Viruses. 2022 Sep 29;14(10):2150. doi: 10.3390/v14102150.

ABSTRACT

The rising incidence of dengue virus (DENV) infections in the tropical and sub-tropical regions of the world emphasizes the need to identify effective therapeutic drugs against the disease. Repurposing of drugs has emerged as a novel concept to combat pathogens. In this study, we employed a transcriptomics-based bioinformatics approach for drug identification against DENV. Gene expression omnibus datasets from patients with different grades of dengue disease severity and healthy controls were used to identify differentially expressed genes in dengue cases, which were then applied to the query tool of Connectivity Map to identify the inverse gene-disease-drug relationship. A total of sixteen identified drugs were investigated for their prophylactic, virucidal, and therapeutic effects against DENV. Focus-forming unit assay and quantitative RT-PCR were used to evaluate the antiviral activity. Results revealed that five compounds, viz., resveratrol, doxorubicin, lomibuvir, elvitegravir, and enalaprilat, have significant anti-DENV activity. Further, molecular docking studies showed that these drugs can interact with a variety of protein targets of DENV, including the glycoprotein, the NS5 RdRp, NS2B-NS3 protease, and NS5 methyltransferase The in vitro and in silico results, therefore, reveal that these drugs have the ability to decrease DENV-2 production, suggesting that these drugs or their derivatives could be attempted as therapeutic agents against DENV infections.

PMID:36298705 | DOI:10.3390/v14102150

Mol Cell Biochem. 2022 Oct 27. doi: 10.1007/s11010-022-04584-0. Online ahead of print.

ABSTRACT

Glioblastoma (GBM) is the most prevalent primary central nervous system tumour in adults. The lethality of GBM lies in its highly invasive, infiltrative, and neurologically destructive nature resulting in treatment failure, tumour recurrence and death. Even with current standard of care treatment with surgery, radiotherapy and chemotherapy, surviving tumour cells invade throughout the brain. We have previously shown that this invasive phenotype is facilitated by actin-rich, membrane-based structures known as invadopodia. The formation and matrix degrading activity of invadopodia is enhanced in GBM cells that survive treatment. Drug repurposing provides a means of identifying new therapeutic applications for existing drugs without the need for discovery or development and the associated time for clinical implementation. We investigate several FDA-approved agents for their ability to act as both cytotoxic agents in reducing cell viability and as 'anti-invadopodia' agents in GBM cell lines. Based on their cytotoxicity profile, three agents were selected, bortezomib, everolimus and fludarabine, to test their effect on GBM cell invasion. All three drugs reduced radiation/temozolomide-induced invadopodia activity, in addition to reducing GBM cell viability. These drugs demonstrate efficacious properties warranting further investigation with the potential to be implemented as part of the treatment regime for GBM.

PMID:36302993 | DOI:10.1007/s11010-022-04584-0

IEEE J Biomed Health Inform. 2022 Oct 27;PP. doi: 10.1109/JBHI.2022.3217433. Online ahead of print.

ABSTRACT

Identifying protein targets for drugs establishes an indispensable knowledge foundation for drug repurposing and drug development. Though expensive and time-consuming, vitro trials are widely employed to discover drug targets, and the existing relevant computational algorithms still cannot satisfy the demand for real application in drug R&D with regards to the prediction accuracy and performance efficiency, which are urgently needed to be improved. To this end, we propose here the PPAEDTI model, which uses the graph personalized propagation technique to predict drug-target interactions from the known interaction network. To evaluate the prediction performance, six benchmark datasets were used for testing with some state-of-the-art methods compared. As a result, using the 5-fold cross-validation, the proposed PPAEDTI model achieves average AUCs>90% on 5 collected datasets. We also manually checked the top-20 prediction list for 2 proteins (hsa:775 and hsa:779) and a kind of drug (D00618), and successfully confirmed 18, 17, and 20 items from the public datasets, respectively. The experimental results indicate that, given known drug-target interactions, the PPAEDTI model can provide accurate predictions for the new ones, which is anticipated to serve as a useful tool for pharmacology research. Using the proposed model that was trained with the collected datasets, we have built a computational platform that is accessible at http://120.77.11.78/PPAEDTI/ and corresponding codes and datasets are also released.

PMID:36301791 | DOI:10.1109/JBHI.2022.3217433

J Gastroenterol. 2022 Oct 27. doi: 10.1007/s00535-022-01929-w. Online ahead of print.

ABSTRACT

BACKGROUND: To establish a treatment option for liver fibrosis, the possibility of the drug repurposing theory was investigated, with a focus on the off-target effects of active pharmaceutical ingredients.

METHODS: First, several active pharmaceutical ingredients were screened for their effects on the gene expression in the hepatocytes using chimeric mice with humanized hepatocytes. As per the gene expression-based screening assay for 36 medications, we assessed the mechanism of the antifibrotic effect of letrozole, a third-generation aromatase inhibitor, in mouse models of liver fibrosis induced by carbon tetrachloride (CCl4) and a methionine choline-deficient (MCD) diet. We assessed liver histology, serum biochemical markers, and fibrosis-related gene and protein expressions in the hepatocytes.

RESULTS: A gene expression-based screening assay revealed that letrozole had a modifying effect on fibrosis-related gene expression in the hepatocytes, including YAP, CTGF, TGF-β, and CYP26A1. Letrozole was administered to mouse models of CCl4- and MCD-induced liver fibrosis and it ameliorated the liver fibrosis. The mechanisms involved the inhibition of the Yap-Ctgf profibrotic pathway following a decrease in retinoic acid levels in the hepatocytes caused by suppression of the hepatic retinol dehydrogenase, Hsd17b13 and activation of the retinoic acid hydrogenase, Cyp26a1.

CONCLUSIONS: Letrozole slowed the progression of liver fibrosis by inhibiting the Yap-Ctgf pathway. The mechanisms involved the modification of the Hsd17b13 and Cyp26a1 expressions led to the suppression of retinoic acid in the hepatocytes, which contributed to the activation of Yap-Ctgf pathway. Because of its off-target effect, letrozole could be repurposed for the treatment of liver fibrosis. The third-generation aromatase inhibitor letrozole ameliorated liver fibrosis by suppressing the Yap-Ctgf pathway by partially modifying the Hsd17b13 and Cyp26a1 expressions, which reduced the retinoic acid level in the hepatocytes. The gene expression analysis using chimeric mice with humanized liver revealed that the mechanisms are letrozole specific and, therefore, may be repurposed for the treatment of liver fibrosis.

PMID:36301364 | DOI:10.1007/s00535-022-01929-w

Vaccines (Basel). 2022 Sep 30;10(10):1643. doi: 10.3390/vaccines10101643.

ABSTRACT

Recent research has highlighted that a large section of druggable protein targets in the Human interactome remains unexplored for various diseases. It might lead to the drug repurposing study and help in the in-silico prediction of new drug-human protein target interactions. The same applies to the current pandemic of COVID-19 disease in global health issues. It is highly desirable to identify potential human drug targets for COVID-19 using a machine learning approach since it saves time and labor compared to traditional experimental methods. Structure-based drug discovery where druggability is determined by molecular docking is only appropriate for the protein whose three-dimensional structures are available. With machine learning algorithms, differentiating relevant features for predicting targets and non-targets can be used for the proteins whose 3-D structures are unavailable. In this research, a Machine Learning-based Drug Target Discovery (ML-DTD) approach is proposed where a machine learning model is initially built up and tested on the curated dataset consisting of COVID-19 human drug targets and non-targets formed by using the Therapeutic Target Database (TTD) and human interactome using several classifiers like XGBBoost Classifier, AdaBoost Classifier, Logistic Regression, Support Vector Classification, Decision Tree Classifier, Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbour Classifier (KNN). In this method, protein features include Gene Set Enrichment Analysis (GSEA) ranking, properties derived from the protein sequence, and encoded protein network centrality-based measures. Among all these, XGBBoost, KNN, and Random Forest models are satisfactory and consistent. This model is further used to predict novel COVID-19 human drug targets, which are further validated by target pathway analysis, the emergence of allied repurposed drugs, and their subsequent docking study.

PMID:36298508 | DOI:10.3390/vaccines10101643

Pharmaceutics. 2022 Sep 29;14(10):2084. doi: 10.3390/pharmaceutics14102084.

ABSTRACT

The molecular revolution could lead drug discovery from chance observation to the rational design of new classes of drugs that could simultaneously be more effective and less toxic. Unfortunately, we are witnessing some failure in this sense, and the causes of the crisis involve a wide range of epistemological and scientific aspects. In pharmacology, one key point is the crisis of the paradigm the "magic bullet", which is to design therapies based on specific molecular targets. Drug repurposing is one of the proposed ways out of the crisis and is based on the off-target effects of known drugs. Here, we propose the microenvironment as the ideal place to direct the off-targeting of known drugs. While it has been extensively investigated in tumors, the generation of a harsh microenvironment is also a phenotype of the vast majority of chronic diseases. The hostile microenvironment, on the one hand, reduces the efficacy of both chemical and biological drugs; on the other hand, it dictates a sort of "Darwinian" selection of those cells armed to survive in such hostile conditions. This opens the way to the consideration of the microenvironment as a convenient target for pharmacological action, with a clear example in proton pump inhibitors.

PMID:36297518 | DOI:10.3390/pharmaceutics14102084

Pharmaceutics. 2022 Sep 28;14(10):2071. doi: 10.3390/pharmaceutics14102071.

ABSTRACT

Nifuroxazide (NAZ), a nitrofuran derivative used to treat diarrhea, has been recently shown to possess anticancer activity. However, its pharmacokinetic profile is poorly known. The pharmacokinetic profile of NAZ was thus investigated in mice using a newly developed method based on high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). We determined the concentrations of NAZ in the plasma and brain tissue of mice treated with the drug. The method proved to be specific, reproducible, precise, and accurate. It also demonstrated high sensitivity, reaching an LOQ in the order of ppb for both matrices, using samples of 100 µL or 0.2 g. The new HPLC-MS/MS assay was successfully applied to study the pharmacokinetics of NAZ after chronic intraperitoneal administration in mice at a dose of 30 mg/kg. One hour after treatment, plasma concentrations of NAZ were in the range of 336-2640 ng/mL. Moreover, unlike the brains of healthy mice or those with healed mechanical injuries, we found that NAZ was able to cross the injured blood-brain barrier of tumor-infiltrated brains. Thus, following i.p. administration, NAZ reaches systemic levels suitable for testing its efficacy in preclinical models of glioblastoma. Overall, these pharmacokinetic data provide robust evidence supporting the repositioning of NAZ as an antitumor drug.

PMID:36297506 | DOI:10.3390/pharmaceutics14102071

Pharmaceuticals (Basel). 2022 Sep 25;15(10):1186. doi: 10.3390/ph15101186.

ABSTRACT

The global burden of cancer necessitates rapid and ongoing development of effective cancer therapies. One promising approach in this context is the repurposing of existing non-cancer drugs for cancer indications. A key to this approach is selecting the cellular targets against which to identify novel repurposed drugs for pre-clinical analysis. Protein kinases are highly sought-after anticancer drug targets since dysregulation of kinases is the hallmark of cancer. To identify potential kinase-targeted drug candidates from the existing portfolio of non-cancer therapeutics, we used combined in silico and in vitro approaches, including ligand-based 3D screening followed by biochemical and cellular assessments. This strategy revealed that the anti-viral drug rilpivirine is an Aurora A kinase inhibitor. In view of previous findings implicating Aurora A kinase in abnormal cell cycle regulation, we also examined the influence of rilpivirine on the growth of T47D breast cancer cells. Herein, we detail the identification of rilpivirine as an Aurora A kinase inhibitor, its molecular basis of inhibitory activity towards this kinase, and its Aurora A-mediated anticancer mechanisms in T47D cells. Our results illustrate the value of integrated in silico and in vitro screening strategies in identifying repurposed drug candidates and provide a scientific basis for further exploring the potential anticancer properties of the anti-viral drug rilpivirine.

PMID:36297298 | DOI:10.3390/ph15101186

Molecules. 2022 Oct 19;27(20):7063. doi: 10.3390/molecules27207063.

ABSTRACT

Infantile onset hereditary spastic paralysis (IAHSP) is a rare neurological disease diagnosed in less than 50 children worldwide. It is transmitted with a recessive pattern and originates from mutations of the ALS2 gene, encoding for the protein alsin and involved in differentiation and maintenance of the upper motoneuron. The exact pathogenic mechanisms of IAHSP and other neurodevelopmental diseases are still largely unknown. However, previous studies revealed that, in the cytosolic compartment, alsin is present as an active tetramer, first assembled from dimer pairs. The C-terminal VPS9 domain is a key interaction site for alsin dimerization. Here, we present an innovative drug discovery strategy, which identified a drug candidate to potentially treat a patient harboring two ALS2 mutations: one truncation at lysine 1457 (not considered) and the substitution of arginine 1611 with a tryptophan (R1611W) in the C-terminus VPS9. With a protein modeling approach, we obtained a R1611W mutant model and characterized the impact of the mutation on the stability and flexibility of VPS9. Furthermore, we showed how arginine 1611 is essential for alsin's homo-dimerization and how, when mutated to tryptophan, it leads to an abnormal dimerization pattern, disrupting the formation of active tetramers. Finally, we performed a virtual screening, individuating an already therapy-approved compound (MK4) able to mask the mutant residue and re-establishing the alsin tetramers in HeLa cells. MK4 has now been approved for compassionate use.

PMID:36296656 | DOI:10.3390/molecules27207063

Molecules. 2022 Oct 18;27(20):7034. doi: 10.3390/molecules27207034.

ABSTRACT

Griseofulvin is an antifungal polyketide metabolite produced mainly by ascomycetes. Since it was commercially introduced in 1959, griseofulvin has been used in treating dermatophyte infections. This fungistatic has gained increasing interest for multifunctional applications in the last decades due to its potential to disrupt mitosis and cell division in human cancer cells and arrest hepatitis C virus replication. In addition to these inhibitory effects, we and others found griseofulvin may enhance ACE2 function, contribute to vascular vasodilation, and improve capillary blood flow. Furthermore, molecular docking analysis revealed that griseofulvin and its derivatives have good binding potential with SARS-CoV-2 main protease, RNA-dependent RNA polymerase (RdRp), and spike protein receptor-binding domain (RBD), suggesting its inhibitory effects on SARS-CoV-2 entry and viral replication. These findings imply the repurposing potentials of the FDA-approved drug griseofulvin in designing and developing novel therapeutic interventions. In this review, we have summarized the available information from its discovery to recent progress in this growing field. Additionally, explored is the possible mechanism leading to rare hepatitis induced by griseofulvin. We found that griseofulvin and its metabolites, including 6-desmethylgriseofulvin (6-DMG) and 4- desmethylgriseofulvin (4-DMG), have favorable interactions with cytokeratin intermediate filament proteins (K8 and K18), ranging from -3.34 to -5.61 kcal mol-1. Therefore, they could be responsible for liver injury and Mallory body (MB) formation in hepatocytes of human, mouse, and rat treated with griseofulvin. Moreover, the stronger binding of griseofulvin to K18 in rodents than in human may explain the observed difference in the severity of hepatitis between rodents and human.

PMID:36296627 | DOI:10.3390/molecules27207034

Membranes (Basel). 2022 Sep 28;12(10):954. doi: 10.3390/membranes12100954.

ABSTRACT

Transient Receptor Potential Melastatin 8 (TRPM8) from the melastatin TRP channel subfamily is a non-selective Ca2+-permeable ion channel with multimodal gating which can be activated by low temperatures and cooling compounds, such as menthol and icilin. Different conditions such as neuropathic pain, cancer, overactive bladder syndrome, migraine, and chronic cough have been linked to the TRPM8 mode of action. Despite the several potent natural and synthetic inhibitors of TRPM8 that have been identified, none of them have been approved for clinical use. The aim of this study was to discover novel blocking TRPM8 agents using automated patch clamp electrophysiology combined with a ligand-based virtual screening based on the SwissSimilarity platform. Among the compounds we have tested, nebivolol and carvedilol exhibited the greatest inhibitory effect, with an IC50 of 0.97 ± 0.15 µM and 9.1 ± 0.6 µM, respectively. This study therefore provides possible candidates for future drug repurposing and suggests promising lead compounds for further optimization as inhibitors of the TRPM8 ion channel.

PMID:36295712 | DOI:10.3390/membranes12100954

J Pers Med. 2022 Oct 18;12(10):1731. doi: 10.3390/jpm12101731.

ABSTRACT

Alzheimer's disease (AD) is a neurologic disorder causing brain atrophy and the death of brain cells. It is a progressive condition marked by cognitive and behavioral impairment that significantly interferes with daily activities. AD symptoms develop gradually over many years and eventually become more severe, and no cure has been found yet to arrest this process. The present study is directed towards suggesting putative novel solutions and paradigms for fighting AD pathogenesis by exploiting new insights from network medicine and drug repurposing strategies. To identify new drug-AD associations, we exploited SAveRUNNER, a recently developed network-based algorithm for drug repurposing, which quantifies the vicinity of disease-associated genes to drug targets in the human interactome. We complemented the analysis with an in silico validation of the candidate compounds through a gene set enrichment analysis, aiming to determine if the modulation of the gene expression induced by the predicted drugs could be counteracted by the modulation elicited by the disease. We identified some interesting compounds belonging to the beta-blocker family, originally approved for treating hypertension, such as betaxolol, bisoprolol, and metoprolol, whose connection with a lower risk to develop Alzheimer's disease has already been observed. Moreover, our algorithm predicted multi-kinase inhibitors such as regorafenib, whose beneficial effects were recently investigated for neuroinflammation and AD pathology, and mTOR inhibitors such as sirolimus, whose modulation has been associated with AD.

PMID:36294870 | DOI:10.3390/jpm12101731

Int J Mol Sci. 2022 Oct 21;23(20):12657. doi: 10.3390/ijms232012657.

ABSTRACT

Individuals with cystic fibrosis (CF) suffer from severe respiratory disease due to a genetic defect in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which impairs airway epithelial ion and fluid secretion. New CFTR modulators that restore mutant CFTR function have been recently approved for a large group of people with CF (pwCF), but ~19% of pwCF cannot benefit from CFTR modulators Restoration of epithelial fluid secretion through non-CFTR pathways might be an effective treatment for all pwCF. Here, we developed a medium-throughput 384-well screening assay using nasal CF airway epithelial organoids, with the aim to repurpose FDA-approved drugs as modulators of non-CFTR-dependent epithelial fluid secretion. From a ~1400 FDA-approved drug library, we identified and validated 12 FDA-approved drugs that induced CFTR-independent fluid secretion. Among the hits were several cAMP-mediating drugs, including β2-adrenergic agonists. The hits displayed no effects on chloride conductance measured in the Ussing chamber, and fluid secretion was not affected by TMEM16A, as demonstrated by knockout (KO) experiments in primary nasal epithelial cells. Altogether, our results demonstrate the use of primary nasal airway cells for medium-scale drug screening, target validation with a highly efficient protocol for generating CRISPR-Cas9 KO cells and identification of compounds which induce fluid secretion in a CFTR- and TMEM16A-indepent manner.

PMID:36293514 | DOI:10.3390/ijms232012657

Int J Mol Sci. 2022 Oct 21;23(20):12648. doi: 10.3390/ijms232012648.

ABSTRACT

Retinal cell death is responsible for irreversible vision loss in many retinal disorders. No commercially approved treatments are currently available to attenuate retinal cell loss and preserve vision. We seek to identify chemicals/drugs with thoroughly-studied biological functions that possess neuroprotective effects in the retina using a computational bioinformatics approach. We queried the National Center for Biotechnology Information (NCBI) to identify genes associated with retinal neuroprotection. Enrichment analysis was performed using ToppGene to identify compounds related to the identified genes. This analysis constructs a Pharmacome from multiple drug-gene interaction databases to predict compounds with statistically significant associations to genes involved in retinal neuroprotection. Compounds with known deleterious effects (e.g., asbestos, ethanol) or with no clinical indications (e.g., paraquat, ozone) were manually filtered. We identified numerous drug/chemical classes associated to multiple genes implicated in retinal neuroprotection using a systematic computational approach. Anti-diabetics, lipid-lowering medicines, and antioxidants are among the treatments anticipated by this analysis, and many of these drugs could be readily repurposed for retinal neuroprotection. Our technique serves as an unbiased tool that can be utilized in the future to lead focused preclinical and clinical investigations for complex processes such as neuroprotection, as well as a wide range of other ocular pathologies.

PMID:36293505 | DOI:10.3390/ijms232012648

Adv Exp Med Biol. 2022 Oct 28. doi: 10.1007/5584_2022_744. Online ahead of print.

ABSTRACT

Drug resistance in leukaemia is a major problem that needs to be addressed. Precision medicine provides an avenue to reduce drug resistance through a personalised treatment plan. It has helped to better stratify patients based on their molecular profile and therefore improved the sensitivity of patients to a given therapeutic regimen. However, therapeutic options are still limited for patients who have already been subjected to many lines of chemotherapy. The process of designing and developing new drugs requires significant resources, including money and time. Drug repurposing has been explored as an alternative to identify effective drug(s) that could be used to target leukaemia and lessen the burden of drug resistance. The drug repurposing process usually includes preclinical studies with drug screening and clinical trials before approval. Although most of the repurposed drugs that have been identified are generally safe for leukaemia treatment, they seem not to be good candidates for monotherapy but could have value in combination with other drugs, especially for patients who have exhausted therapeutic options. In this review, we highlight precision medicine in leukaemia and the role of drug repurposing. Specifically, we discuss the several screening methods via chemoinformatic, in vitro, and ex vivo that have facilitated and accelerated the drug repurposing process.

PMID:36289161 | DOI:10.1007/5584_2022_744

Curr Issues Mol Biol. 2022 Oct 16;44(10):4930-4949. doi: 10.3390/cimb44100335.

ABSTRACT

Our group developed a new model of drug combination consisting of the use of antineoplastic drugs and different repurposed drugs, having demonstrated that antimalarial and central nervous system (CNS) drugs have a promising anticancer profile as standalone agents, as well as in combined regimens. Here, we evaluated the anticancer profiles of two different CNS drugs (edaravone and quetiapine), both alone and in combination with antineoplastic agents for breast and colon cancer, to explore whether these repurposed drugs could synergistically enhance the anticancer potential of chemotherapeutic drugs. We also developed a new model of combination using two repurposed drugs, to explore whether this model of combination could also be suitable for application in breast and colon cancer therapy. MCF-7 and HT-29 cancer cells were incubated for 48 h with each individual drug (0.01-100 µM) to determine their IC50. Cells were then treated with the IC50 value for doxorubicin or paclitaxel (MCF-7) or 5-fluorouracil (HT-29) and combined with increasing concentrations of edaravone or quetiapine for 48 h. Both cell lines were also treated with a combination of two antimalarial drugs (mefloquine and pyronaridine) or two CNS drugs (fluphenazine and sertraline) for 48 h. We found that the use of quetiapine in combined therapies seems to synergistically enhance the anticancer activity of doxorubicin for the management of breast cancer. Both CNS drugs significantly improved the cytotoxic potential of 5-fluorouracil in HT-29 cells, with quetiapine synergistically interacting with the antineoplastic drug in this drug combination. Regarding the combination of repurposed drugs, only found one synergic combination regimen (sertraline IC50 plus variable concentrations of fluphenazine) with anticancer potential against HT-29 colon cancer cells was found. Taken together, these results suggest that quetiapine and edaravone can be used as adjuvant agents in chemotherapy for colon cancer. It was also found that the combination of repurposed drugs, specifically the CNS drugs sertraline and fluphenazine, may have an interesting profile for application in colon cancer novel therapies.

PMID:36286050 | DOI:10.3390/cimb44100335

Ther Adv Respir Dis. 2022 Jan-Dec;16:17534666221132736. doi: 10.1177/17534666221132736.

ABSTRACT

On 30 January 2020, the World Health Organization (WHO) declared the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic a public health emergency of international concern. The viral outbreak led in turn to an exponential growth of coronavirus disease 2019 (COVID-19) cases, that is, a multiorgan disease that has led to more than 6.3 million deaths worldwide, as of June 2022. There are currently few effective drugs approved for treatment of SARS-CoV-2/COVID-19 patients. Many of the compounds tested so far have been selected through a drug repurposing approach, that is, by identifying novel indications for drugs already approved for other conditions. We here present an up-to-date review of the main Food and Drug Administration (FDA)-approved drugs repurposed against SARS-CoV-2 infection, discussing their mechanism of action and their most important preclinical and clinical results. Reviewed compounds were chosen to privilege those that have been approved for use in SARS-CoV-2 patients or that have completed phase III clinical trials. Moreover, we also summarize the evidence on some novel and promising repurposed drugs in the pipeline. Finally, we discuss the current stage and possible steps toward the development of broadly effective drug combinations to suppress the onset or progression of COVID-19.

PMID:36282077 | DOI:10.1177/17534666221132736

Heliyon. 2022 Oct 15;8(10):e11093. doi: 10.1016/j.heliyon.2022.e11093. eCollection 2022 Oct.

ABSTRACT

Acute myeloid leukemia (AML) is one of the most prevalent and acute blood cancers with a poor prognosis and low overall survival rate, especially in the elderly. Although several new AML markers and drug targets have been recently identified, the rate of long-term cancer eradication has not improved significantly due to the presence and drug resistance of AML cancer stem cells (CSCs). Here we develop a novel computational pipeline to analyze the transcriptomic profiles of AML cancer (stem) cells and identify novel candidate AML CSC markers and drug targets. In our novel pipeline we apply a top-down meta-analysis strategy to integrate The Cancer Genome Atlas data with CSC datasets to infer cell stemness features. As a result, a set of genes termed the "AML key CSC genes" along with all the available drugs/compounds that could target them were identified. Overall, our novel computational pipeline could retrieve known cancer drugs (Carfilzomib) and predicted novel drugs such as Zonisamide, Amitriptyline, and their targets amongst the top ranked drugs and drug targets for targeting AML. Additionally, the pipeline applied in this study could be used for the identification of CSC-specific markers, drivers and their respective targeting drugs in other cancer types.

PMID:36281397 | PMC:PMC9586918 | DOI:10.1016/j.heliyon.2022.e11093

Int J Pharm. 2022 Oct 21:122329. doi: 10.1016/j.ijpharm.2022.122329. Online ahead of print.

ABSTRACT

Recently, the U.S. Food and Drug Administration (FDA) approved the first oral antiviral drug to treat mild to moderate cases of coronavirus disease. The combination of nirmatrelvir with an already used protease inhibitor class drug, ritonavir, has led to Paxlovid®. Several studies considered drug repositioning as the first trial for new drugs. The precise identification and quantification of polymorphs in raw materials and finished products are important to researchers involved in pharmaceutical development and quality control processes. In this work, we study the solid-state behavior of the antiretroviral drugs ritonavir and lopinavir in raw materials and in milled compositions. The results indicate that both ritonavir and lopinavir recrystallize in a short time after being ball-milled. Also, mixtures of ritonavir Forms I and II are found in different batches of raw materials from the same manufacturer; besides three equal crystalline samples, an amorphous batch was found in lopinavir. Furthermore, the milling process of the already amorphous lopinavir seems to facilitate the amorphization of ritonavir as well as the production of some unexpected crystalline forms of ritonavir. A phase transition of ritonavir Form I to Form II is only observed when co-milling with amorphous lopinavir. These findings reveal significant variations in phase purity of raw materials that affect the processing and solid-state properties, representing risks for the product quality.

PMID:36280220 | DOI:10.1016/j.ijpharm.2022.122329

Comput Biol Chem. 2022 Oct 12;101:107778. doi: 10.1016/j.compbiolchem.2022.107778. Online ahead of print.

ABSTRACT

The virus that causes Ebola is fatal. Although many researchers have attempted to contain this deadly infection, the fatality rate remains high. The atom-pair fingerprint technique was used to compare drugs suggested for the treatment of Ebola or those that are currently being tested in clinical settings. Subsequently, using scaffold network graph (SNG) methods, the molecular and structural scaffolds of the drugs chosen based on these similar results were created, and the drug structures were examined. Public databases (PubChem and DrugBank) and literature regarding Ebola treatment were used in the analysis. Graphical representations of the molecular architecture and core structures of the drugs with the highest similarity to Food and Drug Administration (FDA)-approved drugs were produced using the SNG method. The combination of molnupiravir, the first licensed oral medication candidate for COVID-19, and favipiravir, employed in other viral outbreaks, should be further researched for treating Ebola, as observed in our study. We also believe that chemists will benefit from understanding the core structure(s) of medication molecules effective against the Ebola virus, their inhibitors, and the chemical structure similarities of existing pharmaceuticals utilized to build alternative drugs or drug combinations.

PMID:36279832 | DOI:10.1016/j.compbiolchem.2022.107778