Bipolar Disord. 2023 Mar 8. doi: 10.1111/bdi.13319. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of this study was to repurpose a drug for the treatment of bipolar depression.

METHODS: A gene expression signature representing the overall transcriptomic effects of a cocktail of drugs widely prescribed to treat bipolar disorder was generated using human neuronal-like (NT2-N) cells. A compound library of 960 approved, off-patent drugs were then screened to identify those drugs that affect transcription most similarly to the effects of the bipolar depression drug cocktail. For mechanistic studies, peripheral blood mononuclear cells were obtained from a healthy subject and reprogrammed into induced pluripotent stem cells, which were then differentiated into co-cultured neurons and astrocytes. Efficacy studies were conducted in two animal models of depressive-like behaviours (Flinders Sensitive Line rats and social isolation with chronic restraint stress rats).

RESULTS: The screen identified trimetazidine as a potential drug for repurposing. Trimetazidine alters metabolic processes to increase ATP production, which is thought to be deficient in bipolar depression. We showed that trimetazidine increased mitochondrial respiration in cultured human neuronal-like cells. Transcriptomic analysis in induced pluripotent stem cell-derived neuron/astrocyte co-cultures suggested additional mechanisms of action via the focal adhesion and MAPK signalling pathways. In two different rodent models of depressive-like behaviours, trimetazidine exhibited antidepressant-like activity with reduced anhedonia and reduced immobility in the forced swim test.

CONCLUSION: Collectively our data support the repurposing of trimetazidine for the treatment of bipolar depression.

PMID:36890661 | DOI:10.1111/bdi.13319

Clin Drug Investig. 2023 Mar 8. doi: 10.1007/s40261-023-01251-0. Online ahead of print.

ABSTRACT

Therapeutic repurposing emerged as an alternative to the traditional drug discovery and development model (DDD) of new molecular entities (NMEs). It was anticipated that by being faster, safer, and cheaper, the development would result in lower-cost drugs. As defined in this work, a repurposed cancer drug is one approved by a health regulatory authority against a non-cancer indication that then gains new approval for cancer. With this definition, only three drugs are repurposed for cancer: Bacillus Calmette-Guerin (BCG) vaccine (superficial bladder cancer, thalidomide [multiple myeloma], and propranolol [infantile hemangioma]). Each of these has a different history regarding price and affordability, and it is not yet possible to generalize the impact of drug repurposing on the final price to the patient. However, the development, including the price, does not differ significantly from an NME. For the end consumer, the product's price is unrelated to whether it followed the classical development or repurposing. Economic constraints for clinical development, and drug prescription biases for repurposing drugs, are barriers yet to be overcome. The affordability of cancer drugs is a complex issue that varies from country to country. Many alternatives for having affordable drugs have been put forward, however these measures have thus far failed and are, at best, palliative. There are no immediate solutions to the problem of access to cancer drugs. It is necessary to critically analyze the impact of the current drug development model and be creative in implementing new models that genuinely benefit society.

PMID:36884210 | DOI:10.1007/s40261-023-01251-0

J Cancer Res Clin Oncol. 2023 Mar 8. doi: 10.1007/s00432-023-04674-6. Online ahead of print.

ABSTRACT

PURPOSE: Exosomes are membrane-derived nano-vesicles upregulated in pathological conditions like cancer. Therefore, inhibiting their release is a potential strategy for the development of more efficient combination therapies. Neutral sphingomyelinase 2 (nSMase2) is a key component in exosome release; however, a clinically safe yet efficient nSMase2 inhibitor remains to be used discovered. Accordingly, we made an effort to identify potential nSMase2 inhibitor(s) among the approved drugs.

METHODS: Virtual screening was performed and aprepitant was selected for further investigation. To evaluate the reliability of the complex, molecular dynamics were performed. Finally, using the CCK-8 assay in HCT116 cells, the highest non-toxic concentrations of aprepitant were identified and the nSMase2 activity assay was performed to measure the inhibitory activity of aprepitant, in vitro.

RESULTS: To validate the screening results, molecular docking was performed, and the retrieved scores were in line with the screening results. The root-mean-square deviation (RMSD) plot of aprepitant-nSMase2 showed proper convergence. Following treatment with different concentrations of aprepitant in both cell-free and cell-dependent assays, nSMase2 activity was remarkably decreased.

CONCLUSION: Aprepitant, at a concentration as low as 15 µM, was able to inhibit nSmase2 activity in HCT116 cells without any significant effects on their viability. Aprepitant is therefore suggested to be a potentially safe exosome release inhibitor.

PMID:36884117 | DOI:10.1007/s00432-023-04674-6

Curr Drug Saf. 2023;18(2):122-124. doi: 10.2174/1574886317666220428133813.

ABSTRACT

The Coronavirus disease (COVID-19) outbreak is marked by infodemic amid conspiracy theories, false claims, rumors, and misleading narratives, which have had a significant impact on the global campaign against COVID-19. The drug repurposing provides a hope to curb the growing encumbrance of the disease but at the same time, it poses various challenges such as selfmedication using repurposed drugs and its associated harms. During the continuing pandemic, this perspective piece explores the potential hazards of self-medication and its attributing factors along with possible countermeasures.

PMID:36883267 | DOI:10.2174/1574886317666220428133813

ACS Pharmacol Transl Sci. 2023 Mar 7;6(4):578-586. doi: 10.1021/acsptsci.2c00225. eCollection 2023 Apr 14.

ABSTRACT

SARS-CoV-2 is the agent responsible for acute respiratory disease COVID-19 and the global pandemic initiated in early 2020. While the record-breaking development of vaccines has assisted the control of COVID-19, there is still a pressing global demand for antiviral drugs to halt the destructive impact of this disease. Repurposing clinically approved drugs provides an opportunity to expediate SARS-CoV-2 treatments into the clinic. In an effort to facilitate drug repurposing, an FDA-approved drug library containing 2400 compounds was screened against the SARS-CoV-2 non-structural protein 7 (nsp7) using a native mass spectrometry-based assay. Nsp7 is one of the components of the SARS-CoV-2 replication/transcription complex essential for optimal viral replication, perhaps serving to off-load RNA from nsp8. From this library, gallic acid was identified as a compound that bound tightly to nsp7, with an estimated K d of 15 μM. NMR chemical shift perturbation experiments were used to map the ligand-binding surface of gallic acid on nsp7, indicating that the compound bound to a surface pocket centered on one of the protein's four α-helices (α2). The identification of the gallic acid-binding site on nsp7 may allow development of a SARS-CoV-2 therapeutic via artificial-intelligence-based virtual docking and other strategies.

PMID:37082753 | PMC:PMC10111621 | DOI:10.1021/acsptsci.2c00225

Interact J Med Res. 2023 Mar 5. doi: 10.2196/39455. Online ahead of print.

ABSTRACT

BACKGROUND: Antidepressants are a type of medication used to treat clinical depression or prevent it recurring. Antidepressants exert an anticholinergic effect in varying degrees and various classes of antidepressants also can produce a different effect on immune function. While early usage of antidepressants has notional role on COVID-19 outcomes, the relationship between the risk of COVID-19 severity and the use of all kinds of antidepressants is not properly investigated before due to the exceeding cost involved with clinical trials. Large-scale observational data such as electronic health records and recent advancement of statistical analysis provide ample opportunity to virtualize clinical trial to discover detrimental effects of early usage of these drugs.

OBJECTIVE: By mining a large-scale electronic health record data set of COVID-19 positive patients, we aim to identify common drugs that are associated with COVID-19 outcome. However, whereas the statisticians have made great progress toward using such rich association estimation methods for risk estimation, precise effects of the medicines as treatments require causal models. Thus, our central aim of this paper lies on investigating electronic health record analytic for causal effect estimation and utilize that in discovering causal effects of early antidepressants use on COVID-19 outcomes. As a secondary aim, we develop methods for validating our causal effect estimation pipeline.

METHODS: We focus on antidepressants, a commonly used category of drugs that have been linked to unexpected effects on diverse inflammatory and cardiovascular outcomes and infer early use of such drug use effects on COVID-19 outcomes. However, whereas the machine learning and statistics community have made great progress toward using rich inference models, precise effects of the medicines as treatments require causal models, for which there is significantly less theoretical and practical guidance available. We used National COVID Cohort Collaborative (N3C), a database aggregating health history for over 12+ million people in the USA, including 5+ million with a positive COVID-19 test. We selected 241,952 COVID-19 positive patients with at least one year of medical history and age>13 that included 18,584-dimensional covariate vector for each person and 16 different antidepressants usage histories. We used propensity score weighting based on logistic regression method to estimate causal effect on whole data. Then we used Node2Vec embedding method to encode SNOMED medical code and apply random forest regression to estimate causal effect. We use both methods to estimate causal effects of antidepressants on COVID-19 outcome. We also selected few negatively effective conditions on COVID-19 outcomes and estimated their effects using our proposed methods to validate their efficacy.

RESULTS: Average Treatment Effect (ATE) of using any one of the antidepressants is -0.076 with 95% CI from -0.082 to - 0.069 with propensity score weighting method. The result is statistically significant at p<0.0001. In case of the method using SNOMED medical embedding, the ATE of using any one of the antidepressants is -0.423 with 95% CI from -0.382 to -0.463. This result is also statistically significant at p<0.0001.

CONCLUSIONS: In this study, we apply multiple causal inference methods incorporating with a novel application of health embeddings to investigate the effects of antidepressants on COVID-19 outcome. Additionally, we propose a novel non-affecting drug effect analysis-based evaluation technique to justify the efficacy of proposed method. This study offers causal inference methods on large-scale EHR data to discover common antidepressants' effects on COVID-19 hospitalization, or a worse outcome. The study finds that common antidepressants may increase risk of COVID-19 complications and uncovers a pattern where certain antidepressants are associated with lower risk of hospitalization. While discovering detrimental effects of these drugs on outcome could guide preventive care, identification of beneficial effects would allow us to propose drug repurposing for COVID-19 treatment.

PMID:36881541 | DOI:10.2196/39455

Med Health Care Philos. 2023 Mar 7. doi: 10.1007/s11019-023-10140-4. Online ahead of print.

ABSTRACT

Drug repurposing is a strategy of identifying new potential uses for already existing drugs. Many researchers adopted this method to identify treatment or prevention during the COVID-19 pandemic. However, despite the considerable number of repurposed drugs that were evaluated, only some of them were labeled for new indications. In this article, we present the case of amantadine, a drug commonly used in neurology that attracted new attention during the COVID-19 outbreak. This example illustrates some of the ethical challenges associated with the launch of clinical trials to evaluate already approved drugs. In our discussion, we follow the ethics framework for prioritization of COVID-19 clinical trials proposed by Michelle N Meyer and colleagues (2021). We focus on four criteria: social value, scientific validity, feasibility, and consolidation/collaboration. We claim that launching amantadine trials was ethically justified. Although the scientific value was anticipated to be low, unusually, the social value was expected to be high. This was because of significant social interest in the drug. In our view, this strongly supports the need for evidence to justify why the drug should not be prescribed or privately accessed by interested parties. Otherwise, a lack of evidence-based argument could enhance its uncontrolled use. With this paper, we join the discussion on the lessons learned from the pandemic. Our findings will help to improve future efforts to decide on the launch of clinical trials on approved drugs when dealing with the widespread off-label use of the drug.

PMID:36881334 | DOI:10.1007/s11019-023-10140-4

Comput Struct Biotechnol J. 2023 Feb 8;21:1533-1542. doi: 10.1016/j.csbj.2023.02.004. eCollection 2023.

ABSTRACT

Discovering effective therapies is difficult for neurological and developmental disorders in that disease progression is often associated with a complex and interactive mechanism. Over the past few decades, few drugs have been identified for treating Alzheimer's disease (AD), especially for impacting the causes of cell death in AD. Although drug repurposing is gaining more success in developing therapeutic efficacy for complex diseases such as common cancer, the complications behind AD require further study. Here, we developed a novel prediction framework based on deep learning to identify potential repurposed drug therapies for AD, and more importantly, our framework is broadly applicable and may generalize to identifying potential drug combinations in other diseases. Our prediction framework is as follows: we first built a drug-target pair (DTP) network based on multiple drug features and target features, as well as the associations between DTP nodes where drug-target pairs are the DTP nodes and the associations between DTP nodes are represented as the edges in the AD disease network; furthermore, we incorporated the drug-target feature from the DTP network and the relationship information between drug-drug, target-target, drug-target within and outside of drug-target pairs, representing each drug-combination as a quartet to generate corresponding integrated features; finally, we developed an AI-based Drug discovery Network (AI-DrugNet), which exhibits robust predictive performance. The implementation of our network model help identify potential repurposed and combination drug options that may serve to treat AD and other diseases.

PMID:36879885 | PMC:PMC9984442 | DOI:10.1016/j.csbj.2023.02.004

Health Aff (Millwood). 2023 Mar;42(3):424-432. doi: 10.1377/hlthaff.2022.01083.

ABSTRACT

The COVID-19 pandemic created a large, sudden unmet public health need for rapid access to safe and effective treatments. Against this backdrop, policy makers and researchers have looked to drug repurposing-using a drug previously approved for one indication to target a new indication-as a means to accelerate the identification and development of COVID-19 treatments. Using detailed data on US clinical trials initiated during the pandemic, we examined the trajectory and sources of drug repurposing initiatives for COVID-19. We found a rapid increase in repurposing efforts at the start of the pandemic, followed by a transition to greater de novo drug development. The drugs tested for repurposing treat a wide range of indications but were typically initially approved for other infectious diseases. Finally, we documented substantial variation by trial sponsor (academic, industry, or government) and generic status: Industry sponsorship for repurposing occurred much less frequently for drugs with generic competitors already on the market. Our findings inform drug repurposing policy for both future emerging diseases and drug development in general.

PMID:36877896 | DOI:10.1377/hlthaff.2022.01083

Cancer Res Commun. 2022 May 4;2(5):293-306. doi: 10.1158/2767-9764.CRC-22-0037. eCollection 2022 May.

ABSTRACT

Drug repurposing is an attractive option for oncology drug development. Itraconazole is an antifungal ergosterol synthesis inhibitor that has pleiotropic actions including cholesterol antagonism, inhibition of Hedgehog and mTOR pathways. We tested a panel of 28 epithelial ovarian cancer (EOC) cell lines with itraconazole to define its spectrum of activity. To identify synthetic lethality in combination with itraconazole, a whole-genome drop-out genome-scale clustered regularly interspaced short palindromic repeats sensitivity screen in two cell lines (TOV1946 and OVCAR5) was performed. On this basis, we conducted a phase I dose-escalation study assessing the combination of itraconazole and hydroxychloroquine in patients with platinum refractory EOC (NCT03081702). We identified a wide spectrum of sensitivity to itraconazole across the EOC cell lines. Pathway analysis showed significant involvement of lysosomal compartments, the trans-golgi network and late endosomes/lysosomes; similar pathways are phenocopied by the autophagy inhibitor, chloroquine. We then demonstrated that the combination of itraconazole and chloroquine displayed Bliss defined synergy in EOC cancer cell lines. Furthermore, there was an association of cytotoxic synergy with the ability to induce functional lysosome dysfunction, by chloroquine. Within the clinical trial, 11 patients received at least one cycle of itraconazole and hydroxychloroquine. Treatment was safe and feasible with the recommended phase II dose of 300 and 600 mg twice daily, respectively. No objective responses were detected. Pharmacodynamic measurements on serial biopsies demonstrated limited pharmacodynamic impact. In vitro, itraconazole and chloroquine have synergistic activity and exert a potent antitumor effect by affecting lysosomal function. The drug combination had no clinical antitumor activity in dose escalation.

SIGNIFICANCE: The combination of the antifungal drug itraconazole with antimalarial drug hydroxychloroquine leads to a cytotoxic lysosomal dysfunction, supporting the rational for further research on lysosomal targeting in ovarian cancer.

PMID:36875717 | PMC:PMC9981200 | DOI:10.1158/2767-9764.CRC-22-0037

Hemasphere. 2023 Feb 28;7(3):e848. doi: 10.1097/HS9.0000000000000848. eCollection 2023 Mar.

ABSTRACT

Drug repurposing is a valuable strategy for rare diseases. Sickle cell disease (SCD) is a rare hereditary hemolytic anemia accompanied by acute and chronic painful episodes, most often in the context of vaso-occlusive crisis (VOC). Although progress in the knowledge of pathophysiology of SCD have allowed the development of new therapeutic options, a large fraction of patients still exhibits unmet therapeutic needs, with persistence of VOCs and chronic disease progression. Here, we show that imatinib, an oral tyrosine kinase inhibitor developed for the treatment of chronic myelogenous leukemia, acts as multimodal therapy targeting signal transduction pathways involved in the pathogenesis of both anemia and inflammatory vasculopathy of humanized murine model for SCD. In addition, imatinib inhibits the platelet-derived growth factor-B-dependent pathway, interfering with the profibrotic response to hypoxia/reperfusion injury, used to mimic acute VOCs. Our data indicate that imatinib might be considered as possible new therapeutic tool for chronic treatment of SCD.

PMID:36874380 | PMC:PMC9977487 | DOI:10.1097/HS9.0000000000000848

Front Pharmacol. 2023 Feb 17;14:1128387. doi: 10.3389/fphar.2023.1128387. eCollection 2023.

ABSTRACT

Background: Growing evidence supports a bidirectional association between diabetes and depression; promising but limited and conflicting data from human studies support the intriguing possibility that antidiabetic agents may be used to relieve effectively depressive symptoms in diabetic patients. We investigated the potential antidepressant effects of antidiabetic drugs in a high-scale population data from the two most important pharmacovigilance databases, i.e., the FDA Adverse Event Reporting System (FAERS) and the VigiBase. Material and methods: From the two primary cohorts of patients treated with antidepressants retrieved from FDA Adverse Event Reporting System and VigiBase we identified cases (depressed patients experiencing therapy failure) and non-cases (depressed patients experiencing any other adverse event). We then calculated the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Empirical Bayes Geometric Mean (EBGM), and Empirical Bayes Regression-Adjusted Mean (ERAM) for cases versus non-cases in relation with the concurrent exposure to at least one of the following antidiabetic agent: A10BA Biguanides; A10BB Sulfonylureas; A10BG Thiazolidinediones; A10BH DPP4-inhibitors; A10BJ GLP-1 analogues; A10BK SGLT2 inhibitors (i.e., those agents for which preliminary evidence from literature supports our pharmacological hypothesis). Results: For GLP-1 analogues, all the disproportionality scores showed values <1, i.e., statistically significant, in both analyses [from the FAERS: ROR confidence interval of 0.546 (0.450-0.662); PRR (p-value) of 0.596 (0.000); EBGM (CI) of 0.488 (0.407-0.582); ERAM (CI) of 0.480 (0.398-0.569) and VigiBase: ROR (CI) of 0.717 (0.559-0.921); PRR (p-value) of 0.745 (0.033); EBGM (CI) of 0.586 (0.464-0.733); ERAM of (CI): 0.515 (0.403-0.639)]. Alongside GLP-1 analogues, DPP-4 Inhibitors and Sulfonylureas showed the greatest potential protective effect. With regard to specific antidiabetic agents, liraglutide and gliclazide were associated with a statistically significant decrease in all disproportionality scores, in both analyses. Conclusion: The findings of this study provide encouraging results, albeit preliminary, supporting the need for further clinical research for investigating repurposing of antidiabetic drugs for neuropsychiatric disorders.

PMID:36873988 | PMC:PMC9981969 | DOI:10.3389/fphar.2023.1128387

Mil Med Res. 2023 Mar 6;10(1):10. doi: 10.1186/s40779-023-00446-y.

ABSTRACT

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time- and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy (cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence (AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of medium-resolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.

PMID:36872349 | DOI:10.1186/s40779-023-00446-y

Zhongguo Zhong Yao Za Zhi. 2023 Feb;48(3):841-846. doi: 10.19540/j.cnki.cjcmm.20220928.502.

ABSTRACT

The aging society has led to a substantial increase in the number of clinical comorbidities. To meet the needs of comorbidity treatment, polypharmacy is widely used in clinical practice. However, polypharmacy has drawbacks such as treatment conflict. Same treatment of different diseases refers to treating different diseases with same treatment. Therefore, the principle of same treatment of different diseases can alleviate the problems caused by polypharmacy. Under the research background of precision medicine, it becomes possible to explore the mechanism of same treatment of different diseases and achieve its clinical application. However, drugs successfully developed in the past have revealed shortcomings in clinical use. To better interpret the mechanism of precision medicine for same treatment of different diseases, under the multi-dimensional attributes including dynamic space and time, omics was performed, and a new strategy of tensor decomposition was proposed. With the characteristics of complete data, tensor decomposition is advantageous in data mining and can fully grasp the connotation of precision treatment of different diseases with same treatment under dynamic spatiotemporal changes. This method is used for drug repositioning in some biocomputations. By taking advantage of the dimensionality reduction of tensor decomposition and integrating the dual influences of time and space, this study achieved accurate target prediction of same treatment of different diseases at each stage, and discovered the mechanism of precision medicine of same treatment for different diseases, providing scientific support for precision prescription and treatment of different diseases with same treatment in clinical practice. This study thus conducted preliminary exploration of the pharmacological mechanism of precision Chinese medicine treatment.

PMID:36872249 | DOI:10.19540/j.cnki.cjcmm.20220928.502

J Infect Chemother. 2023 Mar 3:S1341-321X(23)00053-3. doi: 10.1016/j.jiac.2023.02.017. Online ahead of print.

ABSTRACT

Severe fever with thrombocytopenia syndrome is a hemorrhagic fever caused by a tick-borne infection. The causative agent, Dabie bandavirus, is also called the severe fever with thrombocytopenia syndrome virus (SFTSV). Ogawa et al. (2022) reported that levodopa, an antiparkinsonian drug with an o-dihydroxybenzene backbone, which is important for anti-SFTSV activity, inhibited SFTSV infection. Levodopa is metabolized by dopa decarboxylase (DDC) and catechol-O-methyltransferase (COMT) in vivo. We evaluated the anti-SFTSV efficacy of two DDC inhibitors, benserazide hydrochloride and carbidopa, and two COMT inhibitors, entacapone and nitecapone, which also have an o-dihydroxybenzene backbone. Only DDC inhibitors inhibited SFTSV infection with pretreatment of the virus (half-maximal inhibitory concentration [IC50]: 9.0-23.6 μM), whereas all the drugs inhibited SFTSV infection when infected cells were treated (IC50: 21.3-94.2 μM). Levodopa combined with carbidopa and/or entacapone inhibited SFTSV infection in both conditions: pretreatment of the virus (IC50: 2.9-5.8 μM) and treatment of infected cells (IC50: 10.7-15.4 μM). The IC50 of levodopa in the above-mentioned study for pretreatment of the virus and treatment of infected cells were 4.5 and 21.4 μM, respectively. This suggests that a synergistic effect was observed, especially for treatment of infected cells, although the effect is unclear for pretreatment of the virus. This study demonstrates the anti-SFTSV efficacy of levodopa-metabolizing enzyme inhibitors in vitro. These drugs may increase the time for which the levodopa concentration is maintained in vivo. The combination of levodopa and levodopa-metabolizing enzyme inhibitors might be a candidate for drug repurposing.

PMID:36871824 | DOI:10.1016/j.jiac.2023.02.017

Sci Rep. 2023 Mar 4;13(1):3643. doi: 10.1038/s41598-023-30095-z.

ABSTRACT

The search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns "ensemble embeddings" of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.

PMID:36871056 | DOI:10.1038/s41598-023-30095-z

Br J Cancer. 2023 Mar 4. doi: 10.1038/s41416-023-02210-4. Online ahead of print.

ABSTRACT

BACKGROUND: Autophagy plays an important role in tumour cell growth and survival and also promotes resistance to chemotherapy. Hence, autophagy has been targeted for cancer therapy. We previously reported that macrolide antibiotics including azithromycin (AZM) inhibit autophagy in various types of cancer cells in vitro. However, the underlying molecular mechanism for autophagy inhibition remains unclear. Here, we aimed to identify the molecular target of AZM for inhibiting autophagy.

METHODS: We identified the AZM-binding proteins using AZM-conjugated magnetic nanobeads for high-throughput affinity purification. Autophagy inhibitory mechanism of AZM was analysed by confocal microscopic and transmission electron microscopic observation. The anti-tumour effect with autophagy inhibition by oral AZM administration was assessed in the xenografted mice model.

RESULTS: We elucidated that keratin-18 (KRT18) and α/β-tubulin specifically bind to AZM. Treatment of the cells with AZM disrupts intracellular KRT18 dynamics, and KRT18 knockdown resulted in autophagy inhibition. Additionally, AZM treatment suppresses intracellular lysosomal trafficking along the microtubules for blocking autophagic flux. Oral AZM administration suppressed tumour growth while inhibiting autophagy in tumour tissue.

CONCLUSIONS: As drug-repurposing, our results indicate that AZM is a potent autophagy inhibitor for cancer treatment, which acts by directly interacting with cytoskeletal proteins and perturbing their dynamics.

PMID:36871041 | DOI:10.1038/s41416-023-02210-4

Hereditas. 2023 Mar 4;160(1):9. doi: 10.1186/s41065-023-00270-3.

ABSTRACT

BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disorder which could lead to inflammation and fibrosis in various organs. Pulmonary fibrosis is a severe complication in patients with SLE. Nonetheless, SLE-derived pulmonary fibrosis has unknown pathogenesis. Of pulmonary fibrosis, Idiopathic pulmonary fibrosis (IPF) is a typicality and deadly form. Aiming to investigate the gene signatures and possible immune mechanisms in SLE-derived pulmonary fibrosis, we explored common characters between SLE and IPF from Gene Expression Omnibus (GEO) database.

RESULTS: We employed the weighted gene co-expression network analysis (WGCNA) to identify the shared genes. Two modules were significantly identified in both SLE and IPF, respectively. The overlapped 40 genes were selected out for further analysis. The GO enrichment analysis of shared genes between SLE and IPF was performed with ClueGO and indicated that p38MAPK cascade, a key inflammation response pathway, may be a common feature in both SLE and IPF. The validation datasets also illustrated this point. The enrichment analysis of common miRNAs was obtained from the Human microRNA Disease Database (HMDD) and the enrichment analysis with the DIANA tools also indicated that MAPK pathways' role in the pathogenesis of SLE and IPF. The target genes of these common miRNAs were identified by the TargetScan7.2 and a common miRNAs-mRNAs network was constructed with the overlapped genes in target and shared genes to show the regulated target of SLE-derived pulmonary fibrosis. The result of CIBERSORT showed decreased regulatory T cells (Tregs), naïve CD4+ T cells and rest mast cells but increased activated NK cells and activated mast cells in both SLE and IPF. The target genes of cyclophosphamide were also obtained from the Drug Repurposing Hub and had an interaction with the common gene PTGS2 predicted with protein-protein interaction (PPI) and molecular docking, indicating its potential treatment effect.

CONCLUSIONS: This study originally uncovered the MAPK pathway, and the infiltration of some immune-cell subsets might be pivotal factors for pulmonary fibrosis complication in SLE, which could be used as potentially therapeutic targets. The cyclophosphamide may treat SLE-derived pulmonary fibrosis through interaction with PTGS2, which could be activated by p38MAPK.

PMID:36871016 | DOI:10.1186/s41065-023-00270-3

Eur J Pharm Sci. 2023 Mar 2:106418. doi: 10.1016/j.ejps.2023.106418. Online ahead of print.

ABSTRACT

INTRODUCTION: In the randomized double-blind placebo-controlled CounterCOVID study, oral imatinib treatment conferred a positive clinical outcome and a signal for reduced mortality in COVID-19 patients. High concentrations of alpha-1 acid glycoprotein (AAG) were observed in these patients and were associated with increased total imatinib concentrations.

AIMS: This post-hoc study aimed to compare the difference in exposure following oral imatinib administration in COVID-19 patients to cancer patients and assess assocations between pharmacokinetic (PK) parameters and pharmacodynamic (PD) outcomes of imatinib in COVID-19 patients. We hypothesize that a relatively higher drug exposure of imatinib in severe COVID-19 patients leads to improved pharmacodynamic outcome parameters.

METHODS: 648 total concentration plasma samples obtained from 168 COVID-19 patients were compared to 475 samples of 105 cancer patients, using an AAG-binding model. Total trough concentration at steady state (Ctrough) and average AUC (AUCave) were associated with ratio between partial oxygen pressure and fraction of inspired oxygen (P/F), WHO ordinal scale (WHO-score) and liberation of oxygen supplementation (O2lib). Linear regression, linear mixed effects models and time-to-event analysis were adjusted for possible confounders.

RESULTS: AUCave and Ctrough were respectively 2.21-fold (95%CI 2.07-2.37) and 1.53-fold (95%CI 1.44-1.63) lower for cancer compared to COVID-19 patients. Ctrough, not AUCave, associated significantly with P/F (β=-19,64; p-value=0.014) and O2lib (HR 0.78; p-value= 0.032), after adjusting for sex, age, neutrophil-lymphocyte ratio, dexamethasone concomitant treatment, AAG and baseline P/F-and WHO-score. Ctrough, but not AUCave associated significantly with WHO-score. These results suggest an inverse relationship between PK-parameters, Ctrough and AUCave, and PD outcomes.

CONCLUSION: COVID-19 patients exhibit higher total imatinib exposure compared to cancer patients, attributed to differences in plasma protein concentrations. Higher imatinib exposure in COVID-19 patients did not associate with improved clinical outcomes. Total Ctrough and AUCave inversely associated with some PD-outcomes, which may be biased by disease course, variability in metabolic rate and protein binding. Therefore, additional PKPD analyses into unbound imatinib and its main metabolite may better explain exposure-response.

PMID:36870577 | DOI:10.1016/j.ejps.2023.106418

Kidney Int. 2023 Mar 2:S0085-2538(23)00133-3. doi: 10.1016/j.kint.2023.02.010. Online ahead of print.

ABSTRACT

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive renal cyst formation that leads to kidney failure. Tolvaptan, a vasopressin 2 receptor (V2R) antagonist, is the only drug approved to treat ADPKD patients with rapid disease progression. The use of tolvaptan is limited by reduced tolerability from aquaretic effects and potential hepatotoxicity. Thus, the search for more effective drugs to slow down the progression of ADPKD is urgent and challenging. Drug repurposing is a strategy for identifying new clinical indications for approved or investigational medications. Drug repurposing is increasingly becoming an attractive proposition due to its cost- and time-efficiencies and known pharmacokinetic and safety profiles. In this review, we focus on the repurposing approaches to identify suitable drug candidates to treat ADPKD and prioritization and implementation of candidates with high probability of success. Identification of drug candidates through understanding of disease pathogenesis and signaling pathways is highlighted.

PMID:36870435 | DOI:10.1016/j.kint.2023.02.010