Top Curr Chem (Cham). 2021 Oct 8;379(6):40. doi: 10.1007/s41061-021-00353-7.

ABSTRACT

The highly infectious disease COVID-19 is induced by SARS-coronavirus 2 (SARS-CoV-2), which has spread rapidly around the globe and was announced as a pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 binds to the host cell's angiotensin converting enzyme 2 (ACE2) receptor through the viral surface spike glycoprotein (S-protein). ACE2 is expressed in the oral mucosa and can therefore constitute an essential route for entry of SARS-CoV-2 into hosts through the tongue and lung epithelial cells. At present, no effective treatments for SARS-CoV-2 are yet in place. Blocking entry of the virus by inhibiting ACE2 is more advantageous than inhibiting the subsequent stages of the SARS-CoV-2 life cycle. Based on current published evidence, we have summarized the different in silico based studies and repurposing of anti-viral drugs to target ACE2, SARS-CoV-2 S-Protein: ACE2 and SARS-CoV-2 S-RBD: ACE2. This review will be useful to researchers looking to effectively recognize and deal with SARS-CoV-2, and in the development of repurposed ACE2 inhibitors against COVID-19.

PMID:34623536 | PMC:PMC8498772 | DOI:10.1007/s41061-021-00353-7

Heart Fail Rev. 2021 Oct 8. doi: 10.1007/s10741-021-10166-x. Online ahead of print.

ABSTRACT

The biogenic amine, histamine, is found predominantly in mast cells, as well as specific histaminergic neurons. Histamine exerts its many and varied actions via four G-protein-coupled receptors numbered one through four. Histamine has multiple effects on cardiac physiology, mainly via the histamine 1 and 2 receptors, which on a simplified level have opposing effects on heart rate, force of contraction, and coronary vasculature function. In heart failure, the actions of the histamine receptors are complex, the histamine 1 receptor appears to have detrimental actions predominantly in the coronary vasculature, while the histamine 2 receptor mediates adverse effects on cardiac remodeling via actions on cardiomyocytes, fibroblasts, and even endothelial cells. Conversely, there is growing evidence that the histamine 3 receptor exerts protective actions when activated. Little is known about the histamine 4 receptor in heart failure. Targeting histamine receptors as a therapeutic approach for heart failure is an important area of investigation given the over-the-counter access to many compounds targeting these receptors, and thus the relatively straight forward possibility of drug repurposing. In this review, we briefly describe histamine receptor signaling and the actions of each histamine receptor in normal cardiac physiology, before describing in more detail the known role of each histamine receptor in adverse cardiac remodeling and heart failure. This includes information from both clinical studies and experimental animal models. It is the goal of this review article to bring more focus to the possibility of targeting histamine receptors as therapy for heart failure.

PMID:34622365 | DOI:10.1007/s10741-021-10166-x

Transl Clin Pharmacol. 2021 Sep;29(3):117-124. doi: 10.12793/tcp.2021.29.e18. Epub 2021 Sep 27.

ABSTRACT

Drug repurposing, or repositioning, is to identify new uses for existing drugs. Significantly reducing the costs and time-to-market of a medication, drug repurposing has been an alternative tool to accelerate drug development process. On the other hand, 'real world data (RWD)' has been also increasingly used to support drug development process owing to its better representing actual pattern of drug treatment and outcome in real world. In the healthcare domain, RWD refers to data collected from sources other than traditional clinical trials; for example, in electronic health records or claims and billing data. With the enactment of the 21st Century Cures Act, which encourages the use of RWD in drug development and repurposing as well, such increasing trend in RWD use will be expedited. In this context, this review provides an overview of recent progresses in the area of drug repurposing where RWD was used by firstly introducing the increasing trend and regulatory change in the use of RWD in drug development, secondly reviewing published works using RWD in drug repurposing, classifying them in the repurposing strategy, and lastly addressing limitations and advantages of RWDs.

PMID:34621704 | PMC:PMC8492393 | DOI:10.12793/tcp.2021.29.e18

Front Pharmacol. 2021 Sep 21;12:635293. doi: 10.3389/fphar.2021.635293. eCollection 2021.

ABSTRACT

Interstitial lung diseases (ILDs) are a group of respiratory disorders characterized by chronic inflammation and fibrosis of the pulmonary interstitial tissues. Although the etiology of ILD remains unclear, some drug treatments are among the primary causes of ILD. In the present study, we analyzed the FDA Adverse Event Reporting System and JMDC Inc. insurance claims to identify a coexisting drug that reduced the incidence of ILD associated with the use of an anti-arrhythmic agent, amiodarone, and found that the thrombin inhibitor dabigatran prevented the amiodarone-induced ILD in both clinical datasets. In an experimental validation of the hypothesis, long-term oral treatment of mice with amiodarone caused a gradual decrease in body weight caused by respiratory insufficiency. In the lungs of amiodarone-treated mice, infiltration of macrophages was observed in parallel with a delayed upregulation of the platelet-derived growth factor receptor α gene. In contrast, co-treatment with dabigatran significantly attenuated these amiodarone-induced changes indicative of ILD. These results suggest that dabigatran is effective in preventing drug-induced ILD. This combinatorial approach of drug repurposing based on clinical big data will pave the way for finding a new treatment with high clinical predictability and a well-defined molecular mechanism.

PMID:34621164 | PMC:PMC8490809 | DOI:10.3389/fphar.2021.635293

Proc Natl Acad Sci U S A. 2021 Oct 12;118(41):e2102975118. doi: 10.1073/pnas.2102975118.

ABSTRACT

The atrophic form of age-related macular degeneration (dry AMD) affects nearly 200 million people worldwide. There is no Food and Drug Administration (FDA)-approved therapy for this disease, which is the leading cause of irreversible blindness among people over 50 y of age. Vision loss in dry AMD results from degeneration of the retinal pigmented epithelium (RPE). RPE cell death is driven in part by accumulation of Alu RNAs, which are noncoding transcripts of a human retrotransposon. Alu RNA induces RPE degeneration by activating the NLRP3-ASC inflammasome. We report that fluoxetine, an FDA-approved drug for treating clinical depression, binds NLRP3 in silico, in vitro, and in vivo and inhibits activation of the NLRP3-ASC inflammasome and inflammatory cytokine release in RPE cells and macrophages, two critical cell types in dry AMD. We also demonstrate that fluoxetine, unlike several other antidepressant drugs, reduces Alu RNA-induced RPE degeneration in mice. Finally, by analyzing two health insurance databases comprising more than 100 million Americans, we report a reduced hazard of developing dry AMD among patients with depression who were treated with fluoxetine. Collectively, these studies identify fluoxetine as a potential drug-repurposing candidate for dry AMD.

PMID:34620711 | DOI:10.1073/pnas.2102975118

Pharmazie. 2021 Oct 1;76(10):484-487. doi: 10.1691/ph.2021.1674.

ABSTRACT

We aimed to clarify whether various antipsychotics ameliorate cisplatin-induced pica behavior in mice using a drug repositioning approach. Mice were administered cisplatin (12.5 mg/kg, i.p.) with or without olanzapine (1 mg/kg, i.p.), asenapine (4 mg/kg, i.p.), mirtazapine (5 mg/kg, i.p.) or standard three-drug antiemetics (granisetron [0.5 mg/kg, i.p.], fosaprepitant [25 mg/kg, i.p.], and dexamethasone [3 mg/kg, i.p.]). Kaolin, food, and water intake, and spontaneous motor activity on the day before and seven consecutive days after the cisplatin administration were measured using a telemetry system. At the primary endpoint, kaolin intake was significantly higher at day three in the cisplatin group than in the pre-treatment and saline groups ( p < 0.05). Additionally, kaolin intake was not significantly higher in cisplatin with olanzapine, asenapine, and mirtazapine groups for seven days than in the pre-treatment group. At the secondary endpoint, cisplatin decreased the food and water intake, and spontaneous motor activity in a time-dependent manner. Three antipsychotics failed to improve the cisplatin-induced decrease in food and water intake, and spontaneous motor activity. The findings suggest that prophylactic administration of antipsychotics besides olanzapine may improve cisplatin-induced nausea and vomiting in a delayed phase and de-escalate standard 3-drug antiemetics.

PMID:34620275 | DOI:10.1691/ph.2021.1674

Comb Chem High Throughput Screen. 2021 Oct 7. doi: 10.2174/1386207325666211007110638. Online ahead of print.

ABSTRACT

Leprosy is caused by extremely slow-growing and uncultivated mycobacterial pathogens, namely Mycobacterium leprae and M. lepromatosis. Nearly 95% of the new cases of leprosy recorded globally are found in India, Brazil, and 20 other priority countries [WHO, 2019], of which nearly two-thirds of the cases are reported in India alone. Currently, leprosy is treated with dapsone, rifampicin, and clofazimine, also known as multi-drug therapy [MDT], as per the recommendations of WHO since 1981. Still, the number of new leprosy cases recorded globally has remained constant in the last one-decade ,and resistance to multiple drugs has been documented in various parts of the world, even though relapses are rare in patients treated with MDT. Antimicrobial resistance testing against M. leprae or the evaluation of the anti-leprosy activity of new drugs remains a challenge as leprosy bacilli do not grow in vitro. Besides, developing a new drug against leprosy through the conventional drug development process is not economically attractive or viable for pharma companies. Therefore, a promising alternative is the repurposing of existing drugs/approved medications or their derivatives for assessing their anti-leprosy potential. It is an efficient method to identify novel medicinal and therapeutic properties of approved drug molecules. Any combinatorial chemotherapy that combines these repurposed drugs with the existing first-line [MDT] and second-line drugs could improve the bactericidal and synergistic effects against these notorious bacteria and can help in achieving the much-cherished goal of "leprosy-free world". This review highlights novel opportunities for drug repurposing to combat resistance to current therapeutic approaches.

PMID:34620073 | DOI:10.2174/1386207325666211007110638

Curr Mol Pharmacol. 2021 Oct 6. doi: 10.2174/1874467214666211006123728. Online ahead of print.

ABSTRACT

Advances in cancer therapy have yet to impact worldwide cancer mortality. Poor cancer drug affordability is one of the factors limiting mortality burden strikes. Up to now, cancer drug repurposing had no meet expectations concerning drug affordability. The three FDA-approved cancer drugs developed under repurposing -all-trans-retinoic acid, arsenic trioxide, and thalidomide- do not differ in price from other drugs developed under the classical model. Though additional factors affect the whole process from inception to commercialization, the repurposing of widely used, commercially available, and cheap drugs may help. This work reviews the concept of the malignant metabolic phenotype and its exploitation by simultaneously blocking key metabolic processes altered in cancer. We elaborate on a combination called BAPST, which stands for the following drugs and pathways they inhibit: Benserazide (glycolysis), Apomorphine (glutaminolysis), Pantoprazole (Fatty-acid synthesis), Simvastatin (mevalonate pathway), and Trimetazidine (Fatty-acid oxidation). Their respective primary indications are: • Parkinson's disease (benserazide and apomorphine). • Peptic ulcer disease (pantoprazole). • Hypercholesterolemia (simvastatin). • Ischemic heart disease (trimetazidine). When used for their primary indication, the literature review on each of these drugs shows they have a good safety profile and lack predicted pharmacokinetic interaction among them. Most importantly, the inhibitory enzymatic concentrations required for inhibiting their cancer targets enzymes are below the plasma concentrations observed when these drugs are used for their primary indication. Based on that, we propose that the regimen BAPTS merits preclinical testing.

PMID:34620071 | DOI:10.2174/1874467214666211006123728

Virology. 2021 Oct 2;564:33-38. doi: 10.1016/j.virol.2021.09.009. Online ahead of print.

ABSTRACT

Endemic seasonal coronaviruses cause morbidity and mortality in a subset of patients, but no specific treatment is available. Molnupiravir is a promising pipeline antiviral drug for treating SARS-CoV-2 infection potentially by targeting RNA-dependent RNA polymerase (RdRp). This study aims to evaluate the potential of repurposing molnupiravir for treating seasonal human coronavirus (HCoV) infections. Molecular docking revealed that the active form of molnupiravir, β-D-N4-hydroxycytidine (NHC), has similar binding affinity to RdRp of SARS-CoV-2 and seasonal HCoV-NL63, HCoV-OC43 and HCoV-229E. In cell culture models, treatment of molnupiravir effectively inhibited viral replication and production of infectious viruses of the three seasonal coronaviruses. A time-of-drug-addition experiment indicates the specificity of molnupiravir in inhibiting viral components. Furthermore, combining molnupiravir with the protease inhibitor GC376 resulted in enhanced antiviral activity. Our findings highlight that the great potential of repurposing molnupiravir for treating seasonal coronavirus infected patients.

PMID:34619630 | DOI:10.1016/j.virol.2021.09.009

Sci Rep. 2021 Oct 6;11(1):19839. doi: 10.1038/s41598-021-99399-2.

ABSTRACT

Computational drug repositioning aims at ranking and selecting existing drugs for novel diseases or novel use in old diseases. In silico drug screening has the potential for speeding up considerably the shortlisting of promising candidates in response to outbreaks of diseases such as COVID-19 for which no satisfactory cure has yet been found. We describe DrugMerge as a methodology for preclinical computational drug repositioning based on merging multiple drug rankings obtained with an ensemble of disease active subnetworks. DrugMerge uses differential transcriptomic data on drugs and diseases in the context of a large gene co-expression network. Experiments with four benchmark diseases demonstrate that our method detects in first position drugs in clinical use for the specified disease, in all four cases. Application of DrugMerge to COVID-19 found rankings with many drugs currently in clinical trials for COVID-19 in top positions, thus showing that DrugMerge can mimic human expert judgment.

PMID:34615934 | DOI:10.1038/s41598-021-99399-2

Expert Rev Anti Infect Ther. 2021 Oct 6. doi: 10.1080/14787210.2022.1990042. Online ahead of print.

ABSTRACT

BACKGROUND: Treatment and control of schistosomiasis rely on a single drug, praziquantel. New orally active antischistosomals featuring novel molecular scaffolds are urgently needed to prevent the emergence of resistance.

METHODS: We screened 400 drug-like compounds contained in the open-access Pandemic Response Box (PRB) against newly transformed schistosomula (NTS) at a concentration of 10µM scoring death, changes in motility and morphological alterations. Compounds displaying an activity ≥66% at 72h underwent testing against adult Schistosoma mansoni in vitro. Fast-acting (≥66% at 24h), non-toxic clinical candidates were selected as hits and were investigated in the patent S. mansoni mouse model.

RESULTS: We identified 26 hits active against NTS, of which 17 elicited ≥66% activity against adult S. mansoni following 24h of drug exposure. The highest activity against adult S. mansoni was observed with MMV1581558 (EC50 value of 0.18±0.01µM) and nitazoxanide (0.47±0.07µM). Of five compounds tested in vivo, MMV1581558 and the approved drug ozanimod, reduced average worm burden versus controls by 42±25% and 36±19% respectively, after a single oral dose of 200mg/kg bodyweight in mice harboring a chronic S. mansoni infection.

CONCLUSION: MMV1581558 discovered from screening the PRB represents a novel antischistosomal scaffold with high in vitro antischistosomal activity amenable to chemical modification for drug development.

PMID:34612126 | DOI:10.1080/14787210.2022.1990042

Biocatal Agric Biotechnol. 2021 Oct 1:102178. doi: 10.1016/j.bcab.2021.102178. Online ahead of print.

ABSTRACT

The recent outbreak of COVID-19, caused by the novel pathogen SARS-coronavirus 2 (SARS-CoV-2) is a severe health emergency. In this pandemic, drug repurposing seems to be the most promising alternative to identify effective therapeutic agents for immediate treatment of infected patients. The present study aimed to evaluate all the drugs present in drug bank as potential novel SARS-CoV-2 inhibitors, using computational drug repurposing studies. Docking-based virtual screening and binding energy prediction were performed, followed by Absorption Distribution Metabolism Excretion calculation. Hydroxychloroquine and Nelfinavir have been identified as the best potential inhibitor against the SARS-CoV-2, therefore, they were used as reference compounds in computational DR studies. The docking study revealed 13 best compounds based on their highest binding affinity, binding energy, and dock score concerning the other screened compounds. Out of 13, only 4 compounds were further shortlisted based on their binding energy and best ADME properties. The hierarchical virtual screening yielded the best 04 drugs, DB07042 (compound 2), DB13035 (compound 3), DB13604 (compound 5) and DB08253 (compound 6), with commendable binding energies in kcal/mol, i.e. -65.45, -62.01, -52.09 and -51.70 respectively. Further, Molecular dynamics simulation with 04 best-retrieved hits has confirmed stable trajectories in protein in terms of root mean square deviation and root mean square fluctuation. During 30 nanosecond simulation, the interactions were also found similar to the docking-based studies. However, clinical studies are necessary to investigate their therapeutic use against this outbreak.

PMID:34611467 | PMC:PMC8483991 | DOI:10.1016/j.bcab.2021.102178

Mol Omics. 2021 Oct 5. doi: 10.1039/d1mo00237f. Online ahead of print.

ABSTRACT

Drug repositioning, a method that relies on the information from the original drug-disease association matrix, aims to identify new indications for existing drugs and is expected to greatly reduce the cost and time of drug development. However, most current drug repositioning methods make use of the original drug-disease association matrix directly without preconditioning. As relatively only a few associations between drugs and diseases have been determined from actual observations, the original drug-disease association matrix used in the prediction is sparse, which affects the performance of the prediction method. A method for mining similar features of drugs and diseases is still lacking. To solve these problems, we developed a bipartite graph diffusion algorithm with multiple similarity integration for drug-disease association prediction (BGMSDDA). First, the weight K nearest known neighbors (WKNKN) algorithm was used to reconstruct the drug-disease association matrix. Secondly, an effective method was designed to extract similar characteristics of drugs and diseases based on integrating linear neighborhood similarity and Gaussian kernel similarity. Finally, bipartite graph diffusion was used to infer undiscovered drug-disease associations. After carrying out 10-fold cross-validation experiments, BGMSDDA showed excellent performance on two datasets, specifically with AUC values of 0.939 (Fdataset) and 0.954 (Cdataset), and AUPR values of 0.466 (Fdataset) and 0.565 (Cdataset). Furthermore, to evaluate the accuracy of the results of BGMSDDA, we conducted case studies on three medically used drugs selected from Fdataset and Cdataset and validated the predictive associated diseases of each drug with some databases. Based on the results obtained, BGMSDDA was demonstrated to be useful for predicting drug-disease associations.

PMID:34610633 | DOI:10.1039/d1mo00237f

MRS Bull. 2021 Sep 29:1-7. doi: 10.1557/s43577-021-00185-2. Online ahead of print.

ABSTRACT

ABSTRACT: From Operation Warp Speed to the lipid mRNA vaccine, the COVID-19 pandemic has been a watershed moment for technological development, production, and implementation. The scale and pace of innovation and global collaboration has likely not been experienced since World War II. This article highlights some of the engineering accomplishments that occurred during the pandemic. We provide a broad overview of the technological achievements in vaccine design, antibody engineering, drug repurposing, and rapid diagnostic testing. We also discuss what the future of these technologies and the future of large-scale collaborations might look like moving forward.

PMID:34608355 | PMC:PMC8480751 | DOI:10.1557/s43577-021-00185-2

Curr Med Imaging. 2021 Oct 4. doi: 10.2174/1573405617666211004115208. Online ahead of print.

ABSTRACT

COVID-19 is a pandemic initially identified in Wuhan, China, which is caused by a novel coronavirus, also recognized as the Severe Acute Respiratory Syndrome (SARS-nCoV-2). Unlike other coronaviruses, this novel pathogen may cause unusual contagious pain which results in viral pneumonia, serious heart problems, and even death. Researchers worldwide are continuously striving to develop a cure for this highly infective disease, yet there are no well-defined absolute treatments available at present. Several vaccination drives with emergency use authorisation vaccines are being done across many countries, however, their long term efficacy and side-effects study are yet to be done. The research community is analysing the situation by collecting the datasets from various sources. Healthcare professionals must thoroughly analyse the situation, devise preventive measures for this pandemic, and even develop possible drug combinations. Various analytical and statistical models have been developed, however, their outcome rate is prolonged. Thus, modern science stresses on the application of state-of-the-art methods in this combat against COVID-19. The application of Artificial intelligence (AI), and AI-driven tools are emerging as effective tools, especially with X-Ray and CT-Scan imaging data of infected subjects, infection trend predictions etc. The high efficacy of these AI systems can be observed in terms of highly accurate results, i.e. >95%, as reported in various studies. AI-driven tools are being used in COVID diagnostic, therapeutics, trend prediction, drug design and prevention to help fight against this pandemic. This paper aims to provide a deep insight into the comprehensive literature about AI and AI-driven tools in this battle against the COVID-19 pandemic. The extensive literature is divided into five sections, each describing the application of AI against COVID-19 viz. COVID-19 Prevention, diagnostic, infection spread trend prediction, therapeutic and drug repurposing.

PMID:34607548 | DOI:10.2174/1573405617666211004115208

Curr Top Med Chem. 2021 Oct 3. doi: 10.2174/1568026621666211004095917. Online ahead of print.

ABSTRACT

There is an increasing amount of data arising from neurobehavioral sciences and medical records that cannot be adequately analyzed by traditional research methods. New drugs develop at a slow rate and seem unsatisfactory for the majority of neurobehavioral disorders. Machine learning (ML) techniques, instead, can incorporate psychopathological, computational, cognitive, and neurobiological underpinning knowledge leading to a refinement of detection, diagnosis, prognosis, treatment, research, and support. Machine and deep learning methods are currently used to accelerate the process of discovering new pharmacological targets and drugs.

OBJECTIVE: The present work reviews current evidence regarding the contribution of machine learning to the discovery of new drug targets.

METHODS: Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection published until May 2021 were included in this review.

RESULTS: The most significant areas of research are schizophrenia, depression and anxiety, Alzheimer´s disease, and substance use disorders. ML techniques have pinpointed target gene candidates and pathways, new molecular substances, and several biomarkers regarding psychiatric disorders. Drug repositioning studies using ML have identified multiple drug candidates as promising therapeutic agents.

CONCLUSION: Next-generation ML techniques and subsequent deep learning may power new findings regarding the discovery of new pharmacological agents by bridging the gap between biological data and chemical drug information.

PMID:34607546 | DOI:10.2174/1568026621666211004095917

Curr Top Med Chem. 2021 Oct 3. doi: 10.2174/1568026621666211004093023. Online ahead of print.

NO ABSTRACT

PMID:34607543 | DOI:10.2174/1568026621666211004093023

Heliyon. 2021 Oct;7(10):e08089. doi: 10.1016/j.heliyon.2021.e08089. Epub 2021 Sep 29.

ABSTRACT

Many studies have shown that the lysosomal cathepsins, especially cathepsins B/L (CTSB/L) are required for SARS-CoV-2 entry into host cells. Lysosomal proteases, cathepsins are indispensable for normal health and are involved in several brain disorders occurring at different development age periods. On the other hand, it has been well known that COVID-19 infection is largely associated with several neurological disorders. Taken together these findings and given the high levels of expression of CTSB/L in the brain, we here proposed a reasonable hypothesis about the involvement of CTSB/L in the neurological manifestations linked to COVID-19. Pharmacological inhibitions of the CTSB/L could be a potential therapeutic target to block the virus entry as well as to mitigate the brain disorders. To this end, we utilized the network-based drug repurposing analyses to identify the possible drugs that can target CTSB/L. This study identifies the molecules like cyclosporine, phenytoin, and paclitaxel as potential drugs with binding ability to the CTSB/L. Further, we have performed molecular docking and all-atom molecular dynamics (MD) simulations to investigate the stability of CTSL-drug complexes. The results showed strong and stable binding of drugs with CTSL.

PMID:34604555 | PMC:PMC8479516 | DOI:10.1016/j.heliyon.2021.e08089

Biomed Res Int. 2021 Sep 23;2021:9921195. doi: 10.1155/2021/9921195. eCollection 2021.

ABSTRACT

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies worldwide. Although there have been extensive studies on the molecular mechanisms of its carcinogenesis, FDA-approved drugs for HCC are rare. Side effects, development time, and cost of these drugs are the major bottlenecks, which can be partially overcome by drug repositioning. In this study, we developed a computational framework to study the mechanisms of HCC carcinogenesis, in which drug perturbation-induced gene expression signatures were utilized for repositioning of potential drugs. Specifically, we first performed differential expression analysis and coexpression network module analysis on the HCC dataset from The Cancer Genome Atlas database. Differential gene expression analysis identified 1,337 differentially expressed genes between HCC and adjacent normal tissues, which were significantly enriched in functions related to various pathways, including α-adrenergic receptor activity pathway and epinephrine binding pathway. Weighted gene correlation network analysis (WGCNA) suggested that the number of coexpression modules was higher in HCC tissues than in normal tissues. Finally, by correlating differentially expressed genes with drug perturbation-related signatures, we prioritized a few potential drugs, including nutlin and eribulin, for the treatment of hepatocellular carcinoma. The drugs have been reported by a few experimental studies to be effective in killing cancer cells.

PMID:34604388 | PMC:PMC8483911 | DOI:10.1155/2021/9921195

Front Mol Biosci. 2021 Sep 17;8:741316. doi: 10.3389/fmolb.2021.741316. eCollection 2021.

ABSTRACT

Copper (Cu) plays a pivotal role in cancer progression by acting as a co-factor that regulates the activity of many enzymes and structural proteins in cancer cells. Therefore, Cu-based complexes have been investigated as novel anticancer metallodrugs and are considered as a complementary strategy for currently used platinum agents with undesirable general toxicity. Due to the high failure rate and increased cost of new drugs, there is a global drive towards the repositioning of known drugs for cancer treatment in recent years. Disulfiram (DSF) is a first-line antialcoholism drug used in clinics for more than 65 yr. In combination with Cu, it has shown great potential as an anticancer drug by targeting a wide range of cancers. The reaction between DSF and Cu ions forms a copper diethyldithiocarbamate complex (Cu(DDC)2 also known as CuET) which is the active, potent anticancer ingredient through inhibition of NF-κB and ubiquitin-proteasome system as well as alteration of the intracellular reactive oxygen species (ROS). Importantly, DSF/Cu inhibits several molecular targets related to drug resistance, stemness, angiogenesis and metastasis and is thus considered as a novel strategy for overcoming tumour recurrence and relapse in patients. Despite its excellent anticancer efficacy, DSF has proven unsuccessful in several cancer clinical trials. This is likely due to the poor stability, rapid metabolism and/or short plasma half-life of the currently used oral version of DSF and the inability to form Cu(DDC)2 at relevant concentrations in tumour tissues. Here, we summarize the scientific rationale, molecular targets, and mechanisms of action of DSF/Cu in cancer cells and the outcomes of oral DSF ± Cu in cancer clinical trials. We will focus on the novel insights on harnessing the immune system and hypoxic microenvironment using DSF/Cu complex and discuss the emerging delivery strategies that can overcome the shortcomings of DSF-based anticancer therapies and provide opportunities for translation of DSF/Cu or its Cu(DDC)2 complex into cancer therapeutics.

PMID:34604310 | PMC:PMC8484884 | DOI:10.3389/fmolb.2021.741316