Front Pharmacol. 2021 Nov 10;12:790952. doi: 10.3389/fphar.2021.790952. eCollection 2021.

NO ABSTRACT

PMID:34867425 | PMC:PMC8635986 | DOI:10.3389/fphar.2021.790952

Front Pharmacol. 2021 Nov 18;12:704205. doi: 10.3389/fphar.2021.704205. eCollection 2021.

ABSTRACT

SARS-CoV-2 has spread across the globe in no time. In the beginning, people suffered due to the absence of efficacious drugs required to treat severely ill patients. Nevertheless, still, there are no established therapeutic molecules against the SARS-CoV-2. Therefore, repurposing of the drugs started against SARS-CoV-2, due to which several drugs were approved for the treatment of COVID-19 patients. This paper reviewed the treatment regime for COVID-19 through drug repurposing from December 8, 2019 (the day when WHO recognized COVID-19 as a pandemic) until today. We have reviewed all the clinical trials from RECOVERY trials, ACTT-1 and ACTT-2 study group, and other major clinical trial platforms published in highly reputed journals such as NEJM, Lancet, etc. In addition to single-molecule therapy, several combination therapies were also evaluated to understand the treatment of COVID-19 from these significant clinical trials. To date, several lessons have been learned on the therapeutic outcomes for COVID-19. The paper also outlines the experiences gained during the repurposing of therapeutic molecules (hydroxychloroquine, ritonavir/ lopinavir, favipiravir, remdesivir, ivermectin, dexamethasone, camostatmesylate, and heparin), immunotherapeutic molecules (tocilizumab, mavrilimumab, baricitinib, and interferons), combination therapy, and convalescent plasma therapy to treat COVID-19 patients. We summarized that anti-viral therapeutic (remdesivir) and immunotherapeutic (tocilizumab, dexamethasone, and baricitinib) therapy showed some beneficial outcomes. Until March 2021, 4952 clinical trials have been registered in ClinicalTrials.gov toward the drug and vaccine development for COVID-19. More than 100 countries have participated in contributing to these clinical trials. Other than the registered clinical trials (medium to large-size), several small-size clinical trials have also been conducted from time to time to evaluate the treatment of COVID-19. Four molecules showed beneficial therapeutic to treat COVID-19 patients. The short-term repurposing of the existing drug may provide a successful outcome for COVID-19 patients. Therefore, more clinical trials can be initiated using potential anti-viral molecules by evaluating in different phases of clinical trials.

PMID:34867318 | PMC:PMC8636940 | DOI:10.3389/fphar.2021.704205

J Microbiol Biotechnol. 2021 Dec 1;32(1). doi: 10.4014/jmb.2110.10029. Online ahead of print.

ABSTRACT

Diagnostics, vaccines and drugs are indispensable tools and control measures in order to overcome infectious diseases such as coronavirus disease 2019 (COVID-19). Diagnostic tools based on RT-PCR were developed early in the COVID-19 pandemic, which were urgently required for quarantine (test, trace and isolation). Vaccines were also successfully developed using new platform technologies such as mRNA vaccines and virus-vectored vaccines within one year after identifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a causative agent of COVID-19. Drug development has been conducted in various ways including drug repurposing, convalescent plasma therapy, and monoclonal antibody development. Among all these efforts, COVID-19 drug development will be reviewed along with upcoming challenges.

PMID:34866128 | DOI:10.4014/jmb.2110.10029

Brief Bioinform. 2021 Dec 2:bbab490. doi: 10.1093/bib/bbab490. Online ahead of print.

ABSTRACT

To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

PMID:34864885 | DOI:10.1093/bib/bbab490

Bioinformatics. 2021 Dec 2:btab820. doi: 10.1093/bioinformatics/btab820. Online ahead of print.

ABSTRACT

MOTIVATION: Drug repositioning that aims to find new indications for existing drugs has been an efficient strategy for drug discovery. In the scenario where we only have confirmed disease-drug associations as positive pairs, a negative set of disease-drug pairs is usually constructed from the unknown disease-drug pairs in previous studies, where we do not know whether drugs and diseases can be associated, to train a model for disease-drug association prediction (drug repositioning). Drugs and diseases in these negative pairs can potentially be associated, but most studies have ignored them.

RESULTS: We present a method, springD2A, to capture the uncertainty in the negative pairs, and to discriminate between positive and unknown pairs because the former are more reliable. In springD2A, we introduce a spring-like penalty for the loss of negative pairs, which is strong if they are too close in a unit sphere, but mild if they are at a moderate distance. We also design a sequential sampling in which the probability of an unknown disease-drug pair sampled as negative is proportional to its score predicted as positive. Multiple models are learned during sequential sampling, and we adopt parameter- and feature-based ensemble schemes to boost performance. Experiments show springspringD2A is an effective tool for drug-repositioning.

AVAILABILITY: A python implementation of springD2A and datasets used in this study are available at https://github.com/wangyuanhao/springD2A.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34864881 | DOI:10.1093/bioinformatics/btab820

Brief Bioinform. 2021 Dec 2:bbab511. doi: 10.1093/bib/bbab511. Online ahead of print.

ABSTRACT

Drug repositioning is proposed to find novel usages for existing drugs. Among many types of drug repositioning approaches, predicting drug-drug interactions (DDIs) helps explore the pharmacological functions of drugs and achieves potential drugs for novel treatments. A number of models have been applied to predict DDIs. The DDI network, which is constructed from the known DDIs, is a common part in many of the existing methods. However, the functions of DDIs are different, and thus integrating them in a single DDI graph may overlook some useful information. We propose a graph convolutional network with multi-kernel (GCNMK) to predict potential DDIs. GCNMK adopts two DDI graph kernels for the graph convolutional layers, namely, increased DDI graph consisting of 'increase'-related DDIs and decreased DDI graph consisting of 'decrease'-related DDIs. The learned drug features are fed into a block with three fully connected layers for the DDI prediction. We compare various types of drug features, whereas the target feature of drugs outperforms all other types of features and their concatenated features. In comparison with three different DDI prediction methods, our proposed GCNMK achieves the best performance in terms of area under receiver operating characteristic curve and area under precision-recall curve. In case studies, we identify the top 20 potential DDIs from all unknown DDIs, and the top 10 potential DDIs from the unknown DDIs among breast, colorectal and lung neoplasms-related drugs. Most of them have evidence to support the existence of their interactions. fangxiang.wu@usask.ca.

PMID:34864856 | DOI:10.1093/bib/bbab511

Biomed Pharmacother. 2021 Dec 1:112375. doi: 10.1016/j.biopha.2021.112375. Online ahead of print.

ABSTRACT

Breast cancer (BC) is mostly observed in women and is responsible for huge mortality in women subjects globally. Due to the continued development of drug resistance and other contributing factors, the scientific community needs to look for new alternatives, and drug repurposing is one of the best opportunities. Here we light upon the drug repurposing with a major focus on breast cancer. BC is a division of cancer known as the leading cause of death of 2.3 million women globally, with 685,000 fatalities. This number is steadily rising, necessitating the development of a treatment that can extend survival time. All available treatments for BC are very costly as well as show side effects. This unfulfilled requirement of the anti-cancer drugs ignited an enthusiasm for drug repositioning, which means finding out the anti-cancer use of already marketed drugs for other complications. With the advancement in proteomics, genomics, and computational approaches, the drug repurposing process hastens. So many drugs are repurposed for the BC, including alkylating agents, antimetabolite, anthracyclines, an aromatase inhibitor, mTOR, and many more. The drug resistance in breast cancer is rising, so reviewing how the challenges in breast cancer can be combated with drug repurposing. This paper provides the updated information on all the repurposed drugs candidates for breast cancer with the molecular mechanism responsible for their anti-tumor activity. Additionally, all the challenges that occur during the repurposing of the drugs are discussed.

PMID:34863612 | DOI:10.1016/j.biopha.2021.112375

Sci Rep. 2021 Dec 2;11(1):23315. doi: 10.1038/s41598-021-02432-7.

ABSTRACT

The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of a range of human coronavirus diseases. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cell-based experimental assessment reveals several clinically-relevant drug repurposing candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.

PMID:34857794 | DOI:10.1038/s41598-021-02432-7

Nat Commun. 2021 Dec 2;12(1):7042. doi: 10.1038/s41467-021-27387-1.

ABSTRACT

Despite the increasing global burden of neurological disorders, there is a lack of effective diagnostic and therapeutic biomarkers. Proteins are often dysregulated in disease and have a strong genetic component. Here, we carry out a protein quantitative trait locus analysis of 184 neurologically-relevant proteins, using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In doing so, we elucidate the genetic landscape of the circulating proteome and its connection to neurological disorders. We detect 214 independently-associated variants for 107 proteins, the majority of which (76%) are cis-acting, including 114 variants that have not been previously identified. Using two-sample Mendelian randomisation, we identify causal associations between serum CD33 and Alzheimer's disease, GPNMB and Parkinson's disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting drug repurposing opportunities.

PMID:34857772 | DOI:10.1038/s41467-021-27387-1

Br J Pharmacol. 2021 Dec 2. doi: 10.1111/bph.15763. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: The zinc finger transcription factor Snail is aberrantly activated in many human cancers and strongly associated with poor prognosis. As a transcription factor, Snail has been traditionally considered an "undruggable" target. Here, we identified a potent small molecule inhibitor of Snail, namely trimethoprim, and investigated its potential antitumor effects and the underlying mechanisms.

EXPERIMENTAL APPROACH: The inhibitory action of trimethoprim on Snail protein and the related molecular mechanisms were revealed by molecular docking, biolayer interferometry, immunoblotting, immunoprecipitation, qRT-PCR, pull-down, and cycloheximide pulse-chase assays. The anti-proliferative and anti-metastatic effects of trimethoprim via targeting Snail were tested in multiple cell-based assays and animal models.

KEY RESULTS: This study identified trimethoprim, an antimicrobial drug, as a potent anti-tumor agent via targeting Snail. Molecular modeling analysis predicted that trimethoprim directly binds to the arginine-174 pocket of Snail protein. We further discovered that trimethoprim strongly interrupts the interaction of Snail with CREB-binding protein (CBP)/p300, which consequently suppresses Snail acetylation and promotes Snail degradation through ubiquitin-proteasome pathway. Furthermore, trimethoprim sufficiently inhibited the proliferation, epithelial-mesenchymal transition (EMT), and migration of cancer cells in vitro via specifically targeting Snail. More importantly, trimethoprim effectively reduced Snail-driven tumor growth and metastasis to vital organs such as lung, bone, and liver.

CONCLUSIONS AND IMPLICATIONS: These findings indicate, for the first time, that trimethoprim suppresses tumor growth and metastasis via targeting Snail. This study provides insights for a better understanding of the anticancer effects of trimethoprim and offers a potential anti-cancer therapeutic agent for clinical treatment.

PMID:34855201 | DOI:10.1111/bph.15763

J Drug Target. 2021 Dec 2:1-54. doi: 10.1080/1061186X.2021.2013852. Online ahead of print.

ABSTRACT

Covid- 19 is a clinical outcome of viral infection emerged due to strain of beta coronavirus which attacks the type-2 pneumocytes in alveoli via ACE2 receptors. There is no satisfactory drug therapeutic is developed against "SARS-CoV2", highlighting needs of an immediate necessity to give a thorough insight on using chemotherapeutic repurposing plan for the develop COVID-19 infected patients treatment. Drug repurposing is a method of selection of approved therapeutics for new use and is considered to be the most effective drug finding strategy since it includes less time and cost to obtain treatment compared to the no novo drug acquisition process. Several drugs such as hydroxychloroquine, remdesivir, teicoplanin, darunavir, ritonavir, nitoxazide, chloroquine, tocilizumab, and Favipiravir (FPV) showed their activity against "SARS-CoV2" in-vitro and clinical conditions. This review have emphasis on repurposing of drugs, and biologics used in clinical set up for targeting COVID-19 and to evaluate its pharmacokinetics, pharmacodynamics, and safety with their future aspect. The key benefit of drug repurposing is drug is the wealth of information related to its safety, and easy accessibility. Altogether allows for quick access to regulatory approval as well as sophisticated clinical studies.

PMID:34854327 | DOI:10.1080/1061186X.2021.2013852

Brief Bioinform. 2021 Nov 30:bbab467. doi: 10.1093/bib/bbab467. Online ahead of print.

ABSTRACT

MOTIVATION: The development process of a new drug is time-consuming and costly. Thus, identifying new uses for approved drugs, named drug repositioning, is helpful for speeding up the drug development process and reducing development costs. Existing drug-related disease prediction methods mainly focus on single or multiple drug-disease heterogeneous networks. However, heterogeneous networks, and drug subnets and disease subnet contained in heterogeneous networks cover the common topology information between drug and disease nodes, the specific information between drug nodes and the specific information between disease nodes, respectively.

RESULTS: We design a novel model, CTST, to extract and integrate common and specific topologies in multiple heterogeneous networks and subnets. Multiple heterogeneous networks composed of drug and disease nodes are established to integrate multiple kinds of similarities and associations among drug and disease nodes. These heterogeneous networks contain multiple drug subnets and a disease subnet. For multiple heterogeneous networks and subnets, we then define the common and specific representations of drug and disease nodes. The common representations of drug and disease nodes are encoded by a graph convolutional autoencoder with sharing parameters and they integrate the topological relationships of all nodes in heterogeneous networks. The specific representations of nodes are learned by specific graph convolutional autoencoders, respectively, and they fuse the topology and attributes of the nodes in each subnet. We then propose attention mechanisms at common representation level and specific representation level to learn more informative common and specific representations, respectively. Finally, an integration module with representation feature level attention is built to adaptively integrate these two representations for final association prediction. Extensive experimental results confirm the effectiveness of CTST. Comparison with six latest methods and case studies on five drugs further verify CTST has the ability to discover potential candidate diseases.

PMID:34850815 | DOI:10.1093/bib/bbab467

FEBS Open Bio. 2021 Nov 30. doi: 10.1002/2211-5463.13337. Online ahead of print.

ABSTRACT

Cepharanthine is a natural biscoclaurine alkaloid of plant origin and was recently demonstrated to have anti-SARS-CoV-2 activity. In this study, we evaluated whether natural analogues of cepharanthine may act as potential anti-COVID-19 drugs. A total of 24 compounds resembling cepharanthine were extracted from the KNApSAcK database and their binding affinities to target proteins, including the spike protein and main protease of SARS-CoV-2, NPC1 and TPC2 in humans, were predicted via molecular docking simulations. Selected analogues were further evaluated by a cell-based SARS-CoV-2 infection assay. Additionally, the efficacies of cepharanthine and its analogue tetrandrine were assessed. A comparison of the docking conformations of these compounds suggested that the diphenyl ester moiety of the molecules was a putative pharmacophore of the cepharanthine-analogues.

PMID:34850606 | DOI:10.1002/2211-5463.13337

Mol Oncol. 2021 Nov 30. doi: 10.1002/1878-0261.13144. Online ahead of print.

ABSTRACT

Patient-derived organoids are being considered as models that can help guide personalized therapy through in vitro anti-cancer drug response evaluation. However, attempts to quantify in vitro drug responses in organoids and compare them with responses in matched patients remain inadequate. In this study, we investigated whether drug responses of organoids correlate with clinical responses of matched patients and disease progression of patients. Organoids were established from 54 patients with colorectal cancer who (except for one patient) did not receive any form of therapy before, and tumor organoids were assessed through whole-exome sequencing. For comparisons of in vitro drug responses in matched patients, we developed an "organoid score" based on the variable anti-cancer treatment responses observed in organoids. Very interestingly, a higher organoid score was significantly correlated with a lower tumor regression rate after the standard-of-care treatment in matched patients. Additionally, we confirmed that patients with a higher organoid score (≥ 2.5) had poorer progression-free survival compared with those with a lower organoid score (< 2.5). Furthermore, to assess potential drug repurposing using an FDA-approved drug library, ten tumor organoids derived from patients with disease progression were applied to a simulation platform. Taken together, organoids and organoid scores can facilitate the prediction of anti-cancer therapy efficacy, and they can be used as a simulation model to determine the next therapeutic options through drug screening. Organoids will be an attractive platform to enable the implementation of personalized therapy for colorectal cancer patients.

PMID:34850547 | DOI:10.1002/1878-0261.13144

Med Res Rev. 2021 Dec 1. doi: 10.1002/med.21872. Online ahead of print.

ABSTRACT

Auranofin is an oral gold(I) compound, initially developed for the treatment of rheumatoid arthritis. Currently, Auranofin is under investigation for oncological application within a drug repurposing plan due to the relevant antineoplastic activity observed both in vitro and in vivo tumor models. In this review, we analysed studies in which Auranofin was used as a single drug or in combination with other molecules to enhance their anticancer activity or to overcome chemoresistance. The analysis of different targets/pathways affected by this drug in different cancer types has allowed us to highlight several interesting targets and effects of Auranofin besides the already well-known inhibition of thioredoxin reductase. Among these targets, inhibitory-κB kinase, deubiquitinates, protein kinase C iota have been frequently suggested. To rationalize the effects of Auranofin by a system biology-like approach, we exploited transcriptomic data obtained from a wide range of cell models, extrapolating the data deposited in the Connectivity Maps website and we attempted to provide a general conclusion and discussed the major points that need further investigation.

PMID:34850406 | DOI:10.1002/med.21872

Sci Rep. 2021 Nov 30;11(1):23179. doi: 10.1038/s41598-021-02353-5.

ABSTRACT

Since the 2019 novel coronavirus disease (COVID-19) outbreak in 2019 and the pandemic continues for more than one year, a vast amount of drug research has been conducted and few of them got FDA approval. Our objective is to prioritize repurposable drugs using a pipeline that systematically integrates the interaction between COVID-19 and drugs, deep graph neural networks, and in vitro/population-based validations. We first collected all available drugs (n = 3635) related to COVID-19 patient treatment through CTDbase. We built a COVID-19 knowledge graph based on the interactions among virus baits, host genes, pathways, drugs, and phenotypes. A deep graph neural network approach was used to derive the candidate drug's representation based on the biological interactions. We prioritized the candidate drugs using clinical trial history, and then validated them with their genetic profiles, in vitro experimental efficacy, and population-based treatment effect. We highlight the top 22 drugs including Azithromycin, Atorvastatin, Aspirin, Acetaminophen, and Albuterol. We further pinpointed drug combinations that may synergistically target COVID-19. In summary, we demonstrated that the integration of extensive interactions, deep neural networks, and multiple evidence can facilitate the rapid identification of candidate drugs for COVID-19 treatment.

PMID:34848761 | DOI:10.1038/s41598-021-02353-5

Anticancer Res. 2021 Dec;41(12):6061-6065. doi: 10.21873/anticanres.15425.

ABSTRACT

BACKGROUND/AIM: Antimony is a chemical element used in the therapy of parasitic diseases with a promising anticancer potential. The aim of this study was to evaluate in vitro activity of free or liposomal vesicle-packed antimony trioxide (AT or LAT) in the t(15;17)(q22;q21) translocation-positive acute promyelocytic leukemia (APL) cell line NB4.

MATERIALS AND METHODS: Cytotoxicity was analysed with trypan blue exclusion, the MTT assay and neutral red exclusion assay; cell proliferation with PicoGreen®; and reactive oxygen species (ROS) production with DCFDA.

RESULTS: Liposomal particles did not change the pH of the cell culture medium and entered the cells. Both formulations resulted in a time- and concentration-dependent cytotoxicity and production of ROS. LAT showed higher toxicity at lower concentrations compared to AT.

CONCLUSION: LAT may be used to decrease drug dosage and maintain high anti-tumoral effects on APL cells.

PMID:34848460 | DOI:10.21873/anticanres.15425

Anticancer Res. 2021 Dec;41(12):5913-5918. doi: 10.21873/anticanres.15410.

ABSTRACT

The safety windows and toxicity of clinically available known drugs allow drug repurposing to be a popular treatment strategy for several diseases, including cancers. Several common drugs, e.g., metformin, statin, and aspirin are on clinical trials for repurposing in oncology treatment. Most of repurposed drugs, however, cannot be used as single agents and some do not exert any clinically significant effects. The limitations and possible biases from observational studies and preclinical models to repurpose these drugs are debatable. In this article, the limitations and probability of using metformin, one of the most repurposed drugs for cancer treatment and in oncological practice, are discussed.

PMID:34848445 | DOI:10.21873/anticanres.15410

J Med Chem. 2021 Nov 30. doi: 10.1021/acs.jmedchem.1c01333. Online ahead of print.

ABSTRACT

Commonly used non-antibiotic drugs have been associated with changes in gut microbiome composition, paving the way for the possibility of repurposing FDA-approved molecules as next-generation microbiome therapeutics. Herein, we developed and validated an ex vivo high-throughput screening platform─the mini gut model─to underpin human gut microbiome response to molecular modulators. Ten FDA-approved compounds, selected based on maximum structural diversity of molecular fingerprints, were screened against the gut microbiome of five healthy subjects to characterize the ability of human-targeted drugs to modulate the human gut microbiome network. Three compounds, THIP hydrochloride, methenamine, and mesna, have shown promise as novel gut microbiome therapeutics in light of their capability of promoting health-associated features of the gut microbiome. Our findings provide a resource for future research on drug-microbiome interactions and lay the foundation for a new era of more precise gut microbiome modulation through drug repurposing, aimed at targeting specific dysbiotic events.

PMID:34846885 | DOI:10.1021/acs.jmedchem.1c01333

Environ Sci Pollut Res Int. 2021 Nov 30. doi: 10.1007/s11356-021-17824-5. Online ahead of print.

ABSTRACT

Vasoactive intestinal peptide (VIP) is a neuropeptide that is produced by the lymphoid cells and plays a major role in immunological functions for controlling the homeostasis of the immune system. VIP has been identified as a potent anti-inflammatory factor, in boosting both innate and adaptive immunity. Since December 2019, SARS-Cov-2 was found responsible for the disease COVID-19 which has spread worldwide. No specific therapies or 100% effective vaccines are yet available for the treatment of COVID-19. Drug repositioning may offer a strategy and several drugs have been repurposed, including lopinavir/ritonavir, remdesivir, favipiravir, and tocilizumab. This paper describes the main pharmacological properties of synthetic VIP drug (Aviptadil) which is now under clinical trials. A patented formulation of vasoactive intestinal polypeptide (VIP), named RLF-100 (Aviptadil), was developed and finally got approved for human trials by FDA in 2001 and in European medicines agency in 2005. It was awarded Orphan Drug Designation in 2001 by the US FDA for the treatment of acute respiratory distress syndrome and for the treatment of pulmonary arterial hypertension in 2005. Investigational new drug (IND) licenses for human trials of Aviptadil was guaranteed by both the US FDA and EMEA. Preliminary clinical trials seem to support Aviptadil's benefit. However, such drugs like Aviptadil in COVID-19 patients have peculiar safety profiles. Thus, adequate clinical trials are necessary for these compounds.

PMID:34846667 | DOI:10.1007/s11356-021-17824-5