Front Chem. 2021 Feb 4;8:624163. doi: 10.3389/fchem.2020.624163. eCollection 2020.

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with very limited treatments so far. Demonstrated with good druggability, two major proteases of SARS-CoV-2, namely main protease (Mpro) and papain-like protease (PLpro) that are essential for viral maturation, have become the targets for many newly designed inhibitors. Unlike Mpro that has been heavily investigated, PLpro is not well-studied so far. Here, we carried out the in silico high-throughput screening of all FDA-approved drugs via the flexible docking simulation for potential inhibitors of PLpro and explored the molecular mechanism of binding between a known inhibitor rac5c and PLpro. Our results, from molecular dynamics simulation, show that the chances of drug repurposing for PLpro might be low. On the other hand, our long (about 450 ns) MD simulation confirms that rac5c can be bound stably inside the substrate-binding site of PLpro and unveils the molecular mechanism of binding for the rac5c-PLpro complex. The latter may help perform further structural optimization and design potent leads for inhibiting PLpro.

PMID:33614597 | PMC:PMC7889802 | DOI:10.3389/fchem.2020.624163

Front Oncol. 2021 Feb 3;10:604948. doi: 10.3389/fonc.2020.604948. eCollection 2020.

ABSTRACT

Due to the high resistance that cancer has shown to conventional therapies, it is difficult to treat this disease, particularly in advanced stages. In recent decades, treatments have been improved, being more specific according to the characteristics of the tumor, becoming more effective, less toxic, and invasive. Cancer can be treated by the combination of surgery, radiation therapy, and/or drug administration, but therapies based on anticancer drugs are the main cancer treatment. Cancer drug development requires long-time preclinical and clinical studies and is not cost-effective. Drug repurposing is an alternative for cancer therapies development since it is faster, safer, easier, cheaper, and repurposed drugs do not have serious side effects. However, cancer is a complex, heterogeneous, and highly dynamic disease with multiple evolving molecular constituents. This tumor heterogeneity causes several resistance mechanisms in cancer therapies, mainly the target mutation. The CRISPR-dCas9-based artificial transcription factors (ATFs) could be used in cancer therapy due to their possibility to manipulate DNA to modify target genes, activate tumor suppressor genes, silence oncogenes, and tumor resistance mechanisms for targeted therapy. In addition, drug repurposing combined with the use of CRISPR-dCas9-based ATFs could be an alternative cancer treatment to reduce cancer mortality. The aim of this review is to describe the potential of the repurposed drugs combined with CRISPR-dCas9-based ATFs to improve the efficacy of cancer treatment, discussing the possible advantages and disadvantages.

PMID:33614489 | PMC:PMC7887379 | DOI:10.3389/fonc.2020.604948

Front Microbiol. 2021 Feb 4;12:633467. doi: 10.3389/fmicb.2021.633467. eCollection 2021.

ABSTRACT

Serious infections caused by multidrug-resistant Staphylococcus aureus clearly urge the development of new antimicrobial agents. Drug repositioning has emerged as an alternative approach that enables us to rapidly identify effective drugs. We first reported a guanidine compound, isopropoxy benzene guanidine, had potent antibacterial activity against S. aureus. Unlike conventional antibiotics, repeated use of isopropoxy benzene guanidine had a lower probability of resistance section. We found that isopropoxy benzene guanidine triggered membrane damage by disrupting the cell membrane potential and cytoplasmic membrane integrity. Furthermore, we demonstrated that isopropoxy benzene guanidine is capable of treating invasive MRSA infections in vivo studies. These findings provided strong evidence that isopropoxy benzene guanidine represents a new chemical lead for novel antibacterial agent against multidrug-resistant S. aureus infections.

PMID:33613506 | PMC:PMC7890237 | DOI:10.3389/fmicb.2021.633467

Drug Discov Ther. 2021 Feb 19. doi: 10.5582/ddt.2021.01005. Online ahead of print.

ABSTRACT

An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which began in Wuhan, China in December 2019, has rapidly spread all over the world. The World Health Organization characterized the disease caused by SARS-CoV-2 (COVID-19) as a pandemic in March 2020. In the absence of specific treatments for the virus, treatment options are being examined. Drug repurposing is a process of identifying new therapeutic uses for approved drugs. It is an effective strategy to discover drug molecules with new therapeutic indications. This strategy is time-saving, low-cost, and has a minimal risk of failure. Several existing approved drugs such as chloroquine, hydroxychloroquine, doxycycline, azithromycin, and ivermectin are currently in use because of their efficacy in inhibiting COVID-19. Multidrug therapy, such as a combination of hydroxychloroquine and azithromycin, a combination of doxycycline and ivermectin, or a combination of ivermectin, doxycycline, and azithromycin, has been successfully administered. Multidrug therapy is efficacious because the mechanisms of action of these drugs differ. Moreover, multidrug therapy may prevent the emergence of drug-resistant SARS-CoV-2.

PMID:33612572 | DOI:10.5582/ddt.2021.01005

19 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2021/02/20

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

7 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2021/02/19

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Clin Transl Sci. 2021 Feb 19. doi: 10.1111/cts.13007. Online ahead of print.

ABSTRACT

The outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, leads to a global pandemic with high morbidity and mortality. Despite frenzied efforts in therapeutic development, there are currently no effective drugs for treatment, nor are there vaccines for its prevention. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, is one of the most practical treatment options against the outbreak. In this study, we present a novel strategy for in-silico molecular modeling screening for potential drugs that may interact with multiple main proteins of SARS-CoV-2. Targeting multiple viral proteins is a novel drug discovery concept in that it enables the potential drugs to act on different stages of the virus' life cycle, thereby potentially maximizing the drug potency. We screened 2,631 FDA-approved small molecules against four key proteins of SARS-CoV-2 that are known as attractive targets for anti-viral drug development. In total, we identified 29 drugs that could actively interact with two or more target proteins, with 5 drugs (Avapritinib, Bictegravir, Ziprasidone, Capmatinib and Pexidartinib) being common candidates for all four key host proteins and 3 of them possessing the desirable molecular properties. By overlaying docked positions of drug candidates onto individual host proteins, it has been further confirmed that the binding site conformations are conserved. The drugs identified in our screening provide potential guidance for experimental confirmation such as in vitro molecular assays, in vivo animal testing as well as incorporation into ongoing clinical studies.

PMID:33606912 | DOI:10.1111/cts.13007

PLoS One. 2021 Feb 19;16(2):e0246920. doi: 10.1371/journal.pone.0246920. eCollection 2021.

ABSTRACT

In-silico prediction of repurposable drugs is an effective drug discovery strategy that supplements de-nevo drug discovery from scratch. Reduced development time, less cost and absence of severe side effects are significant advantages of using drug repositioning. Most recent and most advanced artificial intelligence (AI) approaches have boosted drug repurposing in terms of throughput and accuracy enormously. However, with the growing number of drugs, targets and their massive interactions produce imbalanced data which may not be suitable as input to the classification model directly. Here, we have proposed DTI-SNNFRA, a framework for predicting drug-target interaction (DTI), based on shared nearest neighbour (SNN) and fuzzy-rough approximation (FRA). It uses sampling techniques to collectively reduce the vast search space covering the available drugs, targets and millions of interactions between them. DTI-SNNFRA operates in two stages: first, it uses SNN followed by a partitioning clustering for sampling the search space. Next, it computes the degree of fuzzy-rough approximations and proper degree threshold selection for the negative samples' undersampling from all possible interaction pairs between drugs and targets obtained in the first stage. Finally, classification is performed using the positive and selected negative samples. We have evaluated the efficacy of DTI-SNNFRA using AUC (Area under ROC Curve), Geometric Mean, and F1 Score. The model performs exceptionally well with a high prediction score of 0.95 for ROC-AUC. The predicted drug-target interactions are validated through an existing drug-target database (Connectivity Map (Cmap)).

PMID:33606741 | DOI:10.1371/journal.pone.0246920

Assay Drug Dev Technol. 2021 Feb 22. doi: 10.1089/adt.2020.1072. Online ahead of print.

NO ABSTRACT

PMID:33606552 | DOI:10.1089/adt.2020.1072

ACS Chem Neurosci. 2021 Feb 19. doi: 10.1021/acschemneuro.1c00019. Online ahead of print.

ABSTRACT

The COVID-19 pandemic caused by SARS-CoV-2 represents a global public health emergency. The entry of SARS-CoV-2 into host cells requires the activation of its spike protein by host cell proteases. The serine protease, TMPRSS2, and cysteine proteases, Cathepsins B/L, activate spike protein and enable SARS-CoV-2 entry to the host cell through two completely different and independent pathways. Therefore, inhibiting either TMPRSS2 or cathepsin B/L may not sufficiently block the virus entry. We here hypothesized that simultaneous targeting of both the entry pathways would be more efficient to block the virus entry rather than targeting the entry pathways individually. To this end, we utilized the network-based drug repurposing analyses to identify the possible common drugs that can target both the entry pathways. This study, for the first time, reports the molecules like cyclosporine, calcitriol, and estradiol as candidate drugs with the binding ability to the host proteases, TMPRSS2, and cathepsin B/L. Next, we analyzed drug-gene and gene-gene interaction networks using 332 human targets of SARS-CoV-2 proteins. The network results indicate that, out of 332 human proteins, cyclosporine interacts with 216 (65%) proteins. Furthermore, we performed molecular docking and all-atom molecular dynamics (MD) simulations to explore the binding of drug with TMPRSS2 and cathepsin L. The molecular docking and MD simulation results showed strong and stable binding of cyclosporine A (CsA) with TMPRSS2 and CTSL genes. The above results indicate cyclosporine as a potential drug molecule, as apart from interacting with SARS-CoV-2 entry receptors, it also interacts with most of SARS-CoV-2 target host genes; thus it could potentially interfere with functions of SARS-CoV-2 proteins in human cells. We here also suggest that these antiviral drugs alone or in combination can simultaneously target both the entry pathways and thus can be considered as a potential treatment option for COVID-19.

PMID:33606519 | DOI:10.1021/acschemneuro.1c00019

Comb Chem High Throughput Screen. 2021 Feb 18. doi: 10.2174/1386207324666210219102728. Online ahead of print.

ABSTRACT

INTRODUCTION: Drug repositioning aims to screen drugs and therapeutic goals from approved drugs and abandoned compounds that have been identified as safe. This trend is changing the landscape of drug development and creating a model of drug repositioning for new drug development. In recent decade, machine learning methods have been applied to predict the binding affinity of compound proteins, while deep learning is recently becoming hot and achieving significant performances. Among the models, the way of representing the compounds is usually simple, which is the molecular fingerprints, i.e., a single SMILES string.

METHODS: In this work, we improve it by proposing a novel representing manner, named SMILES#, to recode the SMILES string. This approach takes into account the properties of compounds and achieves well performance. After that, we propose a deep learning model that combines recurrent neural networks with a convolutional neural network with an attentional mechanism, using unlabeled data and labeled data to jointly encode molecular and predict binding affinity.

RESULTS: Experimental results show that SMILES# with compound properties can effectively improve the accuracy of the model and reduce the RMS error on most data sets.

CONCLUSION: Then, we used the method to verify the related and unrelated compounds with the same target, and the experimental results show the effectiveness of the method.

PMID:33605851 | DOI:10.2174/1386207324666210219102728

Assay Drug Dev Technol. 2021 Feb 19. doi: 10.1089/adt.2021.005. Online ahead of print.

NO ABSTRACT

PMID:33605782 | DOI:10.1089/adt.2021.005

J Proteome Res. 2021 Feb 19. doi: 10.1021/acs.jproteome.0c00929. Online ahead of print.

ABSTRACT

The SARS-CoV-2 virus is the causative agent of the 2020 pandemic leading to the COVID-19 respiratory disease. With many scientific and humanitarian efforts ongoing to develop diagnostic tests, vaccines, and treatments for COVID-19, and to prevent the spread of SARS-CoV-2, mass spectrometry research, including proteomics, is playing a role in determining the biology of this viral infection. Proteomics studies are starting to lead to an understanding of the roles of viral and host proteins during SARS-CoV-2 infection, their protein-protein interactions, and post-translational modifications. This is beginning to provide insights into potential therapeutic targets or diagnostic strategies that can be used to reduce the long-term burden of the pandemic. However, the extraordinary situation caused by the global pandemic is also highlighting the need to improve mass spectrometry data and workflow sharing. We therefore describe freely available data and computational resources that can facilitate and assist the mass spectrometry-based analysis of SARS-CoV-2. We exemplify this by reanalyzing a virus-host interactome data set to detect protein-protein interactions and identify host proteins that could potentially be used as targets for drug repurposing.

PMID:33605735 | DOI:10.1021/acs.jproteome.0c00929

Cancer Sci. 2021 Feb 19. doi: 10.1111/cas.14858. Online ahead of print.

ABSTRACT

Targeting mutated oncogenes is an effective approach for treating cancer. The four main driver genes of pancreatic ductal adenocarcinoma (PDAC) are KRAS,TP53,CDKN2A, and SMAD4, collectively called the "big 4" of PDAC. However, they remain challenging therapeutic targets. In this study, ArfGAP with SH3 domain, ankyrin repeat and PH domain 2 (ASAP2), one of the ArfGAP family, was identified as a novel driver gene in PDAC. Clinical analysis with PDAC datasets showed that ASAP2 was overexpressed in PDAC cells based on increased DNA copy numbers, and high ASAP2 expression contributed to poor prognosis in PDAC. Next, the biological roles of ASAP2 were investigated using ASAP2-knockout PDAC cells generated with CRISPR-Cas9 technology or transfected PDAC cells. In vitro and in vivo analyses showed that ASAP2 promoted tumor growth by facilitating cell cycle progression through phosphorylation of EGFR. Finally, a repositioned drug targeting the ASAP2 pathway was identified using a bioinformatics approach. The gene perturbation correlation method showed that niclosamide, an antiparasitic drug, suppressed PDAC growth by inhibition of ASAP2 expression. These data show that ASAP2 is a novel druggable driver gene that activates the EGFR signaling pathway. Furthermore, niclosamide was identified as a repositioned therapeutic agent for PDAC possibly targeting ASAP2.

PMID:33605496 | DOI:10.1111/cas.14858

Neurooncol Adv. 2020 Nov 16;3(1):vdaa153. doi: 10.1093/noajnl/vdaa153. eCollection 2021 Jan-Dec.

ABSTRACT

Neurofibromatosis type 2 (NF2) is a rare autosomal dominant disorder characterized by the development of multiple nervous system tumors due to mutation in the NF2 tumor suppressor gene. The hallmark feature of the NF2 syndrome is the development of bilateral vestibular schwannomas (VS). Although there is nearly 100% penetrance by 60 years of age, some patients suffer from a severe form of the disease and develop multiple tumors at an early age, while others are asymptomatic until later in life. Management options for VS include surgery, stereotactic radiation, and observation with serial imaging; however, currently, there are no FDA-approved pharmacotherapies for NF2 or VS. Recent advancements in the molecular biology underlying NF2 have led to a better understanding of the etiology and pathogenesis of VS. These novel signaling pathways may be used to identify targeted therapies for these tumors. This review discusses the clinical features and treatment options for sporadic- and NF2-associated VS, the diagnostic and screening criteria, completed and ongoing clinical trials, quality of life metrics, and opportunities for future research.

PMID:33604573 | PMC:PMC7881257 | DOI:10.1093/noajnl/vdaa153

6 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2021/02/18

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2021/02/17

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2021/02/17

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Indicator Regularized Non-Negative Matrix Factorization Method-Based Drug Repurposing for COVID-19.

Front Immunol. 2020;11:603615

Authors: Tang X, Cai L, Meng Y, Xu J, Lu C, Yang J

Abstract
A novel coronavirus, named COVID-19, has become one of the most prevalent and severe infectious diseases in human history. Currently, there are only very few vaccines and therapeutic drugs against COVID-19, and their efficacies are yet to be tested. Drug repurposing aims to explore new applications of approved drugs, which can significantly reduce time and cost compared with de novo drug discovery. In this study, we built a virus-drug dataset, which included 34 viruses, 210 drugs, and 437 confirmed related virus-drug pairs from existing literature. Besides, we developed an Indicator Regularized non-negative Matrix Factorization (IRNMF) method, which introduced the indicator matrix and Karush-Kuhn-Tucker condition into the non-negative matrix factorization algorithm. According to the 5-fold cross-validation on the virus-drug dataset, the performance of IRNMF was better than other methods, and its Area Under receiver operating characteristic Curve (AUC) value was 0.8127. Additionally, we analyzed the case on COVID-19 infection, and our results suggested that the IRNMF algorithm could prioritize unknown virus-drug associations.

PMID: 33584672 [PubMed - in process]

Pandemics Throughout History.

Front Microbiol. 2020;11:631736

Authors: Piret J, Boivin G

Abstract
The emergence and spread of infectious diseases with pandemic potential occurred regularly throughout history. Major pandemics and epidemics such as plague, cholera, flu, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) have already afflicted humanity. The world is now facing the new coronavirus disease 2019 (COVID-19) pandemic. Many infectious diseases leading to pandemics are caused by zoonotic pathogens that were transmitted to humans due to increased contacts with animals through breeding, hunting and global trade activities. The understanding of the mechanisms of transmission of pathogens to humans allowed the establishment of methods to prevent and control infections. During centuries, implementation of public health measures such as isolation, quarantine and border control helped to contain the spread of infectious diseases and maintain the structure of the society. In the absence of pharmaceutical interventions, these containment methods have still been used nowadays to control COVID-19 pandemic. Global surveillance programs of water-borne pathogens, vector-borne diseases and zoonotic spillovers at the animal-human interface are of prime importance to rapidly detect the emergence of infectious threats. Novel technologies for rapid diagnostic testing, contact tracing, drug repurposing, biomarkers of disease severity as well as new platforms for the development and production of vaccines are needed for an effective response in case of pandemics.

PMID: 33584597 [PubMed]