Antibiotics (Basel). 2024 Feb 10;13(2):177. doi: 10.3390/antibiotics13020177.

ABSTRACT

The aims of this study were (i) to determine if the combination of mitomycin C with pentamidine or existing antibiotics resulted in enhanced efficacy versus infections with MDR P. aeruginosa in vivo; and (ii) to determine if the doses of mitomycin C and pentamidine in combination can be reduced to levels that are non-toxic in humans but still retain antibacterial activity. Resistant clinical isolates of P. aeruginosa, a mutant strain over-expressing the MexAB-OprM resistance nodulation division (RND) efflux pump and a strain with three RND pumps deleted, were used. MIC assays indicated that all strains were sensitive to mitomycin C, but deletion of three RND pumps resulted in hypersensitivity and over-expression of MexAB-OprM caused some resistance. These results imply that mitomycin C is a substrate of the RND efflux pumps. Mitomycin C monotherapy successfully treated infected Galleria mellonella larvae, albeit at doses too high for human administration. Checkerboard and time-kill assays showed that the combination of mitomycin C with pentamidine, or the antibiotic gentamicin, resulted in synergistic inhibition of most P. aeruginosa strains in vitro. In vivo, administration of a combination therapy of mitomycin C with pentamidine, or gentamicin, to G. mellonella larvae infected with P. aeruginosa resulted in enhanced efficacy compared with monotherapies for the majority of MDR clinical isolates. Notably, the therapeutic benefit conferred by the combination therapy occurred with doses of mitomycin C close to those used in human medicine. Thus, repurposing mitomycin C in combination therapies to target MDR P. aeruginosa infections merits further investigation.

PMID:38391563 | DOI:10.3390/antibiotics13020177

Int J Oncol. 2024 Apr;64(4):39. doi: 10.3892/ijo.2024.5627. Epub 2024 Feb 23.

ABSTRACT

Neddylation, akin to ubiquitination, represents a post‑translational modification of proteins wherein neural precursor cell‑expressed developmentally downregulated protein 8 (NEDD8) is modified on the substrate protein through a series of reactions. Neddylation plays a pivotal role in the growth and proliferation of animal cells. In colorectal cancer (CRC), it predominantly contributes to the proliferation, metastasis and survival of tumor cells, decreasing overall patient survival. The strategic manipulation of the NEDD8‑mediated neddylation pathway holds immense therapeutic promise in terms of the potential to modulate the growth of tumors by regulating diverse biological responses within cancer cells, such as DNA damage response and apoptosis, among others. MLN4924 is an inhibitor of NEDD8, and its combined use with platinum drugs and irinotecan, as well as cycle inhibitors and NEDD activating enzyme inhibitors screened by drug repurposing, has been found to exert promising antitumor effects. The present review summarizes the recent progress made in the understanding of the role of NEDD8 in the advancement of CRC, suggesting that NEDD8 is a promising anti‑CRC target.

PMID:38391033 | DOI:10.3892/ijo.2024.5627

J Biomol Struct Dyn. 2024 Feb 22:1-31. doi: 10.1080/07391102.2024.2319104. Online ahead of print.

ABSTRACT

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

PMID:38385447 | DOI:10.1080/07391102.2024.2319104

Front Pharmacol. 2024 Feb 7;15:1337764. doi: 10.3389/fphar.2024.1337764. eCollection 2024.

ABSTRACT

Accurately identifying novel indications for drugs is crucial in drug research and discovery. Traditional drug discovery is costly and time-consuming. Computational drug repositioning can provide an effective strategy for discovering potential drug-disease associations. However, the known experimentally verified drug-disease associations is relatively sparse, which may affect the prediction performance of the computational drug repositioning methods. Moreover, while the existing drug-disease prediction method based on metric learning algorithm has achieved better performance, it simply learns features of drugs and diseases only from the drug-centered perspective, and cannot comprehensively model the latent features of drugs and diseases. In this study, we propose a novel drug repositioning method named RSML-GCN, which applies graph convolutional network and reinforcement symmetric metric learning to predict potential drug-disease associations. RSML-GCN first constructs a drug-disease heterogeneous network by integrating the association and feature information of drugs and diseases. Then, the graph convolutional network (GCN) is applied to complement the drug-disease association information. Finally, reinforcement symmetric metric learning with adaptive margin is designed to learn the latent vector representation of drugs and diseases. Based on the learned latent vector representation, the novel drug-disease associations can be identified by the metric function. Comprehensive experiments on benchmark datasets demonstrated the superior prediction performance of RSML-GCN for drug repositioning.

PMID:38384286 | PMC:PMC10879308 | DOI:10.3389/fphar.2024.1337764

Sci Rep. 2024 Feb 21;14(1):4328. doi: 10.1038/s41598-024-55013-9.

ABSTRACT

The COVID-19 pandemic caused by the SARS-CoV-2 virus has greatly affected global health. Emerging evidence suggests a complex interplay between Alzheimer's disease (AD), diabetes (DM), and COVID-19. Given COVID-19's involvement in the increased risk of other diseases, there is an urgent need to identify novel targets and drugs to combat these interconnected health challenges. Lysophosphatidic acid receptors (LPARs), belonging to the G protein-coupled receptor family, have been implicated in various pathological conditions, including inflammation. In this regard, the study aimed to investigate the involvement of LPARs (specifically LPAR1, 3, 6) in the tri-directional relationship between AD, DM, and COVID-19 through network analysis, as well as explore the therapeutic potential of selected anti-AD, anti-DM drugs as LPAR, SPIKE antagonists. We used the Coremine Medical database to identify genes related to DM, AD, and COVID-19. Furthermore, STRING analysis was used to identify the interacting partners of LPAR1, LPAR3, and LPAR6. Additionally, a literature search revealed 78 drugs on the market or in clinical studies that were used for treating either AD or DM. We carried out docking analysis of these drugs against the LPAR1, LPAR3, and LPAR6. Furthermore, we modeled the LPAR1, LPAR3, and LPAR6 in a complex with the COVID-19 spike protein and performed a docking study of selected drugs with the LPAR-Spike complex. The analysis revealed 177 common genes implicated in AD, DM, and COVID-19. Protein-protein docking analysis demonstrated that LPAR (1,3 & 6) efficiently binds with the viral SPIKE protein, suggesting them as targets for viral infection. Furthermore, docking analysis of the anti-AD and anti-DM drugs against LPARs, SPIKE protein, and the LPARs-SPIKE complex revealed promising candidates, including lupron, neflamapimod, and nilotinib, stating the importance of drug repurposing in the drug discovery process. These drugs exhibited the ability to bind and inhibit the LPAR receptor activity and the SPIKE protein and interfere with LPAR-SPIKE protein interaction. Through a combined network and targeted-based therapeutic intervention approach, this study has identified several drugs that could be repurposed for treating COVID-19 due to their expected interference with LPAR(1, 3, and 6) and spike protein complexes. In addition, it can also be hypothesized that the co-administration of these identified drugs during COVID-19 infection may not only help mitigate the impact of the virus but also potentially contribute to the prevention or management of post-COVID complications related to AD and DM.

PMID:38383841 | DOI:10.1038/s41598-024-55013-9

Schizophrenia (Heidelb). 2024 Feb 21;10(1):22. doi: 10.1038/s41537-024-00445-5.

ABSTRACT

Multimorbidity represents an increasingly important public health challenge with far-reaching implications for health management and policy. Mental health and metabolic diseases have a well-established epidemiological association. In this study, we investigate the genetic intersection between type 2 diabetes and schizophrenia. We use Mendelian randomization to examine potential causal relationships between the two conditions and related endophenotypes. We report no compelling evidence that type 2 diabetes genetic liability potentially causally influences schizophrenia risk and vice versa. Our findings show that increased body mass index (BMI) has a protective effect against schizophrenia, in contrast to the well-known risk-increasing effect of BMI on type 2 diabetes risk. We identify evidence of colocalization of association signals for these two conditions at 11 genomic loci, six of which have opposing directions of effect for type 2 diabetes and schizophrenia. To elucidate these colocalizing signals, we integrate multi-omics data from bulk and single-cell gene expression studies, along with functional information. We identify putative effector genes and find that they are enriched for homeostasis and lipid-related pathways. We also highlight drug repurposing opportunities including N-methyl-D-aspartate (NMDA) receptor antagonists. Our findings provide insights into shared biological mechanisms for type 2 diabetes and schizophrenia, highlighting common factors that influence the risk of the two conditions in opposite directions and shedding light on the complex nature of this comorbidity.

PMID:38383672 | DOI:10.1038/s41537-024-00445-5

J Neuroinflammation. 2024 Feb 21;21(1):53. doi: 10.1186/s12974-024-03041-7.

ABSTRACT

BACKGROUND: Parkinson's disease (PD) is a common and costly progressive neurodegenerative disease of unclear etiology. A disease-modifying approach that can directly stop or slow its progression remains a major unmet need in the treatment of PD. A clinical pharmacology-based drug repositioning strategy is a useful approach for identifying new drugs for PD.

METHODS: We analyzed claims data obtained from the National Health Insurance Service (NHIS), which covers a significant portion of the South Korean population, to investigate the association between antihistamines, a class of drugs commonly used to treat allergic symptoms by blocking H1 receptor, and PD in a real-world setting. Additionally, we validated this model using various animal models of PD such as the 6-hydroxydopmaine (6-OHDA), α-synuclein preformed fibrils (PFF) injection, and Caenorhabditis elegans (C. elegans) models. Finally, whole transcriptome data and Ingenuity Pathway Analysis (IPA) were used to elucidate drug mechanism pathways.

RESULTS: We identified fexofenadine as the most promising candidate using National Health Insurance claims data in the real world. In several animal models, including the 6-OHDA, PFF injection, and C. elegans models, fexofenadine ameliorated PD-related pathologies. RNA-seq analysis and the subsequent experiments suggested that fexofenadine is effective in PD via inhibition of peripheral immune cell infiltration into the brain.

CONCLUSION: Fexofenadine shows promise for the treatment of PD, identified through clinical data and validated in diverse animal models. This combined clinical and preclinical approach offers valuable insights for developing novel PD therapeutics.

PMID:38383441 | DOI:10.1186/s12974-024-03041-7

Arch Virol. 2024 Feb 20;169(3):52. doi: 10.1007/s00705-024-05995-8.

ABSTRACT

Parvoviruses are responsible for multiple diseases, and there is a critical need for effective antiviral therapies. Specific antiviral treatments for parvovirus infections are currently lacking, and the available options are mostly supportive and symptomatic. In recent years, significant research efforts have been directed toward understanding the molecular mechanisms of parvovirus replication and identifying potential targets for antiviral interventions. This review highlights the structure, pathogenesis, and treatment options for major viruses of the subfamily Parvovirinae, such as parvovirus B19 (B19V), canine parvovirus type 2 (CPV-2), and porcine parvovirus (PPV) and also describes different approaches in the development of antiviral alternatives against parvovirus, including drug repurposing, serendipity, and computational tools (molecular docking and artificial intelligence) in drug discovery. These advances greatly increase the likelihood of discoveries that will lead to potent antiviral strategies against different parvovirus infections.

PMID:38378929 | DOI:10.1007/s00705-024-05995-8

BMC Bioinformatics. 2024 Feb 20;25(1):79. doi: 10.1186/s12859-024-05705-w.

ABSTRACT

BACKGROUND: Identification of potential drug-disease associations is important for both the discovery of new indications for drugs and for the reduction of unknown adverse drug reactions. Exploring the potential links between drugs and diseases is crucial for advancing biomedical research and improving healthcare. While advanced computational techniques play a vital role in revealing the connections between drugs and diseases, current research still faces challenges in the process of mining potential relationships between drugs and diseases using heterogeneous network data.

RESULTS: In this study, we propose a learning framework for fusing Graph Transformer Networks and multi-aggregate graph convolutional network to learn efficient heterogenous information graph representations for drug-disease association prediction, termed WMAGT. This method extensively harnesses the capabilities of a robust graph transformer, effectively modeling the local and global interactions of nodes by integrating a graph convolutional network and a graph transformer with self-attention mechanisms in its encoder. We first integrate drug-drug, drug-disease, and disease-disease networks to construct heterogeneous information graph. Multi-aggregate graph convolutional network and graph transformer are then used in conjunction with neural collaborative filtering module to integrate information from different domains into highly effective feature representation.

CONCLUSIONS: Rigorous cross-validation, ablation studies examined the robustness and effectiveness of the proposed method. Experimental results demonstrate that WMAGT outperforms other state-of-the-art methods in accurate drug-disease association prediction, which is beneficial for drug repositioning and drug safety research.

PMID:38378479 | DOI:10.1186/s12859-024-05705-w

Ann Rheum Dis. 2024 Feb 19:ard-2023-224795. doi: 10.1136/ard-2023-224795. Online ahead of print.

ABSTRACT

OBJECTIVES: To unveil biological milieus underlying low disease activity (LDA) and remission versus active systemic lupus erythematosus (SLE).

METHODS: We determined differentially expressed pathways (DEPs) in SLE patients from the PRECISESADS project (NTC02890121) stratified into patients fulfilling and not fulfilling the criteria of (1) Lupus LDA State (LLDAS), (2) Definitions of Remission in SLE remission, and (3) LLDAS exclusive of remission.

RESULTS: We analysed data from 321 patients; 40.8% were in LLDAS, and 17.4% in DORIS remission. After exclusion of patients in remission, 28.3% were in LLDAS. Overall, 604 pathways differed significantly in LLDAS versus non-LLDAS patients with an false-discovery rate-corrected p (q)<0.05 and a robust effect size (dr)≥0.36. Accordingly, 288 pathways differed significantly between DORIS remitters and non-remitters (q<0.05 and dr≥0.36). DEPs yielded distinct molecular clusters characterised by differential serological, musculoskeletal, and renal activity. Analysis of partially overlapping samples showed no DEPs between LLDAS and DORIS remission. Drug repurposing potentiality for treating SLE was unveiled, as were important pathways underlying active SLE whose modulation could aid attainment of LLDAS/remission, including toll-like receptor (TLR) cascades, Bruton tyrosine kinase (BTK) activity, the cytotoxic T lymphocyte antigen 4 (CTLA-4)-related inhibitory signalling, and the nucleotide-binding oligomerization domain leucine-rich repeat-containing protein 3 (NLRP3) inflammasome pathway.

CONCLUSIONS: We demonstrated for the first time molecular signalling pathways distinguishing LLDAS/remission from active SLE. LLDAS/remission was associated with reversal of biological processes related to SLE pathogenesis and specific clinical manifestations. DEP clustering by remission better grouped patients compared with LLDAS, substantiating remission as the ultimate treatment goal in SLE; however, the lack of substantial pathway differentiation between the two states justifies LLDAS as an acceptable goal from a biological perspective.

PMID:38373843 | DOI:10.1136/ard-2023-224795

Cancer Lett. 2024 Feb 17:216705. doi: 10.1016/j.canlet.2024.216705. Online ahead of print.

ABSTRACT

Malignant tumors have increased energy requirements due to growth, differentiation or response to stress. A significant number of studies in recent years have described upregulation of mitochondrial genes responsible for oxidative phosphorylation (OXPHOS) in some tumors. Although OXPHOS is replaced by glycolysis in some tumors (Warburg effect), both processes can occur simultaneously during the evolution of the same malignancies. In particular, chemoresistant and/or cancer stem cells appear to find a way to activate OXPHOS and metastasize. In this paper, we discuss recent work showing upregulation of OXPHOS in chemoresistant tumors and cell models. In addition, we show an inverse correlation of OXPHOS gene expression with the survival time of cancer patients after chemotherapy and discuss combination therapies for resistant cancer tumors.

PMID:38373691 | DOI:10.1016/j.canlet.2024.216705

J Chem Inf Model. 2024 Feb 19. doi: 10.1021/acs.jcim.3c01726. Online ahead of print.

ABSTRACT

As is well-known, the process of developing new drugs is extremely expensive, whereas drug repurposing represents a promising approach to augment the efficiency of new drug development. While this method can indeed spare us from expensive drug toxicity and safety experiments, it still demands a substantial amount of time to carry out precise efficacy experiments for specific diseases, thereby consuming a significant quantity of resources. Therefore, if we can prescreen potential other indications for selected drugs, it could result in substantial cost savings. In light of this, this paper introduces a drug repurposing recommendation model called MRNDR, which stands for Multi-head attention-based Recommendation Network for Drug Repurposing. This model serves as a prediction tool for drug-disease relationships, leveraging the multihead self-attention mechanism that demonstrates robust generalization capabilities. These capabilities stem not only from our extensive million-level training data set, BioRE (Biology Recommended Entity data), but also from the utilization of the WRDS (Weighted Representation Distance Score) algorithm proposed by us. The MRNDR model has achieved new state-of-the-art results on the GP-KG public data set, with an MRR (Mean Reciprocal Rank) score of 0.308 and a Hits@10 score of 0.628. This represents significant improvements of 4.7% (MRR) and 18.1% (Hits@10) over the current best-performing models. Additionally, to further validate the practical utility of the model, we examined results recommended by MRNDR that were not present in the training data set. Some of these recommendations have undergone clinical trials, as evidenced by their presence on ClinicalTrials.gov and the China Clinical Trials Center, indirectly confirming the applicability of MRNDR. The MRNDR model can predict the reusability of candidate drugs, reducing the need for manual expert assessments and enabling efficient drug repurposing.

PMID:38373300 | DOI:10.1021/acs.jcim.3c01726

J Biomol Struct Dyn. 2024 Feb 19:1-11. doi: 10.1080/07391102.2024.2317987. Online ahead of print.

ABSTRACT

Neurodegenerative diseases such as Alzheimer's disease (AD) pose a significant global health challenge that requires the exploration of innovative therapeutic strategies. Triggering receptor expressed on myeloid cells-2 (TREM2) is one of the critical proteins involved in immune regulation and neuroinflammation. It has emerged as a promising therapeutic target to develop treatments for neurodegenerative disorders like AD. Here, we employed a comprehensive virtual screening approach to identify potential small molecule inhibitors among FDA-approved drugs for TREM2. The docking study reveals significant binding affinity, ranging from -7.8 kcal/mol to -8.5 kcal/mol, for the elucidated hits against TREM2, accompanied by several crucial interactions. Among the repurposed drugs identified in the initial screening, Carpipramine, Clocapramine, and Pimozide stood out due to their notable binding potential and favorable drug profiling. Further, we conducted molecular dynamics (MD) simulations on the selected molecules that probed their structural dynamics and stability within the TREM2 binding pocket. The structural parameters and hydrogen bond dynamics remained remarkably stable throughout the simulated trajectories. Furthermore, we performed principal component analysis (PCA) and constructed free energy landscapes (FELs) to gain deeper insights into ligand binding and conformational flexibility of TREM2. The findings revealed that the elucidated molecules, Carpipramine, Clocapramine, and Pimozide, exhibited an exceptional fit within the binding pocket of TREM2 with remarkable stability and interaction patterns throughout the 500 ns simulation window. Interestingly, these molecules possessed a spectrum of anti-neurodegenerative properties and favorable drug profiles, which suggest their potential as promising drug candidates for repurposing in the treatment of AD.Communicated by Ramaswamy H. Sarma.

PMID:38373093 | DOI:10.1080/07391102.2024.2317987

Biofilm. 2024 Feb 7;7:100180. doi: 10.1016/j.bioflm.2024.100180. eCollection 2024 Jun.

ABSTRACT

Antivirulence agents are considered a promising strategy to treat bacterial infections. Fluoropyrimidines possess antivirulence and antibiofilm activity against Gram-negative bacteria; however, their mechanism of action is yet unknown. Consistent with their known antibiofilm activity, fluoropyrimidines, particularly 5-fluorocytosine (5-FC), impair curli-dependent surface adhesion by Escherichia coli MG1655 via downregulation of curli fimbriae gene transcription. Curli inhibition requires fluoropyrimidine conversion into fluoronucleotides and is not mediated by c-di-GMP or the ymg-rcs envelope stress response axis, previously suggested as the target of fluorouracil antibiofilm activity in E. coli. In contrast, 5-FC hampered the transcription of curli activators RpoS and stimulated the expression of Fis, a curli repressor affected by nucleotide availability. This last observation suggested a possible perturbation of the de novo pyrimidine biosynthesis by 5-FC: indeed, exposure to 5-FC resulted in a ca. 2-fold reduction of UMP intracellular levels while not affecting ATP. Consistently, expression of the de novo pyrimidine biosynthesis genes carB and pyrB was upregulated in the presence of 5-FC. Our results suggest that the antibiofilm activity of fluoropyrimidines is mediated, at least in part, by perturbation of the pyrimidine nucleotide pool. We screened a genome library in search of additional determinants able to counteract the effects of 5-FC. We found that a DNA fragment encoding the unknown protein D8B36_18,480 and the N-terminal domain of the penicillin-binding protein 1b (PBP1b), involved in peptidoglycan synthesis, could restore curli production in the presence of 5-FC. Deletion of the PBP1b-encoding gene mrcB, induced csgBAC transcription, while overexpression of the gene encoding the D8B36_18,480 protein obliterated its expression, possibly as part of a coordinated response in curli regulation with PBP1b. While the two proteins do not appear to be direct targets of 5-FC, their involvement in curli regulation suggests a connection between peptidoglycan biosynthesis and curli production, which might become even more relevant upon pyrimidine starvation and reduced availability of UDP-sugars needed in cell wall biosynthesis. Overall, our findings link the antibiofilm activity of fluoropyrimidines to the redirection of at least two global regulators (RpoS, Fis) by induction of pyrimidine starvation. This highlights the importance of the de novo pyrimidines biosynthesis pathway in controlling virulence mechanisms in different bacteria and makes the pathway a potential target for antivirulence strategies.

PMID:38370152 | PMC:PMC10869245 | DOI:10.1016/j.bioflm.2024.100180

Eur J Pharm Biopharm. 2024 Feb 15:114223. doi: 10.1016/j.ejpb.2024.114223. Online ahead of print.

ABSTRACT

The lung is an attractive target organ for inhalation of RNA therapeutics, such as small interfering RNA (siRNA). However, clinical translation of siRNA drugs for application in the lung is hampered by many extra- and intracellular barriers. We previously developed hybrid nanoparticles consisting of an siRNA-loaded nanosized hydrogel (nanogel) core coated with Curosurf®, a clinically used pulmonary surfactant. The surfactant shell was shown to markedly improve particle stability and promote intracellular siRNA delivery, both in vitro and in vivo. However, the full potential of siRNA nanocarriers is typically not reached as they are rapidly trafficked towards lysosomes for degradation and only a fraction of the internalized siRNA cargo is able to escape into the cytosol. We recently reported on the repurposing of widely applied cationic amphiphilic drugs (CADs) as siRNA delivery enhancers. Due to their physicochemical properties, CADs passively accumulate in the (endo)lysosomal compartment causing a transient permeabilization of the lysosomal membrane, which facilitates cytosolic drug delivery. In this work, we assessed a selection of cationic amphiphilic β2-agonists (i.e., salbutamol, formoterol, salmeterol and indacaterol) for their ability to enhance siRNA delivery in a lung epithelial and macrophage cell line. These drugs are widely used in the clinic for their bronchodilating effect in obstructive lung disease. As opposed to the least hydrophobic drugs salbutamol and formoterol, the more hydrophobic long-acting β2-agonist (LABA) salmeterol promoted siRNA delivery in both cell types for both uncoated and surfactant-coated nanogels, whereas indacaterol showed this effect solely in lung epithelial cells. Our results demonstrate the potential of both salmeterol and indacaterol to be repurposed as adjuvants for nanocarrier-mediated siRNA delivery to the lung, which could provide opportunities for drug combination therapy.

PMID:38367760 | DOI:10.1016/j.ejpb.2024.114223

Cancer Treat Res Commun. 2024 Feb 1;39:100792. doi: 10.1016/j.ctarc.2024.100792. Online ahead of print.

ABSTRACT

One of the cancers that affect men, prostate cancer considerably raises mortality rates for males around the world. Patients with prostate cancer can have a localized or advanced form of the illness. Digital rectal examinations, prostate-specific antigen analyses, and prostate biopsies are all used to identify prostate cancer. The onset, development, and spread of cancer are all correlated with mutations in specific genes. Radical prostatectomy, ablative radiation, and active surveillance are all forms of treatment for localized prostate cancer. Androgen deprivation therapy (ADT), radiation, and chemotherapy are given to men who have metastatic prostate cancer or have experienced a relapse. When compared to traditional cancer chemotherapeutic methods, the liposome-based drug delivery technology offers less toxic, biodegradable, and biocompatible nanomedicine. Liposomes offer great advantages for use in nanomedicines by improving the sensitivity, specificity, and persistence of these anti-malignant cell agents in the body. Liposomal formulations are undergoing clinical trials of variety of cancers including prostate cancer. The present narrative review describes the composition and types of liposomes, its advantages, disadvantages, and the methods of preparation, research studies, clinical applications, drug repurposing and administration.

PMID:38367412 | DOI:10.1016/j.ctarc.2024.100792

Anticancer Agents Med Chem. 2024 Feb 1. doi: 10.2174/0118715206282904240122063914. Online ahead of print.

ABSTRACT

Ovarian cancer (OC) is one of the most prevalent malignancies in female reproductive organs, and its 5-year survival is below 45%. Despite the advances in surgical and chemotherapeutic options, OC treatment is still a challenge, and new anticancer agents are urgently needed. Drug repositioning has gained significant attention in drug discovery, representing a smart way to identify new clinical applications for drugs whose human safety and pharmacokinetics have already been established, with great time and cost savings in pharmaceutical development endeavors. This review offers an update on the most promising drugs repurposable for OC treatment and/or prevention.

PMID:38367265 | DOI:10.2174/0118715206282904240122063914

BMJ Open. 2024 Feb 15;14(2):e075981. doi: 10.1136/bmjopen-2023-075981.

ABSTRACT

INTRODUCTION: Compared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the treatment of certain breast, colorectal, head and neck, lung and melanoma cancers. These drugs target immune checkpoint proteins to reduce the suppression of T cell activation by cancer cells. As T cell suppression is a hallmark of cancer common across anatomical sites, we hypothesise that immune checkpoint inhibitors could be repurposed for the treatment of additional cancers beyond the ones already indicated.

METHODS AND ANALYSIS: We will use two-sample Mendelian randomisation to investigate the effect of genetically proxied levels of protein targets of two immune checkpoint inhibitors-programmed cell death protein 1 and programmed death ligand 1-on survival of seven cancer types (breast, colorectal, head and neck, lung, melanoma, ovarian and prostate). Summary genetic association data will be obtained from prior genome-wide association studies of circulating protein levels and cancer survival in populations of European ancestry. Various sensitivity analyses will be performed to examine the robustness of findings to potential violations of Mendelian randomisation assumptions, collider bias and the impact of alternative genetic instrument construction strategies. The impact of treatment history and tumour stage on the findings will also be investigated using summary-level and individual-level genetic data where available.

ETHICS AND DISSEMINATION: No separate ethics approval will be required for these analyses as we will be using data from previously published genome-wide association studies which individually gained ethical approval and participant consent. Results from analyses will be submitted as an open-access peer-reviewed publication and statistical code will be made freely available on the completion of the analysis.

PMID:38365286 | DOI:10.1136/bmjopen-2023-075981

Sci Rep. 2024 Feb 14;14(1):3696. doi: 10.1038/s41598-024-54281-9.

ABSTRACT

Nipah virus (NiV), with its significantly higher mortality rate compared to COVID-19, presents a looming threat as a potential next pandemic, particularly if constant mutations of NiV increase its transmissibility and transmission. Considering the importance of preventing the facilitation of the virus entry into host cells averting the process of assembly forming the viral envelope, and encapsulating the nucleocapsid, it is crucial to take the Nipah attachment glycoprotein-human ephrin-B2 and matrix protein as dual targets. Repurposing approved small molecules in drug development is a strategic choice, as it leverages molecules with known safety profiles, accelerating the path to finding effective treatments against NiV. The approved small molecules from DrugBank were used for repurposing and were subjected to extra precision docking followed by absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling. The 4 best molecules were selected for 500 ns molecular dynamics (MD) simulation followed by Molecular mechanics with generalized Born and surface area solvation (MM-GBSA). Further, the free energy landscape, the principal component analysis followed by the defined secondary structure of proteins analysis were introspected. The inclusive analysis proposed that Iotrolan (DB09487) and Iodixanol (DB01249) are effective dual inhibitors, while Rutin (DB01698) and Lactitol (DB12942) were found to actively target the matrix protein only.

PMID:38355980 | DOI:10.1038/s41598-024-54281-9

Br J Pharmacol. 2024 Feb 15. doi: 10.1111/bph.16330. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: The post-acute sequelae of SARS-CoV-2 infection pose a significant global challenge, with nearly 50% of critical COVID-19 survivors manifesting persistent lung abnormalities. The lack of understanding about the molecular mechanisms and effective treatments hampers their management. Here, we employed microRNA (miRNA) profiling to decipher the systemic molecular underpinnings of the persistent pulmonary complications.

EXPERIMENTAL APPROACH: We conducted a longitudinal investigation including 119 critical COVID-19 survivors. A comprehensive pulmonary evaluation was performed in the short-term (median = 94.0 days after hospital discharge) and long-term (median = 358 days after hospital discharge). Plasma miRNAs were quantified at the short-term evaluation using the gold-standard technique, RT-qPCR. The analyses combined machine learning feature selection techniques with bioinformatic investigations. Two additional datasets were incorporated for validation.

KEY RESULTS: In the short-term, 84% of the survivors exhibited impaired lung diffusion (DLCO < 80% of predicted). One year post-discharge, 54.4% of this patient subgroup still presented abnormal DLCO . Four feature selection methods identified two specific miRNAs, miR-9-5p and miR-486-5p, linked to persistent lung dysfunction. The downstream experimentally validated targetome included 1473 genes, with heterogeneous enriched pathways associated with inflammation, angiogenesis and cell senescence. Validation studies using RNA-sequencing and proteomic datasets emphasized the pivotal roles of cell migration and tissue repair in persistent lung dysfunction. The repositioning potential of the miRNA targets was limited.

CONCLUSION AND IMPLICATIONS: Our study reveals early mechanistic pathways contributing to persistent lung dysfunction in critical COVID-19 survivors, offering a promising approach for the development of targeted disease-modifying agents.

PMID:38359818 | DOI:10.1111/bph.16330