burden for both drugs. These findings suggest that betamethasone and doxazosin hold promise for repurposing in treating schistosomiasis. Additionally, the study showcases a useful approach for identifying new antischistosomal drugs.

PMID:39072451 | DOI:10.1080/17568919.2024.2379231

Virusdisease. 2024 Jun;35(2):260-270. doi: 10.1007/s13337-024-00869-8. Epub 2024 Jun 11.

ABSTRACT

Zoonotic monkeypox disease, caused by the double-stranded DNA monkeypox virus, has become a global concern. Due to the absence of a specific small molecule drug for the disease, this report aims to identify potential inhibitor drugs for monkeypox. This study explores a drug repurposing strategy using virtual screening to evaluate 1615 FDA approved drugs against the monkeypox virus DNA dependent RNA polymerase subunit A6R. Normal mode analysis and molecular dynamics simulation assessed the flexibility and stability of the target protein in complex with the top screened drugs. The analysis identified Nilotinib (ZINC000006716957), Conivaptan (ZINC000012503187), and Ponatinib (ZINC000036701290) as the most potential RNA polymerase inhibitors with binding energies of - 7.5 kcal/mol. These drugs mainly established hydrogen bonds and hydrophobic interactions with the protein active sites, including LEU95, LEU90, PRO96, MET110, and VAL113, and residues nearby. Normal mode analysis and molecular dynamics simulation confirmed the stability of interactions between the top drugs and the protein. In conclusion, we have discovered promising drugs that can potentially control the monkeypox virus and should be further explored through experimental assays and clinical trials to assess their actual activity against the disease. The findings of this study could lay the foundation for screening repurposed compounds as possible antiviral treatments against various highly pathogenic viruses.

PMID:39071866 | PMC:PMC11269544 | DOI:10.1007/s13337-024-00869-8