Drug repositioning: Progress and challenges in drug discovery for various diseases

Decreasing the burden of non-alcoholic fatty liver disease: From therapeutic targets to drug discovery opportunities

Non-alcoholic fatty liver disease (NAFLD) presents a pervasive global pandemic, affecting approximately 25 % of the world's population. This grave health issue not only demands urgent attention but also stands as a significant economic concern on a global scale. The genesis of NAFLD can be primarily attributed to unhealthy dietary habits and a sedentary lifestyle, albeit certain genetic factors have also been recorded to contribute to its occurrence. NAFLD is characterized by fat accumulation in more than 5 % of hepatocytes according to histological analysis, or >5.6 % of lipid volume fraction in total liver weight in patients. The pathophysiology of NAFLD/non-alcoholic steatohepatitis (NASH) is multifactorial and the mechanisms underlying the progression to advanced forms remain unclear, thereby representing a challenge to disease therapy. Despite the substantial efforts from the scientific community and the large number of pre-clinical and clinical trials performed so far, only one drug was approved by the Food and Drug Administration (FDA) to treat NAFLD/NASH specifically. This review provides an overview of available information concerning emerging molecular targets and drug candidates tested in clinical studies for the treatment of NAFLD/NASH. Improving our understanding of NAFLD pathophysiology and pharmacotherapy is crucial not only to explore new molecular targets, but also to potentiate drug discovery programs to develop new therapeutic strategies. This knowledge endeavours scientific efforts to reduce the time for achieving a specific and effective drug for NAFLD or NASH management and improve patients' quality of life.

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

Overview of pro-inflammatory and pro-survival components in neuroinflammatory signalling and neurodegeneration

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

The molecular basis of the anticancer effect of statins

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia

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

A High-Throughput Screening Platform Identifies FDA-Approved Drugs That Inhibit SREBP Pathway Activation

Sterol regulatory element-binding protein (SREBP) transcription factors are central regulators of lipid homeostasis and are essential for lipid metabolic reprogramming that supports tumor growth in multiple cancers. SREBP pathway inhibitors have been identified, but bioavailable compounds are lacking. To address this need, we designed a novel approach for screening a collection of 4,474 FDA-approved drugs. SREBPs are conditionally essential and required under low lipid conditions. Leveraging this property, we screened for drugs that inhibited pancreatic cancer cell growth in lipid-poor, but not lipid-rich, medium. The primary screen identified 83 drugs that inhibited cell growth in a lipid-dependent manner. Secondary assays examining SREBP target gene expression, SREBP proteolytic cleavage, and effects on human breast cancer cells identified 13 FDA-approved drugs that inhibit SREBP pathway activation. Taken together, we demonstrated that our screening approach can identify SREBP inhibitors from a small library of compounds. This high-throughput screening platform enables screening of large compound collections to discover novel small molecule SREBP inhibitors.

Integrated transcriptomics- and structure-based drug repositioning identifies drugs with proteasome inhibitor properties

Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors.

Antibiofilm activity of promethazine against ESBL-producing strains of Escherichia coli in urinary catheters

The bacterium Escherichia coli is one of the main causes of urinary tract infections. The formation of bacterial biofilms, especially associated with the use of urinary catheters, contributes to the establishment of recurrent infections and the development of resistance to treatment. Strains of E. coli that produce extended-spectrum beta-lactamases (ESBL) have a greater ability to form biofilms. In addition, there is a lack of drugs available in the market with antibiofilm activity. Promethazine (PMZ) is an antihistamine known to have antimicrobial activity against different pathogens, including in the form of biofilms, but there are still few studies of its activity against ESBL E. coli biofilms. The aim of this study was to evaluate the antimicrobial activity of PMZ against ESBL E. coli biofilms, as well as to assess the application of this drug as a biofilm prevention agent in urinary catheters. To this end, the minimum inhibitory concentration and minimum bactericidal concentration of PMZ in ESBL E. coli strains were determined using the broth microdilution assay and tolerance level measurement. The activity of PMZ against the cell viability of the in vitro biofilm formation of ESBL E. coli was analyzed by the MTT colorimetric assay and its ability to prevent biofilm formation when impregnated in a urinary catheter was investigated by counting colony-forming units (CFU) and confirmed by scanning electron microscopy (SEM). PMZ showed bactericidal activity and significantly reduced (p < 0.05) the viability of the biofilm being formed by ESBL E. coli at concentrations of 256 and 512 μg/ml, as well as preventing the formation of biofilm on urinary catheters at concentrations starting at 512 μg/ml by reducing the number of CFUs, as also observed by SEM. Thus, PMZ is a promising candidate to prevent the formation of ESBL E. coli biofilms on abiotic surfaces.

A Computational Framework for Predicting Novel Drug Indications Using Graph Convolutional Network With Contrastive Learning

Inferring potential drug indications plays a vital role in the drug discovery process. It can be time-consuming and costly to discover novel drug indications through biological experiments. Recently, graph learning-based methods have gained popularity for this task. These methods typically treat the prediction task as a binary classification problem, focusing on modeling associations between drugs and diseases within a graph. However, labeled data for drug indication prediction is often limited and expensive to acquire. Contrastive learning addresses this challenge by aligning similar drug-disease pairs and separating dissimilar pairs in the embedding space. Thus, we developed a model called DrIGCL for drug indication prediction, which utilizes graph convolutional networks and contrastive learning. DrIGCL incorporates drug structure, disease comorbidities, and known drug indications to extract representations of drugs and diseases. By combining contrastive and classification losses, DrIGCL predicts drug indications effectively. In multiple runs of hold-out validation experiments, DrIGCL consistently outperformed existing computational methods for drug indication prediction, particularly in terms of top-k. Furthermore, our ablation study has demonstrated a significant improvement in the predictive capabilities of our model when utilizing contrastive learning. Finally, we validated the practical usefulness of DrIGCL by examining the predicted novel indications of Aspirin.

Drug repurposing in Rett and Rett-like syndromes: a promising yet underrated opportunity?

Rett syndrome (RTT) and Rett-like syndromes [i.e., CDKL5 deficiency disorder (CDD) and FOXG1-syndrome] represent rare yet profoundly impactful neurodevelopmental disorders (NDDs). The severity and complexity of symptoms associated with these disorders, including cognitive impairment, motor dysfunction, seizures and other neurological features significantly affect the quality of life of patients and families. Despite ongoing research efforts to identify potential therapeutic targets and develop novel treatments, current therapeutic options remain limited. Here the potential of drug repurposing (DR) as a promising avenue for addressing the unmet medical needs of individuals with RTT and related disorders is explored. Leveraging existing drugs for new therapeutic purposes, DR presents an attractive strategy, particularly suited for neurological disorders given the complexities of the central nervous system (CNS) and the challenges in blood-brain barrier penetration. The current landscape of DR efforts in these syndromes is thoroughly examined, with partiuclar focus on shared molecular pathways and potential common drug targets across these conditions.

The 3D pharmacophore modeling to explore new antischistosomal agents among US FDA approved drugs

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.

Computational Methods for the Discovery and Optimization of TAAR1 and TAAR5 Ligands

G-protein-coupled receptors (GPCRs) represent a family of druggable targets when treating several diseases and continue to be a leading part of the drug discovery process. Trace amine-associated receptors (TAARs) are GPCRs involved in many physiological functions with TAAR1 having important roles within the central nervous system (CNS). By using homology modeling methods, the responsiveness of TAAR1 to endogenous and synthetic ligands has been explored. In addition, the discovery of different chemo-types as selective murine and/or human TAAR1 ligands has helped in the understanding of the species-specificity preferences. The availability of TAAR1-ligand complexes sheds light on how different ligands bind TAAR1. TAAR5 is considered an olfactory receptor but has specific involvement in some brain functions. In this case, the drug discovery effort has been limited. Here, we review the successful computational efforts developed in the search for novel TAAR1 and TAAR5 ligands. A specific focus on applying structure-based and/or ligand-based methods has been done. We also give a perspective of the experimental data available to guide the future drug design of new ligands, probing species-specificity preferences towards more selective ligands. Hints for applying repositioning approaches are also discussed.

Wnt/β-catenin pathway as a potential target for Parkinson's disease: a cohort study of romosozumab using routinely collected health data in Japan

Introduction

Romosozumab is a monoclonal antibody approved for osteoporosis which targets sclerostin, an endogenous inhibitor of Wnt/β-catenin pathway. Given the essential roles of the Wnt/β-catenin pathway in various tissues, we hypothesized romosozumab treatment may influence other conditions.

Methods

This cohort study included patients prescribed romosozumab or parathyroid receptor (PTHR) agonists after 1 January 2019, using a Japanese electronic medical record database. The outcomes of interest included autoimmune disease, interstitial pneumonia, cardiovascular outcome, Alzheimer's disease, Parkinson's disease (PD), serious infections, and malignancies. A stabilized inverse probability-weighted Cox proportional hazard model was used to estimate the hazard ratios. Age- and gender-based subgroup analyses were conducted. Exploratory outcomes based on three-digit International Classification of Diseases 10th Revision-based were also examined.

Results

In total, 2,673 patients treated with romosozumab and 5,980 treated with PTHR agonists were identified, respectively. While most outcomes of interest showed no association with romosozumab, the risk of PD decreased with romosozumab (hazard ratio [95% confidence interval], 0.37 [0.14-0.94]) compared with PTHR agonist. Regarding the cardiovascular outcome, no notable association was identified overall; however, gender-based subgroup analysis suggested that male sex may be a potential risk factor with romosozumab treatment. Only 16 of 903 exploratory outcomes were potentially influenced by romosozumab.

Conclusion

Romosozumab lowered the risk of PD development compared with PTHR agonist. The study also highlights the utility of routinely collected health data for drug repositioning. While further validation is warranted, the findings suggest that the Wnt-β-catenin pathway holds promise as a therapeutic target for PD.

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Repurposing lipid-lowering drugs on asthma and lung function: evidence from a genetic association analysis

OBJECTIVE

To explore the correlation between asthma risk and genetic variants affecting the expression or function of lipid-lowering drug targets.

METHODS

We conducted Mendelian randomization (MR) analyses using variants in several genes associated with lipid-lowering medication targets: HMGCR (statin target), PCSK9 (alirocumab target), NPC1L1 (ezetimibe target), APOB (mipomersen target), ANGPTL3 (evinacumab target), PPARA (fenofibrate target), and APOC3 (volanesorsen target), as well as LDLR and LPL. Our objective was to investigate the relationship between lipid-lowering drugs and asthma through MR. Finally, we assessed the efficacy and stability of the MR analysis using the MR Egger and inverse variance weighted (IVW) methods.

RESULTS

The elevated triglyceride (TG) levels associated with the APOC3, and LPL targets were found to increase asthma risk. Conversely, higher LDL-C levels driven by LDLR were found to decrease asthma risk. Additionally, LDL-C levels (driven by APOB, NPC1L1 and HMGCR targets) and TG levels (driven by the LPL target) were associated with improved lung function (FEV1/FVC). LDL-C levels driven by PCSK9 were associated with decreased lung function (FEV1/FVC).

CONCLUSION

In conclusion, our findings suggest a likely causal relationship between asthma and lipid-lowering drugs. Moreover, there is compelling evidence indicating that lipid-lowering therapies could play a crucial role in the future management of asthma.

Strategies of Pharmacological Repositioning for the Treatment of Medically Relevant Mycoses

Fungal infections represent a worldwide concern for public health, due to their prevalence and significant increase in cases each year. Among the most frequent mycoses are those caused by members of the genera Candida, Cryptococcus, Aspergillus, Histoplasma, Pneumocystis, Mucor, and Sporothrix, which have been treated for years with conventional antifungal drugs, such as flucytosine, azoles, polyenes, and echinocandins. However, these microorganisms have acquired the ability to evade the mechanisms of action of these drugs, thus hindering their treatment. Among the most common evasion mechanisms are alterations in sterol biosynthesis, modifications of drug transport through the cell wall and membrane, alterations of drug targets, phenotypic plasticity, horizontal gene transfer, and chromosomal aneuploidies. Taking into account these problems, some research groups have sought new therapeutic alternatives based on drug repositioning. Through repositioning, it is possible to use existing pharmacological compounds for which their mechanism of action is already established for other diseases, and thus exploit their potential antifungal activity. The advantage offered by these drugs is that they may be less prone to resistance. In this article, a comprehensive review was carried out to highlight the most relevant repositioning drugs to treat fungal infections. These include antibiotics, antivirals, anthelmintics, statins, and anti-inflammatory drugs.

Amoebicidal Effect of COVID Box Molecules against Acanthamoeba: A Study of Cell Death

Acanthamoeba spp. can cause a sight threatening disease. At present, the current treatments used to treat Acanthamoeba spp. Infections, such as biguanide-based antimicrobials, remain inefficacious, with the appearance of resistant forms and high cytotoxicity to host cells. In this study, an initial screening was conducted against Acanthamoeba castellanii Neff and murine macrophages J774A.1 using alamarBlue™. Among the 160 compounds included in the cited box, 90% exhibited an inhibition of the parasite above 80%, while only 18.75% of the compounds inhibited the parasite with a lethality towards murine macrophage lower than 20%. Based on the amoebicidal activity, the cytotoxicity assay, and availability, Terconazole was chosen for the elucidation of the action mode in two clinical strains, Acanthamoeba culbertsoni and Acanthamoeba castellanii L10. A fluorescence image-based system and proteomic techniques were used to investigate the effect of the present azole on the cytoskeleton network and various programmed cell death features, including chromatin condensation and mitochondria dysfunction. Taking all the results together, we can suggest that Terconazole can induce programmed cell death (PCD) via the inhibition of sterol biosynthesis inhibition.

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia

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

Author Summary

This manuscript outlines our project involving the application of AGATHA, an AI-based literature mining tool, to discover drugs with the potential for repurposing in the context of neurocognitive disorders. The primary objective is to identify connections between approved medications and specific health conditions through advanced statistical analysis, including techniques like Partial Least Squares Discriminant Analysis (PLSDA) and unsupervised clustering. The methodology involves grouping scientific terms related to different health conditions and genes, followed by building discrimination models to extract lists of disease-specific genes. These genes are then analyzed through pathway analysis to select candidates for drug repurposing.

Improving the treatment of bacterial infections caused by multidrug-resistant bacteria through drug repositioning

Drug repurposing (repositioning) is a dynamically-developing area in the search for effective therapy of infectious diseases. Repositioning existing drugs with a well-known pharmacological and toxicological profile is an attractive method for quickly discovering new therapeutic indications. The off-label use of drugs for infectious diseases requires much less capital and time, and can hasten progress in the development of new antimicrobial drugs, including antibiotics. The use of drug repositioning in searching for new therapeutic options has brought promising results for many viral infectious diseases, such as Ebola, ZIKA, Dengue, and HCV. This review describes the most favorable results for repositioned drugs for the treatment of bacterial infections. It comprises publications from various databases including PubMed and Web of Science published from 2015 to 2023. The following search keywords/strings were used: drug repositioning and/or repurposing and/or antibacterial activity and/or infectious diseases. Treatment options for infections caused by multidrug-resistant bacteria were taken into account, including methicillin-resistant staphylococci, multidrug-resistant Mycobacterium tuberculosis, or carbapenem-resistant bacteria from the Enterobacteriaceae family. It analyses the safety profiles of the included drugs and their synergistic combinations with antibiotics and discusses the potential of antibacterial drugs with antiparasitic, anticancer, antipsychotic effects, and those used in metabolic diseases. Drug repositioning may be an effective response to public health threats related to the spread of multidrug-resistant bacterial strains and the growing antibiotic resistance of microorganisms.

Antidepressant-induced membrane trafficking regulates blood-brain barrier permeability

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.

Cyclodextrin encapsulation enabling the anticancer repositioning of disulfiram: Preparation, analytical and in vitro biological characterization of the inclusion complexes

Drug repositioning is a high-priority and feasible strategy in the field of oncology research, where the unmet medical needs are continuously unbalanced. Disulfiram is a potential non-chemotherapeutic, adjuvant anticancer agent. However, the clinical translation is limited by the drug's poor bioavailability. Therefore, the molecular encapsulation of disulfiram with cyclodextrins is evaluated to enhance the solubility and stability of the drug. The present work describes for the first time the complexation of disulfiram with randomly methylated-β-cyclodextrin. A parallel analytical andin vitrobiological comparison of disulfiram inclusion complexes with hydroxypropyl-β-cyclodextrin, randomly methylated-β-cyclodextrin and sulfobutylether-β-cyclodextrin is conducted. A significant drug solubility enhancement by about 1000-folds and fast dissolution in 1 min is demonstrated. Thein vitrodissolution-permeation studies and proliferation assays demonstrate the solubility-dependent efficacy of the drug. Throughout the different cancer cell lines' characteristics and disulfiram unspecific antitumoral activity, the inhibitory efficacy of the cyclodextrin encapsulated drug on melanoma (IC50 about 100 nM) and on glioblastoma (IC50 about 7000 nM) cell lines differ by a magnitude. This pre-formulation screening experiment serves as a proof of concept of using cyclodextrin encapsulation as a platform tool for further drug delivery development in repositioning areas.

Drug repurposing for neurodegenerative diseases

Neurodegenerative diseases (NDDs) are neuronal problems that include the brain and spinal cord and result in loss of sensory and motor dysfunction. Common NDDs include Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS) etc. The occurrence of these diseases increases with age and is one of the challenging problems among elderly people. Though, several scientific research has demonstrated the key pathologies associated with NDDs still the underlying mechanisms and molecular details are not well understood and need to be explored and this poses a lack of effective treatments for NDDs. Several lines of evidence have shown that NDDs have a high prevalence and affect more than a billion individuals globally but still, researchers need to work forward in identifying the best therapeutic target for NDDs. Thus, several researchers are working in the directions to find potential therapeutic targets to alter the disease pathology and treat the diseases. Several steps have been taken to identify the early detection of the disease and drug repurposing for effective treatment of NDDs. Moreover, it is logical that current medications are being evaluated for their efficacy in treating such disorders; therefore, drug repurposing would be an efficient, safe, and cost-effective way in finding out better medication. In the current manuscript we discussed the utilization of drugs that have been repurposed for the treatment of AD, PD, HD, MS, and ALS.

Drug repurposing for parasitic protozoan diseases

Protozoan parasites are major hazards to human health, society, and the economy, especially in equatorial regions of the globe. Parasitic diseases, including leishmaniasis, malaria, and others, contribute towards majority of morbidity and mortality. Around 1.1 million people die from these diseases annually. The lack of licensed vaccinations worsens the worldwide impact of these diseases, highlighting the importance of safe and effective medications for their prevention and treatment. However, the appearance of drug resistance in parasites continuously affects the availability of medications. The demand for novel drugs motivates global antiparasitic drug discovery research, necessitating the implementation of many innovative ways to maintain a continuous supply of promising molecules. Drug repurposing has come out as a compelling tool for drug development, offering a cost-effective and efficient alternative to standard de novo approaches. A thorough examination of drug repositioning candidates revealed that certain drugs may not benefit significantly from their original indications. Still, they may exhibit more pronounced effects in other disorders. Furthermore, certain medications can produce a synergistic effect, resulting in enhanced therapeutic effectiveness when given together. In this chapter, we outline the approaches employed in drug repurposing (sometimes referred to as drug repositioning), propose novel strategies to overcome these hurdles and fully exploit the promise of drug repurposing. We highlight a few major human protozoan diseases and a range of exemplary drugs repurposed for various protozoan infections, providing excellent outcomes for each disease.

Drug repurposing for regenerative medicine and cosmetics: Scientific, technological and economic issues

Regenerative medicine and cosmetics are currently two outstanding fields for drug discovery. Although many pharmaceutical products for regenerative medicine and cosmetics have received approval by official agencies, several challenges are still needed to overcome, especially financial and time issues. As a result, drug repositioning, which is the usage of previously approved drugs for new treatment, stands out as a promising approach to tackle these problems. Recently, increasing scientific evidence is collected to demonstrate the applicability of this novel method in the field of regenerative medicine and cosmetics. Experts in drug development have also taken advantage of novel technologies to discover new candidates for repositioning purposes following computational approach, one of two main approaches of drug repositioning. Therefore, numerous repurposed candidates have obtained approval to enter the market and have witnessed financial success such as minoxidil and fingolimod. The benefits of drug repositioning are undeniable for regenerative medicine and cosmetics. However, some aspects still need to be carefully considered regarding this method including actual effectiveness during clinical trials, patent regulations, data integration and analysis, publicly unavailable databases as well as environmental concerns and more effort are required to overcome these obstacles.

Drug repurposing for bacterial infections

Repurposing pharmaceuticals is a technique used to find new, alternate clinical applications for approved drug molecules. It may include altering the drug formulation, route of administration, dose or the dosage regimen. The process of repurposing medicines starts with screening libraries of previously approved drugs for the targeted disease condition. If after an the initial in silico, in vitro or in vivo experimentation, the molecule has been found to be active against a particular target, the molecule is considered as a good candidate for clinical trials. As the safety profile of such molecules is available from the previous data, significant time and resources are saved. These advantages of drug repurposing approach make it especially helpful for finding treatments for rapidly evolving conditions including bacterial infections. An ever-increasing incidence of antimicrobial resistance, owing to the mutations in bacterial genome, leads to therapeutic failure of many approved antibiotics. Repurposing the approved drug molecules for use as antibiotics can provide an effective means for the combating life-threatening bacterial diseases. A number of drugs have been considered for drug repurposing against bacterial infections. These include, but are not limited to, Auranofin, Closantel, and Toremifene that have been repurposed for various infections. In addition, the reallocation of route of administration, redefining dosage regimen and reformulation of dosage forms have also been carried out for repurposing purpose. The current chapter addresses the drug discovery and development process with relevance to repurposing against bacterial infections.

Inhibitors of amyloid fibril formation

Many diseases are caused by misfolded and denatured proteins, leading to neurodegenerative diseases. In recent decades researchers have developed a variety of compounds, including polymeric inhibitors and natural compounds, antibodies, and chaperones, to inhibit protein aggregation, decrease the toxic effects of amyloid fibrils, and facilitate refolding proteins. The causes and mechanisms of amyloid formation are still unclear, and there are no effective treatments for Amyloid diseases. This section describes research and achievements in the field of inhibiting amyloid accumulation and also discusses the importance of various strategies in facilitating the removal of aggregates species (refolding) in the treatment of neurological diseases such as chemical methods like as, small molecules, metal chelators, polymeric inhibitors, and nanomaterials, as well as the use of biomolecules (peptide and, protein, nucleic acid, and saccharide) as amyloid inhibitors, are also highlighted.

The circadian rhythm: A new target of natural products that can protect against diseases of the metabolic system, cardiovascular system, and nervous system

BACKGROUND

The treatment of metabolic system, cardiovascular system, and nervous system diseases remains to be explored. In the internal environment of organisms, the metabolism of substances such as carbohydrates, lipids and proteins (including biohormones and enzymes) exhibit a certain circadian rhythm to maintain the energy supply and material cycle needed for the normal activities of organisms. As a key factor for the health of organisms, the circadian rhythm can be disrupted by pathological conditions, and this disruption accelerates the progression of diseases and results in a vicious cycle. The current treatments targeting the circadian rhythm for the treatment of metabolic system, cardiovascular system, and nervous system diseases have certain limitations, and the identification of safer and more effective circadian rhythm regulators is needed.

AIM OF THE REVIEW

To systematically assess the possibility of using the biological clock as a natural product target for disease intervention, this work reviews a range of evidence on the potential effectiveness of natural products targeting the circadian rhythm to protect against diseases of the metabolic system, cardiovascular system, and nervous system. This manuscript focuses on how natural products restore normal function by affecting the amplitude of the expression of circadian factors, sleep/wake cycles and the structure of the gut microbiota.

KEY SCIENTIFIC CONCEPTS OF THE REVIEW

This work proposes that the circadian rhythm, which is regulated by the amplitude of the expression of circadian rhythm-related factors and the sleep/wake cycle, is crucial for diseases of the metabolic system, cardiovascular system and nervous system and is a new target for slowing the progression of diseases through the use of natural products. This manuscript provides a reference for the molecular modeling of natural products that target the circadian rhythm and provides a new perspective for the time-targeted action of drugs.

Revitalizing Cancer Treatment: Exploring the Role of Drug Repurposing

Cancer persists as a global challenge necessitating continual innovation in treatment strategies. Despite significant advancements in comprehending the disease, cancer remains a leading cause of mortality worldwide, exerting substantial economic burdens on healthcare systems and societies. The emergence of drug resistance further complicates therapeutic efficacy, underscoring the urgent need for alternative approaches. Drug repurposing, characterized by the utilization of existing drugs for novel clinical applications, emerges as a promising avenue for addressing these challenges. Repurposed drugs, comprising FDA-approved (in other disease indications), generic, off-patent, and failed medications, offer distinct advantages including established safety profiles, cost-effectiveness, and expedited development timelines compared to novel drug discovery processes. Various methodologies, such as knowledge-based analyses, drug-centric strategies, and computational approaches, play pivotal roles in identifying potential candidates for repurposing. However, despite the promise of repurposed drugs, drug repositioning confronts formidable obstacles. Patenting issues, financial constraints associated with conducting extensive clinical trials, and the necessity for combination therapies to overcome the limitations of monotherapy pose significant challenges. This review provides an in-depth exploration of drug repurposing, covering a diverse array of approaches including experimental, re-engineering protein, nanotechnology, and computational methods. Each of these avenues presents distinct opportunities and obstacles in the pursuit of identifying novel clinical uses for established drugs. By examining the multifaceted landscape of drug repurposing, this review aims to offer comprehensive insights into its potential to transform cancer therapeutics.

Drug repositioning and ovarian cancer, a study based on Mendelian randomisation analysis

Background

The role of drug repositioning in the treatment of ovarian cancer has received increasing attention. Although promising results have been achieved, there are also major controversies.

Methods

In this study, we conducted a drug-target Mendelian randomisation (MR) analysis to systematically investigate the reported effects and relevance of traditional drugs in the treatment of ovarian cancer. The inverse-variance weighted (IVW) method was used in the main analysis to estimate the causal effect. Several MR methods were used simultaneously to test the robustness of the results.

Results

By screening 31 drugs with 110 targets, FNTA, HSPA5, NEU1, CCND1, CASP1, CASP3 were negatively correlated with ovarian cancer, and HMGCR, PLA2G4A, ITGAL, PTGS1, FNTB were positively correlated with ovarian cancer.

Conclusion

Statins (HMGCR blockers), lonafarnib (farnesyltransferase inhibitors), the anti-inflammatory drug aspirin, and the anti-malarial drug adiponectin all have potential therapeutic roles in ovarian cancer treatment.

Network-based identification of key proteins and repositioning of drugs for non-small cell lung cancer

BACKGROUND

NSCLC is a lethal cancer that is highly prevalent and accounts for 85% of cases of lung cancer. Conventional cancer treatments, such as chemotherapy and radiation, frequently exhibit limited efficacy and notable adverse reactions. Therefore, a drug repurposing method is proposed for effective NSCLC treatment.

AIMS

This study aims to evaluate candidate drugs that are effective for NSCLC at the clinical level using a systems biology and network analysis approach.

METHODS

Differentially expressed genes in transcriptomics data were identified using the systems biology and network analysis approaches. A network of gene co-expression was developed with the aim of detecting two modules of gene co-expression. Following that, the Drug-Gene Interaction Database was used to find possible drugs that target important genes within two gene co-expression modules linked to non-small cell lung cancer (NSCLC). The use of Cytoscape facilitated the creation of a drug-gene interaction network. Finally, gene set enrichment analysis was done to validate candidate drugs.

RESULTS

Unlike previous research on repositioning drugs for NSCLC, which uses a gene co-expression network, this project is the first to research both gene co-expression and co-occurrence networks. And the co-occurrence network also accounts for differentially expressed genes in cancer cells and their adjacent normal cells. For effective management of non-small cell lung cancer (NSCLC), drugs that show higher gene regulation and gene affinity within the drug-gene interaction network are thought to be important. According to the discourse, NSCLC genes have a lot of control over medicines like vincristine, fluorouracil, methotrexate, clotrimazole, etoposide, tamoxifen, sorafenib, doxorubicin, and pazopanib.

CONCLUSION

Hence, there is a possibility of repurposing these drugs for the treatment of non-small-cell lung cancer.

GCNGAT: Drug-disease association prediction based on graph convolution neural network and graph attention network

Predicting drug-disease associations can contribute to discovering new therapeutic potentials of drugs, and providing important association information for new drug research and development. Many existing drug-disease association prediction methods have not distinguished relevant background information for the same drug targeted to different diseases. Therefore, this paper proposes a drug-disease association prediction model based on graph convolutional network and graph attention network (GCNGAT) to reposition marketed drugs under the distinguishment of background information. Firstly, in order to obtain initial drug-disease information, a drug-disease heterogeneous graph structure is constructed based on all known drug-disease associations. Secondly, based on the heterogeneous graph structure, the corresponding subgraphs of each group of drug-disease association pairs are extracted to distinguish different background information for the same drug from different diseases. Finally, a model combining Graph neural network with global Average pooling (GnnAp) is designed to predict potential drug-disease associations by learning drug-disease interaction feature representations. The experimental results show that adding subgraph extraction can effectively improve the prediction performance of the model, and the graph representation learning module can fully extract the deep features of drug-disease. Using the 5-fold cross-validation, the proposed model (GCNGAT) achieves AUC (Area Under the receiver operating characteristic Curve) values of 0.9182 and 0.9417 on the PREDICT dataset and CDataset dataset, respectively. Compared with other predictors on the same dataset (PREDICT dataset), GCNGAT outperforms the existing best-performing model (PSGCN), with a 1.58% increase in the AUC value. It is anticipated that this model can provide experimental reference for drug repositioning and further promote the drug research and development process.

SGCLDGA: unveiling drug-gene associations through simple graph contrastive learning

Drug repurposing offers a viable strategy for discovering new drugs and therapeutic targets through the analysis of drug-gene interactions. However, traditional experimental methods are plagued by their costliness and inefficiency. Despite graph convolutional network (GCN)-based models' state-of-the-art performance in prediction, their reliance on supervised learning makes them vulnerable to data sparsity, a common challenge in drug discovery, further complicating model development. In this study, we propose SGCLDGA, a novel computational model leveraging graph neural networks and contrastive learning to predict unknown drug-gene associations. SGCLDGA employs GCNs to extract vector representations of drugs and genes from the original bipartite graph. Subsequently, singular value decomposition (SVD) is employed to enhance the graph and generate multiple views. The model performs contrastive learning across these views, optimizing vector representations through a contrastive loss function to better distinguish positive and negative samples. The final step involves utilizing inner product calculations to determine association scores between drugs and genes. Experimental results on the DGIdb4.0 dataset demonstrate SGCLDGA's superior performance compared with six state-of-the-art methods. Ablation studies and case analyses validate the significance of contrastive learning and SVD, highlighting SGCLDGA's potential in discovering new drug-gene associations. The code and dataset for SGCLDGA are freely available at https://github.com/one-melon/SGCLDGA.

Drug-repurposing by virtual and experimental screening of PFKFB3 inhibitors for pancreatic cancer therapy

Pancreatic cancer (PC) is the most frequently occurring cancer, with few effective treatments and a 5-year survival rate of only about 11%. It is characterized by stiff interstitium and pressure on blood vessels, leading to an increased glycolytic metabolism. PFKFB3 plays an important role in glycolysis, and its products (fructose-2,6-bisphosphate), which are allosteric PFK1 activators, limit the glycolytic rate. In this study, 14 PFKFB3 inhibitors were obtained by virtually screening the FDA-approved compound library. Subsequently, the in-vitro investigations confirmed that Lomitapide and Cabozantinib S-malate exhibit the excellent potential to inhibit PFKFB3. The combined administration of Lomitapide and Gemcitabine at a certain molar ratio indicated an enhanced anti-tumor effect in Orthotopic Pancreatic Cancer (OPC) models. This investigation provides a new treatment strategy for PC therapy.

First Description of Marinoquinoline Derivatives' Activity against Toxoplasma gondii

Toxoplasmosis is a globally prevalent zoonotic disease with significant clinical implications, including neurotoxoplasmosis, a leading cause of cerebral lesions in AIDS patients. The current pharmacological treatments for toxoplasmosis face clinical limitations, necessitating the urgent development of new therapeutics. Natural sources have yielded diverse bioactive compounds, serving as the foundation for clinically used derivatives. The exploration of marine bacteria-derived natural products has led to marinoquinolines, which feature a pyrroloquinoline core and demonstrate in vitro and in vivo anti-Plasmodium activity. This study investigates the in vitro anti-Toxoplasma gondii potential of six marinoquinoline derivatives. Additionally, it conducts absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions, and evaluates the in vivo efficacy of one selected compound. The compounds displayed half-maximal effective concentration (EC50) values between 1.31 and 3.78 µM and half-maximal cytotoxic concentration (CC50) values ranging from 4.16 to 30.51 µM, resulting in selectivity indices (SI) from 3.18 to 20.85. MQ-1 exhibiting the highest in vitro SI, significantly reduced tachyzoite numbers in the peritoneum of RH-infected Swiss mice when it was orally administered at 12.5 mg/kg/day for eight consecutive days. Also, MQ-1 significantly reduced the cerebral parasite burden in chronically ME49 infected C57BL/6 mice when it was orally administered at 25 mg/kg/day for 10 consecutive days. These findings underscore the promising anti-T. gondii activity of marinoquinolines and their potential as novel therapeutic agents against this disease.

Repurposing a human acetyl-CoA carboxylase inhibitor firsocostat to treat fungal candidiasis alone and in combination

Opportunistic fungal infections, particularly caused by Candida albicans, remain a common cause of high morbidity and mortality in immunocompromised patients. The escalating prevalence of antifungal drug resistance necessitates the immediate exploration of alternative treatment strategies to combat these life-threatening fungal diseases. In this study, we investigated the antifungal efficacy of firsocostat, a human acetyl-CoA carboxylase (ACC) inhibitor, against C. albicans. Firsocostat alone displayed moderate antifungal activity, while combining it with voriconazole, itraconazole, or amphotericin B exhibited synergistic effects across almost all drug-sensitive and drug-resistant C. albicans strains tested. These observed synergies were further validated in two mouse models of oropharyngeal and systemic candidiasis, where the combination therapies demonstrated superior fungicidal effects compared to monotherapy. Moreover, firsocostat was shown to directly bind to C. albicans ACC and inhibit its enzymatic activity. Sequencing spontaneous firsocostat-resistant mutants revealed mutations mapping to C. albicans ACC, confirming that firsocostat has retained its target in C. albicans. Overall, our findings suggest that repurposing firsocostat, either alone or in combination with other antifungal agents, holds promising potential in the development of antifungal drugs and the treatment of candidiasis.

Comparing the interactions of nitrendipine with lysozyme or human serum albumin and the effects of vitamin C and naringin on these interactions by spectroscopy and molecular docking methods

The interactions between drugs and proteins play a pivotal role in determining the pharmacological effects and disposition of drugs within the human body. This study focuses on exploring the interaction between nitrendipine and lysozyme/human serum albumin. Spectroscopic analysis indicated a compound static quenching, indicative of the formation of stable complexes between the drug and proteins. The addition of vitamin C or naringin resulted in a decrease of the binding constant between nitrendipine and lysozyme/human serum albumin. The presence of these compounds may disrupt the interactions between the drug and proteins, potentially leading to an increased concentration of free nitrendipine in the bloodstream. Nitrendipine binds more easily to human serum albumin at 310 K, and human serum albumin has an average binding site ratio with nitrendipine approximately 0.1 higher than that with lysozyme. Vitamin C has a greater impact on the binding constant of nitrendipine to human serum albumin and lysozyme. Compared to the binary system of proteins with the drug, the ternary system with the addition of vitamin C at 310 K reduces the binding constants of lysozyme and human serum albumin by 85%. In conclusion, this study explores the significance of considering drug-protein interactions in understanding drug behavior and potential drug-food interactions.

Biological Activities of Zinc Oxide Nanoparticles Green Synthesized Using the Aqueous Extract of Dracocephalum kotschyi Boiss

BACKGROUND

Dracocephalum kotschyi Boiss. is known as a native medicinal plant of Iran.

OBJECTIVE

In this study, aqueous extract of D. kotschyi was used to synthesize ZnO-NPs. To produce ZnO-NPs, aerial parts of D. kotschyi were powdered and then macerated for obtaining aqueous extract, after that, aqueous extract was used to reduse zinc nitrate to ZnO-NPs.

METHODS

To confirm nanoparticles synthesis, SEM, TEM, UV-Vis, FTIR, and XRD were used. The synthesized ZnO-NPs were studied for antimicrobial activities by microdilution method for calculating MIC and MBC. Analysis of ZnO-NPs confirmed successful synthesis by extract of D. kotschyi.

RESULTS

The sizes of ZnO-NPs were estimated 50-200 nm in diameter. Antibacterial and antifungal experiments showed potent activities against Staphylococos aureus, Pseudomonas aeruginosa and Candida albicans. The results of the studies showed that the nanoparticles synthesized with the aqueous extract of D. kotschyi have a much greater antimicrobial effect than the aqueous extract of D. kotschyi and zinc nanoparticles, each alone (MIC values 3.7 to 7.5 mg/ml).

CONCLUSION

The noteworthy point is that the inhibitory rate of synthesized zinc oxide nanoparticles is higher compared to broad-spectrum antibiotics, such as chloramphenicol (MIC values 15 mg/ml). Determining the therapeutic and toxic dose of this product for humans requires further investigation and clinical trials.

Solid Lipid Nanoparticles Enhancing the Leishmanicidal Activity of Delamanid

Leishmaniasis, a zoonotic parasitic disease transmitted by infected sandflies, impacts nearly 1 million people yearly and is endemic in many countries across Asia, Africa, the Americas, and the Mediterranean; despite this, it remains a neglected disease with limited effective treatments, particularly in impoverished communities with limited access to healthcare. This study aims to repurpose approved drugs for an affordable leishmaniasis treatment. After the screening of potential drug candidates by reviewing databases and utilizing molecular docking analysis, delamanid was chosen to be incorporated into solid lipid nanoparticles (SLNPs). Both in cellulo and in vivo tests confirmed the successful payload release within macrophages and through the epidermis following topical application on murine skin. The evaluation of macrophages infected with L. infantum amastigotes showed that the encapsulated delamanid exhibited greater leishmanicidal activity compared with the free drug. The process of encapsulating delamanid in SLNPs, as demonstrated in this study, places a strong emphasis on employing minimal technology, ensuring energy efficiency, cost-effectiveness, and reproducibility. It enables consistent, low-cost production of nanomedicines, even on a small scale, offering a promising step toward more accessible and effective leishmaniasis treatments.

Scaffold Hopping and Structural Modification of NSC 663284: Discovery of Potent (Non)Halogenated Aminobenzoquinones

The development of new anticancer drugs is still ongoing as a solution to the unsatisfactory results obtained by chemotherapy patients. Our previous studies on natural product-based anticancer agents led us to synthesize a new series of Plastoquinone (PQ) analogs and study their anticancer effects. Four members of PQ analogs (PQ1-4) were designed based on the scaffold hopping strategy; the design was later completed with structural modification. The obtained PQ analogs were synthesized and biologically evaluated against different cancer genotypes according to NCI-60 screening in vitro. According to the NCI results, bromo and iodo-substituted PQ analogs (PQ2 and PQ3) showed remarkable anticancer activities with a wide-spectrum profile. Among the two selected analogs (PQ2 and PQ3), PQ2 showed promising anticancer activity, in particular against leukemia cell lines, at both single- and five-dose NCI screenings. This compound was also detected by MTT assay to reveal significant selectivity between Jurkat cells and PBMC (healthy) compared to imatinib. Further in silico studies indicated that PQ2 was able to occupy the ATP-binding cleft of Abl TK, one of the main targets of leukemia, through key interactions similar to dasatinib and imatinib. PQ2 is also bound to the minor groove of the double helix of DNA. Based on computational pharmacokinetic studies, PQ2 possessed a remarkable drug-like profile, making it a potential anti-leukemia drug candidate for future studies.

Repurposing Salicylamides to Combat Phytopathogenic Bacteria and Induce Plant Defense Responses

Based on the research strategy of "drug repurposing", a series of derivatives and marketed drugs that containing salicylic acid skeleton were tested for their antibacterial activities against phytopathogens. Salicylic acid can not only regulate some important growth metabolism of plants, but also induce plant disease resistance. The bioassay results showed that the salicylamides exhibited excellent antibacterial activity. Especially, oxyclozanide showed the best antibacterial effect against Xanthomonas oryzae, Xanthomonas axonopodis pv. citri and Pectobacterium atroseptica with MICs of 0.78, 3.12 and 12.5 μg.mL-1, respectively. In vivo experiments with rice bacterial leaf blight had further demonstrated that oxyclozanide exhibited stronger antibacterial activity than the commercial bactericide, thiodiazole copper. Oxyclozanide could induce plant defense responses through the determination of salicylic acid content and the activities of defense-related enzymes including CAT, POD, and SOD in rice. The preliminarily antibacterial mechanism study indicated that oxyclozanide exhibited the antibacterial activity by disrupting cell integrity and reducing bacterial pathogenicity. Additionally, oxyclozanide could induce plant defense responses through the determination of salicylic acid content.

Unveiling Potential Targeted Therapeutic Opportunities for Co-Overexpressed Targeting Protein for Xklp2 and Aurora-A Kinase in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most prevalent and leading causes of cancer deaths globally, with limited diagnostic and clinically significant therapeutic targets. Identifying the genes and processes involved in developing and progressing LUAD is crucial for developing effective targeted therapeutics and improving patient outcomes. Therefore, the study aimed to explore the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) and gene expression profile datasets involving GSE10072, GSE31210, and GSE32863 from the Gene Expression Omnibus (GEO) databases. The differential gene expression and the downstream analysis determined clinically significant biomarkers using a network-based approach. These therapeutic targets predominantly enriched the dysregulation of mitotic cell cycle regulation and revealed the co-overexpression of Aurora-A Kinase (AURKA) and Targeting Protein for Xklp2 (TPX2) with high survival risk in LUAD patients. The hydrophobic residues of the AURKA-TPX2 interaction were considered as the target site to block the autophosphorylation of AURKA during the mitotic cell cycle. The tyrosine kinase inhibitor (TKI) dacomitinib demonstrated the strong binding potential to hinder TPX2, shielding the AURKA destabilization. This in silico study lays the foundation for repurposing targeted therapeutic options to impede the Protein-Protein Interactions (PPIs) in LUAD progression and aid in future translational investigations.

Aceclofenac/Citronellol Oil Nanoemulsion Repurposing Study: Formulation, In Vitro Characterization, and In Silico Evaluation of Their Antiproliferative and Pro-Apoptotic Activity against Melanoma Cell Line

Aceclofenac (ACF) is a widely used non-steroidal anti-inflammatory drug (NSAID) known for its effectiveness in treating pain and inflammation. Recent studies have demonstrated that ACF possesses antiproliferative properties, inhibiting the growth of cancer cells in various cancer cell lines. Citronellol, a monoterpenoid alcohol found in essential oils, exhibits antioxidant properties and activities such as inhibiting cell growth and acetylcholinesterase inhibition. In this study, the objective was to formulate and evaluate an aceclofenac/citronellol oil nanoemulsion for its antiproliferative effects on melanoma. The optimal concentrations of citronellol oil, Tween 80, and Transcutol HP were determined using a pseudoternary phase diagram. The formulated nanoemulsions were characterized for droplet size, zeta potential, thermophysical stability, and in vitro release. The selected formula (F1) consisted of citronellol oil (1 gm%), Tween 80 (4 gm%), and Transcutol HP (1 gm%). F1 exhibited a spherical appearance with high drug content, small droplet size, and acceptable negative zeta potential. The amorphous state of the drug in the nanoemulsion was confirmed by Differential Scanning Calorimetry, while FTIR analysis indicated its homogenous solubility. The nanoemulsion showed significant antiproliferative activity, with a lower IC50 value compared to aceclofenac or citronellol alone. Flow cytometric analysis revealed cell cycle arrest and increased apoptosis induced by the nanoemulsion. In silico studies provided insights into the molecular mechanism underlying the observed antitumor activity. In conclusion, the developed aceclofenac/citronellol oil nanoemulsion exhibited potent cytotoxicity and pro-apoptotic effects, suggesting its potential as a repurposed antiproliferative agent for melanoma treatment. In a future plan, further animal model research for validation is suggested.

Indole-Based Compounds as Potential Drug Candidates for SARS-CoV-2

The COVID-19 pandemic has posed a significant threat to society in recent times, endangering human health, life, and economic well-being. The disease quickly spreads due to the highly infectious SARS-CoV-2 virus, which has undergone numerous mutations. Despite intense research efforts by the scientific community since its emergence in 2019, no effective therapeutics have been discovered yet. While some repurposed drugs have been used to control the global outbreak and save lives, none have proven universally effective, particularly for severely infected patients. Although the spread of the disease is generally under control, anti-SARS-CoV-2 agents are still needed to combat current and future infections. This study reviews some of the most promising repurposed drugs containing indolyl heterocycle, which is an essential scaffold of many alkaloids with diverse bio-properties in various biological fields. The study also discusses natural and synthetic indole-containing compounds with anti-SARS-CoV-2 properties and computer-aided drug design (in silico studies) for optimizing anti-SARS-CoV-2 hits/leads.

Understanding the Clinical Use of Levosimendan and Perspectives on its Future in Oncology

Drug repurposing, also known as repositioning or reprofiling, has emerged as a promising strategy to accelerate drug discovery and development. This approach involves identifying new medical indications for existing approved drugs, harnessing the extensive knowledge of their bioavailability, pharmacokinetics, safety and efficacy. Levosimendan, a calcium sensitizer initially approved for heart failure, has been repurposed for oncology due to its multifaceted pharmacodynamics, including phosphodiesterase 3 inhibition, nitric oxide production and reduction of reactive oxygen species. Studies have demonstrated that levosimendan inhibits cancer cell migration and sensitizes hypoxic cells to radiation. Moreover, it exerts organ-protective effects by activating mitochondrial potassium channels. Combining levosimendan with traditional anticancer agents such as 5-fluorouracil (5-FU) has shown a synergistic effect in bladder cancer cells, highlighting its potential as a novel therapeutic approach. This drug repurposing strategy offers a cost-effective and time-efficient solution for developing new treatments, ultimately contributing to the advancement of cancer therapeutics and improved outcomes for patients. Further investigations and clinical trials are warranted to validate the effectiveness of levosimendan in oncology and explore its potential benefits in a clinical setting.

Navigating drug repurposing for Chagas disease: advances, challenges, and opportunities

Chagas disease is a vector-borne illness caused by the protozoan parasite Trypanosoma cruzi (T. cruzi). It poses a significant public health burden, particularly in the poorest regions of Latin America. Currently, there is no available vaccine, and chemotherapy has been the traditional treatment for Chagas disease. However, the treatment options are limited to just two outdated medicines, nifurtimox and benznidazole, which have serious side effects and low efficacy, especially during the chronic phase of the disease. Collectively, this has led the World Health Organization to classify it as a neglected disease. To address this problem, new drug regimens are urgently needed. Drug repurposing, which involves the use of existing drugs already approved for the treatment of other diseases, represents an increasingly important option. This approach offers potential cost reduction in new drug discovery processes and can address pharmaceutical bottlenecks in the development of drugs for Chagas disease. In this review, we discuss the state-of-the-art of drug repurposing approaches, including combination therapy with existing drugs, to overcome the formidable challenges associated with treating Chagas disease. Organized by original therapeutic area, we describe significant recent advances, as well as the challenges in this field. In particular, we identify candidates that exhibit potential for heightened efficacy and reduced toxicity profiles with the ultimate objective of accelerating the development of new, safe, and effective treatments for Chagas disease.

Sertindole, an Antipsychotic Drug, Curbs the STAT3/BCL-xL Axis to Elicit Human Bladder Cancer Cell Apoptosis In Vitro

Bladder cancer is the leading urinary tract malignancy. Epidemiological evidence has linked lower cancer incidence in schizophrenia patients to long-term medication, highlighting the anticancer potential of antipsychotics. Sertindole is an atypical antipsychotic agent with reported anticancer action on breast and gastric cancers. Yet, sertindole's effect on bladder cancer remains unaddressed. We herein present the first evidence of sertindole's antiproliferative effect and mechanisms of action on human bladder cancer cells. Sertindole was cytotoxic against bladder cancer cells while less cytotoxic to normal urothelial cells. Apoptosis was a primary cause of sertindole's cytotoxicity, as the pan-caspase inhibitor z-VAD-fmk rescued cells from sertindole-induced killing. Mechanistically, sertindole inhibited the activation of signal transducer and activator of transcription 3 (STAT3), an oncogenic driver of bladder cancer, as sertindole lowered the levels of tyrosine 705-phosphorylated STAT3 along with that of STAT3's target gene BCL-xL. Notably, ectopic expression of the dominant-active STAT3 mutant impaired sertindole-induced apoptosis in addition to restoring BCL-xL expression. Moreover, bladder cancer cells overexpressing BCL-xL were refractory to sertindole's proapoptotic action, arguing that sertindole represses STAT3 to downregulate BCL-xL, culminating in the induction of apoptosis. Overall, the current study indicated sertindole exerts bladder cancer cytotoxicity by provoking apoptosis through targeted inhibition of the antiapoptotic STAT3/BCL-xL signaling axis. These findings implicate the potential to repurpose sertindole as a therapeutic strategy for bladder cancer.

Molecular Mechanisms of the Antitumor Effects of Mesalazine and Its Preventive Potential in Colorectal Cancer

Chemoprevention is one of the ways to fight colorectal cancer, which is a huge challenge in oncology. Numerous pieces of evidence indicate that chronic inflammation in the course of Crohn's disease or ulcerative colitis (UC) is a significant cancer risk factor. Epidemiologic studies suggest that long-term use of non-steroidal anti-inflammatory drugs (NSAIDs), including mesalazine, has beneficial effects on colitis-associated colorectal cancer. Mesalazine is a first-line therapy for UC and is also widely used for maintaining remission in UC. Data showed that mesalazine has antiproliferative properties associated with cyclooxygenase (COX) inhibition but can also act through COX-independent pathways. This review summarizes knowledge about mesalazine's molecular mechanisms of action and chemopreventive effect by which it could interfere with colorectal cancer cell proliferation and survival.

Drug Repurposing in Oncology: A Systematic Review of Randomized Controlled Clinical Trials

Quality pharmacological treatment can improve survival in many types of cancer. Drug repurposing offers advantages in comparison with traditional drug development procedures, reducing time and risk. This systematic review identified the most recent randomized controlled clinical trials that focus on drug repurposing in oncology. We found that only a few clinical trials were placebo-controlled or standard-of-care-alone-controlled. Metformin has been studied for potential use in various types of cancer, including prostate, lung, and pancreatic cancer. Other studies assessed the possible use of the antiparasitic agent mebendazole in colorectal cancer and of propranolol in multiple myeloma or, when combined with etodolac, in breast cancer. We were able to identify trials that study the potential use of known antineoplastics in other non-oncological conditions, such as imatinib for severe coronavirus disease in 2019 or a study protocol aiming to assess the possible repurposing of leuprolide for Alzheimer's disease. Major limitations of these clinical trials were the small sample size, the high clinical heterogeneity of the participants regarding the stage of the neoplastic disease, and the lack of accounting for multimorbidity and other baseline clinical characteristics. Drug repurposing possibilities in oncology must be carefully examined with well-designed trials, considering factors that could influence prognosis.

Antibacterial activity of paroxetine against Staphylococcus aureus and possible mechanisms of action

Aim: To evaluate the antibacterial activity of paroxetine alone and associated with oxacillin against isolates of methicillin-sensitive and -resistant Staphylococcus aureus. Materials & methods: The broth microdilution and checkerboard techniques were used, with investigation of possible mechanisms of action through flow cytometry, fluorescence microscopy and molecular docking, in addition to scanning electron microscopy for morphological analysis. Results: Paroxetine showed a MIC of 64 μg/ml and bactericidal activity, mostly additive interactions in combination with oxacillin, evidence of action on genetic material and membrane, morphological changes in microbial cells and influence on virulence factors. Conclusion: Paroxetine has antibacterial potential from the perspective of drug repositioning.

Quinolines and isoquinolines as HIV-1 inhibitors: Chemical structures, action targets, and biological activities

Human immunodeficiency virus type 1 (HIV-1), a lentivirus that causes acquired immunodeficiency syndrome (AIDS), poses a serious threat to global public health. Since the advent of the first drug zidovudine, a number of anti-HIV agents acting on different targets have been approved to combat HIV/AIDS. Among the abundant heterocyclic families, quinoline and isoquinoline moieties are recognized as promising scaffolds for HIV inhibition. This review intends to highlight the advances in diverse chemical structures and abundant biological activity of quinolines and isoquinolines as anti-HIV agents acting on different targets, which aims to provide useful references and inspirations to design and develop novel HIV inhibitors for medicinal chemists.