Heliyon. 2021 Jun 16;7(6):e07320. doi: 10.1016/j.heliyon.2021.e07320. eCollection 2021 Jun.

ABSTRACT

Waddlia chondrophila is an emerging pathogen that has been implicated in numerous unpropitious pregnancy events in humans and ruminants. Taking into account its association with abortigenic events, possible modes of transmission, and future risk, immediate clinical measures are required to prevent widespread damage caused by this organism and hence this study. Here, a subtractive proteomics approach was employed to identify druggable proteins of W. chondrophila. Considering the essential genes, antibiotic resistance proteins, and virulence factors, 676 unique important proteins were initially identified for this bacterium. Afterward, NCBI BLASTp performed against human proteome identified 223 proteins that were further pushed into KEGG Automatic Annotation Server (KAAS) for automatic annotation. Using the information from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database 14 Waddlia specific metabolic pathways were identified with respect to humans. Analyzing the data from KAAS and KEGG databases, forty-eight metabolic pathway-dependent, and seventy metabolic pathway independent proteins were identified. Standalone BLAST search against DrugBank FDA approved drug targets revealed eight proteins that are finally considered druggable proteins. Prediction of three-dimensional structures was done for the eight proteins through homology modeling and the Ramachandran plot model showed six models as a valid prediction. Finally, virtual screening against MurB protein was performed using FDA approved drugs to employ the drug repositioning strategy. Three drugs showed promising docking results that can be used for therapeutic purposes against W. chondrophila following the clinical validation of the study.

PMID:34195427 | PMC:PMC8239728 | DOI:10.1016/j.heliyon.2021.e07320

BMJ Open. 2021 Jun 30;11(6):e051343. doi: 10.1136/bmjopen-2021-051343.

ABSTRACT

INTRODUCTION: Alzheimer's disease (AD) is one of the most common causes of dementia. Pathogenic variants in the presenilin 1 (PSEN1) gene are the most frequent cause of early-onset AD. Medications for patients with AD bearing PSEN1 mutation (PSEN1-AD) are limited to symptomatic therapies and no established radical treatments are available. Induced pluripotent stem cell (iPSC)-based drug repurposing identified bromocriptine as a therapeutic candidate for PSEN1-AD. In this study, we used an enrichment strategy with iPSCs to select the study population, and we will investigate the safety and efficacy of an orally administered dose of bromocriptine in patients with PSEN1-AD.

METHODS AND ANALYSIS: This is a multicentre, randomised, placebo-controlled trial. AD patients with PSEN1 mutations and a Mini Mental State Examination-Japanese score of ≤25 will be randomly assigned, at a 2:1 ratio, to the trial drug or placebo group (≥4 patients in TW-012R and ≥2 patients in placebo). This clinical trial consists of a screening period, double-blind phase (9 months) and extension phase (3 months). The double-blind phase for evaluating the efficacy and safety is composed of the low-dose maintenance period (10 mg/day), high-dose maintenance period (22.5 mg/day) and tapering period of the trial drug. Additionally, there is an open-labelled active drug extension period for evaluating long-term safety. Primary outcomes are safety and efficacy in cognitive and psychological function. Also, exploratory investigations for the efficacy of bromocriptine by neurological scores and biomarkers will be conducted.

ETHICS AND DISSEMINATION: The proposed trial is conducted according to the Declaration of Helsinki, and was approved by the Institutional Review Board (K070). The study results are expected to be disseminated at international or national conferences and published in international journals following the peer-review process.

TRIAL REGISTRATION NUMBER: jRCT2041200008, NCT04413344.

PMID:34193504 | DOI:10.1136/bmjopen-2021-051343

Sci Adv. 2021 Jun 30;7(27):eabh3032. doi: 10.1126/sciadv.abh3032. Print 2021 Jun.

ABSTRACT

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates the rapid development of new therapies against coronavirus disease 2019 (COVID-19) infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein network, based on disease signatures defined by COVID-19 multiomics datasets, and cross-examined these pathways against approved drugs. This analysis identified 200 drugs predicted to target SARS-CoV-2-induced pathways, 40 of which are already in COVID-19 clinical trials, testifying to the validity of the approach. Using artificial neural network analysis, we classified these 200 drugs into nine distinct pathways, within two overarching mechanisms of action (MoAs): viral replication (126) and immune response (74). Two drugs (proguanil and sulfasalazine) implicated in viral replication were shown to inhibit replication in cell assays. This unbiased and validated analysis opens new avenues for the rapid repurposing of approved drugs into clinical trials.

PMID:34193418 | DOI:10.1126/sciadv.abh3032

Br J Clin Pharmacol. 2021 Jun 30. doi: 10.1111/bcp.14964. Online ahead of print.

ABSTRACT

Repurposing the large arsenal of existing non-cancer drugs is an attractive proposition to expand the clinical pipelines for cancer therapeutics. The earlier successes in repurposing resulted primarily from serendipitous findings but more recently, drug or target-centric systematic identification of repurposing opportunities continues to rise. Kinases are one of the most sought-after cancer drug targets over the last three decades. There are many non-cancer approved drugs that can inhibit kinases as "off-targets" as well as many existing kinase inhibitors that can target new additional kinases in cancer. Identifying cancer-associated kinase inhibitors through mining commercial drug databases or new kinase targets for existing inhibitors through comprehensive kinome profiling can offer more effective trial-ready options to rapidly advance drugs for clinical validation. In this review, we argue that drug repurposing is an important approach in modern drug development for cancer therapeutics. We have summarized the advantages of repurposing, the rationale behind this approach together with key barriers and opportunities in cancer drug development. We have also included examples of non-cancer drugs that inhibit kinases or are associated with kinase signalling as a basis for their anti-cancer action.

PMID:34192364 | DOI:10.1111/bcp.14964

Brief Funct Genomics. 2021 Jun 29:elab031. doi: 10.1093/bfgp/elab031. Online ahead of print.

ABSTRACT

Drug-target interaction prediction is important for drug development and drug repurposing. Many computational methods have been proposed for drug-target interaction prediction due to their potential to the time and cost reduction. In this review, we introduce the molecular docking and machine learning-based methods, which have been widely applied to drug-target interaction prediction. Particularly, machine learning-based methods are divided into different types according to the data processing form and task type. For each type of method, we provide a specific description and propose some solutions to improve its capability. The knowledge of heterogeneous network and learning to rank are also summarized in this review. As far as we know, this is the first comprehensive review that summarizes the knowledge of heterogeneous network and learning to rank in the drug-target interaction prediction. Moreover, we propose three aspects that can be explored in depth for future research.

PMID:34189559 | DOI:10.1093/bfgp/elab031

Drug Des Devel Ther. 2021 Jun 22;15:2747-2767. doi: 10.2147/DDDT.S308973. eCollection 2021.

ABSTRACT

Drug repurposing is a feasible strategy in developing novel medications. Regarding the cancer field, scientists are continuously making efforts to redirect conventional drugs into cancer treatment. This approach aims at exploring new applications in the existing agents. Antiparasitic medications, including artemisinin derivatives (ARTs), quinine-related compounds, niclosamide, ivermectin, albendazole derivatives, nitazoxanide and pyrimethamine, have been deeply investigated and widely applied in treating various parasitic diseases for a long time. Generally, their pharmacokinetic and pharmacodynamic properties are well understood, while the side effects are roughly acceptable. Scientists noticed that some of these agents have anticancer potentials and explored the underlying mechanisms to achieve drug repurposing. Recent studies show that these agents inhibit cancer progression via multiple interesting ways, inducing ferroptosis induction, autophagy regulation, mitochondrial disturbance, immunoregulation, and metabolic disruption. In this review, we summarize the recent advancement in uncovering antiparasitic drugs' anticancer properties from the perspective of their pharmacological targets. Instead of paying attention to the previously discovered mechanisms, we focus more on newly emerging ones that are worth noticing. While most investigations are focusing on the mechanisms of their antiparasitic effect, more in vivo exploration in clinical trials in the future is necessary. Moreover, we also paid attention to what limits the clinical application of these agents. For some of these agents like ARTs and niclosamide, drug modification, novel delivery system invention, or drug combination are strongly recommended for future exploration.

PMID:34188451 | PMC:PMC8235938 | DOI:10.2147/DDDT.S308973

Sci Rep. 2021 Jun 29;11(1):13540. doi: 10.1038/s41598-021-92903-8.

ABSTRACT

Computational methods accelerate the drug repurposing pipelines that are a quicker and cost-effective alternative to discovering new molecules. However, there is a paucity of web servers to conduct fast, focussed, and customized investigations for identifying new uses of old drugs. We present the NOD web server, which has the mentioned characteristics. NOD uses a sensitive sequence-guided approach to identify close and distant homologs of a protein of interest. NOD then exploits this evolutionary information to suggest potential compounds from the DrugBank database that can be repurposed against the input protein. NOD also allows expansion of the chemical space of the potential candidates through similarity searches. We have validated the performance of NOD against available experimental and/or clinical reports. In 65.6% of the investigated cases in a control study, NOD is able to identify drugs more effectively than the searches made in DrugBank. NOD is freely-available at http://pauling.mbu.iisc.ac.in/NOD/NOD/ .

PMID:34188160 | DOI:10.1038/s41598-021-92903-8

Diabetes Metab Syndr. 2021 Jun 18;15(4):102180. doi: 10.1016/j.dsx.2021.06.017. Online ahead of print.

ABSTRACT

BACKGROUND AND AIM: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.

METHODS: Recent literature were studied and analyzed from various sources such as Scopus, PubMed, and IEEE Xplore databases.

RESULTS: Drugs like Niclosamideethanolamine, Methazolamide, Diacerein, Berberine, Clobetasol, etc. with possibility of repurposing to curb diabetes can be potential late-stage clinical candidates, providing access to information on pharmacology, formulation, and probable toxicity if any.

CONCLUSIONS: With collaboration of artificial intelligence (AI) with pharmacology, the efficiency of drug repurposing can improve significantly.

PMID:34186343 | DOI:10.1016/j.dsx.2021.06.017

Genet Med. 2021 Jun 28. doi: 10.1038/s41436-021-01243-5. Online ahead of print.

ABSTRACT

PURPOSE: It is critical to identify putative causal targets for SARS coronavirus 2, which may guide drug repurposing options to reduce the public health burden of COVID-19.

METHODS: We applied complementary methods and multiphased design to pinpoint the most likely causal genes for COVID-19 severity. First, we applied cross-methylome omnibus (CMO) test and leveraged data from the COVID-19 Host Genetics Initiative (HGI) comparing 9,986 hospitalized COVID-19 patients and 1,877,672 population controls. Second, we evaluated associations using the complementary S-PrediXcan method and leveraging blood and lung tissue gene expression prediction models. Third, we assessed associations of the identified genes with another COVID-19 phenotype, comparing very severe respiratory confirmed COVID versus population controls. Finally, we applied a fine-mapping method, fine-mapping of gene sets (FOGS), to prioritize putative causal genes.

RESULTS: Through analyses of the COVID-19 HGI using complementary CMO and S-PrediXcan methods along with fine-mapping, XCR1, CCR2, SACM1L, OAS3, NSF, WNT3, NAPSA, and IFNAR2 are identified as putative causal genes for COVID-19 severity.

CONCLUSION: We identified eight genes at five genomic loci as putative causal genes for COVID-19 severity.

PMID:34183789 | DOI:10.1038/s41436-021-01243-5

Biochim Biophys Acta Mol Cell Res. 2021 Jun 25:119087. doi: 10.1016/j.bbamcr.2021.119087. Online ahead of print.

ABSTRACT

Due to its potent anti-tumor activity, well-investigated pharmacokinetic properties and safety profile, disulfiram (DSF) has emerged as a promising candidate for drug repurposing in cancer therapy. Although several molecular mechanisms have been proposed for its anti-cancer effects, the precise underlying mechanisms remain unclear. In the present study, we showed that DSF inhibited proliferation of cancer cells by inducing reactive oxygen species (ROS) production, a G1 cell cycle arrest and autophagy. Moreover, DSF triggered apoptosis via suppression of the anti-apoptotic protein survivin. To elucidate the mechanisms for the anti-proliferative activities of DSF, we applied a 2-DE combined with MALDI-TOF-MS/MS analysis to identify differentially expressed proteins in breast cancer cells upon treatment with DSF. Nine differentially expressed proteins were identified among which, three candidates including calmodulin (CaM), peroxiredoxin 1 (PRDX1) and collagen type I alpha 1 (COL1A1) are involved in the regulation of the AKT signaling pathway. The results of western blot analysis confirmed that DSF inhibited p-AKT, suggesting that DSF induces its anti-tumor effects via AKT blockade. Moreover, we found that DSF increased the mRNA levels of FOXO1, FOXO3 and FOXO4, and upregulated the expression of their target genes involved in G1 cell cycle arrest, apoptosis and autophagy. Finally, DSF potentiated the anti-proliferative effects of well-known chemotherapeutic agents such as arsenic trioxide (ATO), doxorubicin, paclitaxel and cisplatin. Altogether, these findings provide mechanistic insights into the anti-growth activities of DSF.

PMID:34182011 | DOI:10.1016/j.bbamcr.2021.119087

Mol Divers. 2021 Jun 28. doi: 10.1007/s11030-021-10263-x. Online ahead of print.

ABSTRACT

Anterior Gradient 2 (AGR2) has recently been reported as a tumor biomarker in various cancers, i.e., breast, prostate and lung cancer. Predominantly, AGR2 exists as a homodimer via a dimerization domain (E60-K64); after it is self-dimerized, it helps FGF2 and VEGF to homo-dimerize and promotes the angiogenesis and the invasion of vascular endothelial cells and fibroblasts. Up till now, no small molecule has been discovered to inhibit the AGR2-AGR2 homodimer. Therefore, the present study was performed to prepare a validated 3D structure of AGR2 by homology modeling and discover a small molecule by screening the FDA-approved drugs library on AGR2 homodimer as a target protein. Thirteen different homology models of AGR2 were generated based on different templates which were narrowed down to 5 quality models sorted by their overall Z-scores. The top homology model based on PDB ID = 3PH9 was selected having the best Z-score and was further assessed by Verify-3D, ERRAT and RAMPAGE analysis. Structure-based virtual screening narrowed down the large library of FDA-approved drugs to ten potential AGR2-AGR2 homodimer inhibitors having FRED score lower than - 7.8 kcal/mol in which the top 5 drugs' binding stability was counter-validated by molecular dynamic simulation. To sum up, the present study prepared a validated 3D structure of AGR2 and, for the first time reported the discovery of 5 FDA-approved drugs to inhibit AGR2-AGR2 homodimer by using structure-based virtual screening. Moreover, the binding of the top 5 hits with AGR2 was also validated by molecular dynamic simulation. A validated 3D structure of Anterior Gradient 2 (AGR2) was prepared by homology modeling, which was used in virtual screening of FDA-approved drugs library for the discovery of prospective inhibitors of AGR2-AGR2 homodimer.

PMID:34181147 | DOI:10.1007/s11030-021-10263-x

Bioinformatics. 2021 Jun 28:btab473. doi: 10.1093/bioinformatics/btab473. Online ahead of print.

ABSTRACT

MOTIVATION: Predicting new drug-target interactions is an important step in new drug development, understanding of its side effects, and drug repositioning. Heterogeneous data sources can provide comprehensive information and different perspectives for drug-target interaction prediction. Thus, there have been many calculation methods relying on heterogeneous networks. Most of them use graph-related algorithms to characterize nodes in heterogeneous networks for predicting new DTI. However, these methods can only make predictions in known heterogeneous network datasets, and cannot support the prediction of new chemical entities outside the heterogeneous network, which hinder further drug discovery and development.

RESULTS: To solve this problem, we proposed a multi-modal DTI prediction model named 'MultiDTI' which uses our proposed joint learning framework based on heterogeneous networks. It combines the interaction or association information of the heterogeneous network and the drug/target sequence information, and maps the drugs, targets, side effects and disease nodes in the heterogeneous network into a common space. In this way, 'MultiDTI' can map the new chemical entity to this learned common space based on the chemical structure of the new entity. That is, bridging the gap between new chemical entities and known heterogeneous network. Our model has strong predictive performance, and the area under the receiver operating characteristic curve(AUC) of the model is 0.961 and the area under the precision recall curve (AUPRC) is 0.947 with 10-fold cross validation. In addition, some predicted new DTIs have been confirmed by ChEMBL database. Our results indicate that 'MultiDTI' is a powerful and practical tool for predicting new DTI, which can promote the development of drug discovery or drug repositioning.

AVAILABILITY: Python codes and dataset are available at https://github.com/Deshan-Zhou/MultiDTI/.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34180970 | DOI:10.1093/bioinformatics/btab473

Adv Ther (Weinh). 2021 May 20:2100055. doi: 10.1002/adtp.202100055. Online ahead of print.

ABSTRACT

Identifying effective drug treatments for COVID-19 is essential to reduce morbidity and mortality. Although a number of existing drugs have been proposed as potential COVID-19 treatments, effective data platforms and algorithms to prioritize drug candidates for evaluation and application of knowledge graph for drug repurposing have not been adequately explored. A COVID-19 knowledge graph by integrating 14 public bioinformatic databases containing information on drugs, genes, proteins, viruses, diseases, symptoms and their linkages is developed. An algorithm is developed to extract hidden linkages connecting drugs and COVID-19 from the knowledge graph, to generate and rank proposed drug candidates for repurposing as treatments for COVID-19 by integrating three scores for each drug: motif scores, knowledge graph PageRank scores, and knowledge graph embedding scores. The knowledge graph contains over 48 000 nodes and 13 37 000 edges, including 13 563 molecules in the DrugBank database. From the 5624 molecules identified by the motif-discovery algorithms, ranking results show that 112 drug molecules had the top 2% scores, of which 50 existing drugs with other indications approved by health administrations reported. The proposed drug candidates serve to generate hypotheses for future evaluation in clinical trials and observational studies.

PMID:34179346 | PMC:PMC8212091 | DOI:10.1002/adtp.202100055

Front Oncol. 2021 Jun 11;11:678966. doi: 10.3389/fonc.2021.678966. eCollection 2021.

ABSTRACT

While genetic alterations in Epidermal growth factor receptor (EGFR) and PI3K are common in head and neck squamous cell carcinomas (HNSCC), their impact on oncogenic signaling and cancer drug sensitivities remains elusive. To determine their consequences on the transcriptional network, pathway activities of EGFR, PI3K, and 12 additional oncogenic pathways were inferred in 498 HNSCC samples of The Cancer Genome Atlas using PROGENy. More than half of HPV-negative HNSCC showed a pathway activation in EGFR or PI3K. An amplification in EGFR and a mutation in PI3KCA resulted in a significantly higher activity of the respective pathway (p = 0.017 and p = 0.007). Interestingly, both pathway activations could only be explained by genetic alterations in less than 25% of cases indicating additional molecular events involved in the downstream signaling. Suitable in vitro pathway models could be identified in a published drug screen of 45 HPV-negative HNSCC cell lines. An active EGFR pathway was predictive for the response to the PI3K inhibitor buparlisib (p = 6.36E-03) and an inactive EGFR and PI3K pathway was associated with efficacy of the B-cell lymphoma (BCL) inhibitor navitoclax (p = 9.26E-03). In addition, an inactive PI3K pathway correlated with a response to multiple Histone deacetylase inhibitor (HDAC) inhibitors. These findings require validation in preclinical models and clinical studies.

PMID:34178665 | PMC:PMC8226088 | DOI:10.3389/fonc.2021.678966

Rev Med Interne. 2021 Jun 24:S0248-8663(21)00524-5. doi: 10.1016/j.revmed.2021.06.005. Online ahead of print.

ABSTRACT

Direct oral anticoagulants recently became the first-line choice for anticoagulation in venous thromboembolic disease. Many studies have shown its non-inferiority regarding the risk of thromboembolic recurrence compared to anti-vitamin K without increasing the risk of bleeding in the general population. However, specific populations such as patients with cancer, patients with kidney failure, patients with constitutional thrombophilia, elderly patients, or patients with extreme weight are at risk of intolerance to the use of direct oral anticoagulants. Precautions in use may be necessary as discussed in recently published guidelines about antiphospholipid syndrome. This review aims to list the main clinical trials investigating direct oral anticoagulants in venous thromboembolic disease in the general population and populations at risk, as well as to provide an update on current international and French guidelines.

PMID:34176700 | DOI:10.1016/j.revmed.2021.06.005

Pharmacol Ther. 2021 Jun 23:107930. doi: 10.1016/j.pharmthera.2021.107930. Online ahead of print.

ABSTRACT

Traditional drug development and discovery has not kept pace with threats from emerging and re-emerging diseases such as Ebola virus, MERS-CoV and more recently, SARS-CoV-2. Among other reasons, the exorbitant costs, high attrition rate and extensive periods of time from research to market approval are the primary contributing factors to the lag in recent traditional drug developmental activities. Due to these reasons, drug developers are starting to consider drug repurposing (or repositioning) as a viable alternative to the more traditional drug development process. Drug repurposing aims to find alternative uses of an approved or investigational drug outside of its original indication. The key advantages of this approach are that there is less developmental risk, and it is less time-consuming since the safety and pharmacological profile of the repurposed drug is already established. To that end, various approaches to drug repurposing are employed. Computational approaches make use of machine learning and algorithms to model disease and drug interaction, while experimental approaches involve a more traditional wet-lab experiments. This review would discuss in detail various ongoing drug repurposing strategies and approaches to combat the current COVID-19 pandemic, along with the advantages and the potential challenges.

PMID:34174275 | DOI:10.1016/j.pharmthera.2021.107930

Future Med Chem. 2021 Jun 25. doi: 10.4155/fmc-2021-0025. Online ahead of print.

ABSTRACT

Background: The new coronavirus pandemic has had a significant impact worldwide, and therapeutic treatment for this viral infection is being strongly pursued. Efforts have been undertaken by medicinal chemists to discover molecules or known drugs that may be effective in COVID-19 treatment - in particular, targeting the main protease (Mpro) of the virus. Materials & methods: We have employed an innovative strategy - application of ligand- and structure-based virtual screening - using a special compilation of an approved and diverse set of SARS-CoV-2 crystallographic complexes that was recently published. Results and conclusion: We identified seven drugs with different original indications that might act as potential Mpro inhibitors and may be preferable to other drugs that have been repurposed. These drugs will be experimentally tested to confirm their potential Mpro inhibition and thus their effectiveness against COVID-19.

PMID:34169729 | DOI:10.4155/fmc-2021-0025

Proteins. 2021 Jun 24. doi: 10.1002/prot.26164. Online ahead of print.

ABSTRACT

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has serious negative effects on health, social life, and economics. Recently, vaccines from various companies have been urgently approved to control SARS-CoV-2 infections. However, any specific antiviral drug has not been confirmed so far for regular treatment. An important target is the main protease (Mpro ), which plays a major role in replication of the virus. In this study, Gaussian and residue network models are employed to reveal two distinct potential allosteric sites on Mpro that can be evaluated as drug targets besides the active site. Then, FDA-approved drugs are docked to three distinct sites with flexible docking using AutoDock Vina to identify potential drug candidates. 14 best molecule hits for the active site of Mpro are determined. 6 of these also exhibit high docking scores for the potential allosteric regions. Full-atom molecular dynamics simulations with MM-GBSA method indicate that compounds docked to active and potential allosteric sites form stable interactions with high binding free energy (∆Gbind ) values. ∆Gbind values reach -52.06 kcal/mol for the active site, -51.08 kcal/mol for the potential allosteric site 1, and - 42.93 kcal/mol for the potential allosteric site 2. Energy decomposition calculations per residue elucidate key binding residues stabilizing the ligands that can further serve to design pharmacophores. This systematic and efficient computational analysis successfully determines ivermectine, diosmin and selinexor currently subjected to clinical trials, and further proposes bromocriptine, elbasvir as Mpro inhibitor candidates to be evaluated against SARS-CoV-2 infections. This article is protected by copyright. All rights reserved.

PMID:34169568 | DOI:10.1002/prot.26164

Sci Rep. 2021 Jun 24;11(1):13208. doi: 10.1038/s41598-021-92416-4.

ABSTRACT

Effective agents to treat coronavirus infection are urgently required, not only to treat COVID-19, but to prepare for future outbreaks. Repurposed anti-virals such as remdesivir and human anti-inflammatories such as barcitinib have received emergency approval but their overall benefits remain unclear. Vaccines are the most promising prospect for COVID-19, but will need to be redeveloped for any future coronavirus outbreak. Protecting against future outbreaks requires the identification of targets that are conserved between coronavirus strains and amenable to drug discovery. Two such targets are the main protease (Mpro) and the papain-like protease (PLpro) which are essential for the coronavirus replication cycle. We describe the discovery of two non-antiviral therapeutic agents, the caspase-1 inhibitor SDZ 224015 and Tarloxotinib that target Mpro and PLpro, respectively. These were identified through extensive experimental screens of the drug repurposing ReFRAME library of 12,000 therapeutic agents. The caspase-1 inhibitor SDZ 224015, was found to be a potent irreversible inhibitor of Mpro (IC50 30 nM) while Tarloxotinib, a clinical stage epidermal growth factor receptor inhibitor, is a sub micromolar inhibitor of PLpro (IC50 300 nM, Ki 200 nM) and is the first reported PLpro inhibitor with drug-like properties. SDZ 224015 and Tarloxotinib have both undergone safety evaluation in humans and hence are candidates for COVID-19 clinical evaluation.

PMID:34168183 | DOI:10.1038/s41598-021-92416-4

Int J Antimicrob Agents. 2021 Jun 21:106380. doi: 10.1016/j.ijantimicag.2021.106380. Online ahead of print.

ABSTRACT

The global spread of microbial resistance coupled with high costs and slow pace in the discovery of a new antibiotic have made drug repositioning an attractive and promising alternative in the treatment of infections caused by multidrug resistant (MDR) microorganisms. The reuse involves the production of compounds with lower costs and development time, using diversified production technologies. The present systematic review aimed to present a selection of studies published in the last 20 years, which report the antimicrobial activity of non-antibiotic drugs that are candidates for repositioning, which could be used against the current microbial multidrug resistance. A search was performed in the PubMed, SciELO and Google Scholar databases using the following search strategies: [(drug repurposing) OR (drug repositioning) OR (repositioning) AND (non-antibiotic) AND (antibacterial activity) AND (antimicrobial activity)]. Overall, 112 articles were included, which explored the antimicrobial activity in antidepressants, antihypertensives, anti-inflammatories, antineoplastics, hypoglycemic agents, among other drugs. It was concluded that they have significant antimicrobial activity in vitro and in vivo, against standard strain and clinical isolates (Gram-negative and Gram-positive) and fungi. When associated with antibacterials, most of these drugs had their antibacterial activity enhanced. It was also a consensus of the studies included in this review that the presence of aromatic rings in the molecular structure contributes to antimicrobial activity. This review highlights the potential repositioning of several classes of non-antibiotic drugs as promising candidates for repositioning in the treatment of severe bacterial infections of MDR bacteria, extensively resistant (XDR) and pan-resistant (PDR) to drugs.

PMID:34166776 | DOI:10.1016/j.ijantimicag.2021.106380