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1.
Int J Mol Sci ; 22(24)2021 Dec 18.
Article in English | MEDLINE | ID: covidwho-1580690

ABSTRACT

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a potential antiviral drug.


Subject(s)
Benzamides/pharmacology , COVID-19/drug therapy , Indazoles/pharmacology , SARS-CoV-2/drug effects , Animals , Antiviral Agents/pharmacology , Benzamides/metabolism , COVID-19/metabolism , Cell Line , Chlorocebus aethiops , Drug Evaluation, Preclinical , Drug Repositioning/methods , Humans , Indazoles/metabolism , Lung/pathology , Lung/virology , Molecular Docking Simulation , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , Vero Cells , Virus Attachment/drug effects
2.
Molecules ; 26(24)2021 Dec 09.
Article in English | MEDLINE | ID: covidwho-1572566

ABSTRACT

This study demonstrates the inhibitory effect of 42 pyrimidonic pharmaceuticals (PPs) on the 3-chymotrypsin-like protease of SARS-CoV-2 (3CLpro) through molecular docking, molecular dynamics simulations, and free binding energies by means of molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) and molecular mechanics-generalized Born surface area (MM-GBSA). Of these tested PPs, 11 drugs approved by the US Food and Drug Administration showed an excellent binding affinity to the catalytic residues of 3CLpro of His41 and Cys145: uracil mustard, cytarabine, floxuridine, trifluridine, stavudine, lamivudine, zalcitabine, telbivudine, tipiracil, citicoline, and uridine triacetate. Their percentage of residues involved in binding at the active sites ranged from 56 to 100, and their binding affinities were in the range from -4.6 ± 0.14 to -7.0 ± 0.19 kcal/mol. The molecular dynamics as determined by a 200 ns simulation run of solvated docked complexes confirmed the stability of PP conformations that bound to the catalytic dyad and the active sites of 3CLpro. The free energy of binding also demonstrates the stability of the PP-3CLpro complexes. Citicoline and uridine triacetate showed free binding energies of -25.53 and -7.07 kcal/mol, respectively. Therefore, I recommend that they be repurposed for the fight against COVID-19, following proper experimental and clinical validation.


Subject(s)
COVID-19/drug therapy , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus Papain-Like Proteases/antagonists & inhibitors , Drug Repositioning/methods , Protease Inhibitors/pharmacology , SARS-CoV-2/drug effects , Acetates/chemistry , Acetates/pharmacology , Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Cytidine Diphosphate Choline/chemistry , Cytidine Diphosphate Choline/pharmacology , Drug Evaluation, Preclinical , Humans , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/chemistry , Uridine/analogs & derivatives , Uridine/chemistry , Uridine/pharmacology
3.
Future Microbiol ; 16: 1341-1370, 2021 11.
Article in English | MEDLINE | ID: covidwho-1555047

ABSTRACT

Since the beginning of the COVID-19 pandemic, large in silico screening studies and numerous in vitro studies have assessed the antiviral activity of various drugs on SARS-CoV-2. In the context of health emergency, drug repurposing represents the most relevant strategy because of the reduced time for approval by international medicines agencies, the low cost of development and the well-known toxicity profile of such drugs. Herein, we aim to review drugs with in vitro antiviral activity against SARS-CoV-2, combined with molecular docking data and results from preliminary clinical studies. Finally, when considering all these previous findings, as well as the possibility of oral administration, 11 molecules consisting of nelfinavir, favipiravir, azithromycin, clofoctol, clofazimine, ivermectin, nitazoxanide, amodiaquine, heparin, chloroquine and hydroxychloroquine, show an interesting antiviral activity that could be exploited as possible drug candidates for COVID-19 treatment.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/drug therapy , Middle East Respiratory Syndrome Coronavirus/drug effects , SARS-CoV-2/drug effects , Animals , COVID-19/virology , Cell Line , Chlorocebus aethiops , Drug Repositioning/methods , Humans , Molecular Docking Simulation , Pandemics/prevention & control , Vero Cells
4.
Biomolecules ; 11(12)2021 12 04.
Article in English | MEDLINE | ID: covidwho-1554985

ABSTRACT

Inflammation involves a complex biological response of the body tissues to damaging stimuli. When dysregulated, inflammation led by biomolecular mediators such as caspase-1 and tumor necrosis factor-alpha (TNF-alpha) can play a detrimental role in the progression of different medical conditions such as cancer, neurological disorders, autoimmune diseases, and cytokine storms caused by viral infections such as COVID-19. Computational approaches can accelerate the search for dual-target drugs able to simultaneously inhibit the aforementioned proteins, enabling the discovery of wide-spectrum anti-inflammatory agents. This work reports the first multicondition model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mtc-QSAR-MLP) for the virtual screening of agency-regulated chemicals as versatile anti-inflammatory therapeutics. The mtc-QSAR-MLP model displayed accuracy higher than 88%, and was interpreted from a physicochemical and structural point of view. When using the mtc-QSAR-MLP model as a virtual screening tool, we could identify several agency-regulated chemicals as dual inhibitors of caspase-1 and TNF-alpha, and the experimental information later retrieved from the scientific literature converged with our computational results. This study supports the capabilities of our mtc-QSAR-MLP model in anti-inflammatory therapy with direct applications to current health issues such as the COVID-19 pandemic.


Subject(s)
Anti-Inflammatory Agents/pharmacology , Caspase Inhibitors/pharmacology , Drug Repositioning/methods , Tumor Necrosis Factor-alpha/antagonists & inhibitors , Anti-Inflammatory Agents/chemistry , COVID-19/drug therapy , Caspase 1/metabolism , Caspase Inhibitors/chemistry , Humans , Inflammation/drug therapy , Molecular Docking Simulation , Quantitative Structure-Activity Relationship , Tumor Necrosis Factor-alpha/metabolism
5.
BMC Med Genomics ; 14(1): 226, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1542114

ABSTRACT

BACKGROUND: Higher mortality of COVID-19 patients with lung disease is a formidable challenge for the health care system. Genetic association between COVID-19 and various lung disorders must be understood to comprehend the molecular basis of comorbidity and accelerate drug development. METHODS: Lungs tissue-specific neighborhood network of human targets of SARS-CoV-2 was constructed. This network was integrated with lung diseases to build a disease-gene and disease-disease association network. Network-based toolset was used to identify the overlapping disease modules and drug targets. The functional protein modules were identified using community detection algorithms and biological processes, and pathway enrichment analysis. RESULTS: In total, 141 lung diseases were linked to a neighborhood network of SARS-CoV-2 targets, and 59 lung diseases were found to be topologically overlapped with the COVID-19 module. Topological overlap with various lung disorders allows repurposing of drugs used for these disorders to hit the closely associated COVID-19 module. Further analysis showed that functional protein-protein interaction modules in the lungs, substantially hijacked by SARS-CoV-2, are connected to several lung disorders. FDA-approved targets in the hijacked protein modules were identified and that can be hit by exiting drugs to rescue these modules from virus possession. CONCLUSION: Lung diseases are clustered with COVID-19 in the same network vicinity, indicating the potential threat for patients with respiratory diseases after SARS-CoV-2 infection. Pathobiological similarities between lung diseases and COVID-19 and clinical evidence suggest that shared molecular features are the probable reason for comorbidity. Network-based drug repurposing approaches can be applied to improve the clinical conditions of COVID-19 patients.


Subject(s)
COVID-19/drug therapy , COVID-19/epidemiology , Drug Repositioning , Lung Diseases/epidemiology , Pandemics , SARS-CoV-2 , Algorithms , Antiviral Agents/therapeutic use , COVID-19/genetics , Comorbidity , Drug Discovery , Drug Repositioning/methods , Gene Regulatory Networks/drug effects , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Humans , Lung Diseases/drug therapy , Lung Diseases/genetics , Protein Interaction Maps/drug effects , Protein Interaction Maps/genetics , Systems Biology
6.
Sci Rep ; 11(1): 20687, 2021 10 19.
Article in English | MEDLINE | ID: covidwho-1475486

ABSTRACT

This analysis presents a systematic evaluation of the extent of therapeutic opportunities that can be obtained from drug repurposing by connecting drug targets with disease genes. When using FDA-approved indications as a reference level we found that drug repurposing can offer an average of an 11-fold increase in disease coverage, with the maximum number of diseases covered per drug being increased from 134 to 167 after extending the drug targets with their high confidence first neighbors. Additionally, by network analysis to connect drugs to disease modules we found that drugs on average target 4 disease modules, yet the similarity between disease modules targeted by the same drug is generally low and the maximum number of disease modules targeted per drug increases from 158 to 229 when drug targets are neighbor-extended. Moreover, our results highlight that drug repurposing is more dependent on target proteins being shared between diseases than on polypharmacological properties of drugs. We apply our drug repurposing and network module analysis to COVID-19 and show that Fostamatinib is the drug with the highest module coverage.


Subject(s)
COVID-19/drug therapy , Drug Repositioning/methods , Gene Regulatory Networks/drug effects , Protein Interaction Maps/genetics , SARS-CoV-2 , Antiviral Agents/pharmacology , Bayes Theorem , Computational Biology/methods , Drug Delivery Systems , Drug Discovery , Humans , Polypharmacology , Protein Interaction Mapping , United States , United States Food and Drug Administration
7.
Sci Rep ; 11(1): 19839, 2021 10 06.
Article in English | MEDLINE | ID: covidwho-1454816

ABSTRACT

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


Subject(s)
Antineoplastic Agents/pharmacology , COVID-19/drug therapy , Drug Repositioning/methods , Neoplasms/drug therapy , Antiviral Agents , COVID-19/genetics , COVID-19/metabolism , COVID-19/virology , Computational Biology/methods , Databases, Genetic , Databases, Pharmaceutical , Gene Regulatory Networks , Humans , Neoplasms/genetics , Neoplasms/metabolism , Neoplasms/virology , SARS-CoV-2/isolation & purification
8.
Mayo Clin Proc ; 95(6): 1213-1221, 2020 06.
Article in English | MEDLINE | ID: covidwho-1450185

ABSTRACT

As the coronavirus disease 19 (COVID-19) global pandemic rages across the globe, the race to prevent and treat this deadly disease has led to the "off-label" repurposing of drugs such as hydroxychloroquine and lopinavir/ritonavir, which have the potential for unwanted QT-interval prolongation and a risk of drug-induced sudden cardiac death. With the possibility that a considerable proportion of the world's population soon could receive COVID-19 pharmacotherapies with torsadogenic potential for therapy or postexposure prophylaxis, this document serves to help health care professionals mitigate the risk of drug-induced ventricular arrhythmias while minimizing risk of COVID-19 exposure to personnel and conserving the limited supply of personal protective equipment.


Subject(s)
Death, Sudden, Cardiac , Hydroxychloroquine , Long QT Syndrome , Lopinavir , Risk Adjustment/methods , Ritonavir , Torsades de Pointes , Anti-Infective Agents/administration & dosage , Anti-Infective Agents/adverse effects , Betacoronavirus/drug effects , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/drug therapy , Coronavirus Infections/epidemiology , Death, Sudden, Cardiac/etiology , Death, Sudden, Cardiac/prevention & control , Drug Combinations , Drug Monitoring/methods , Drug Repositioning/ethics , Drug Repositioning/methods , Electrocardiography/methods , Humans , Hydroxychloroquine/administration & dosage , Hydroxychloroquine/adverse effects , Long QT Syndrome/chemically induced , Long QT Syndrome/mortality , Long QT Syndrome/therapy , Lopinavir/administration & dosage , Lopinavir/adverse effects , Pandemics , Pneumonia, Viral/drug therapy , Pneumonia, Viral/epidemiology , Ritonavir/administration & dosage , Ritonavir/adverse effects , SARS-CoV-2 , Torsades de Pointes/chemically induced , Torsades de Pointes/mortality , Torsades de Pointes/therapy
9.
PLoS One ; 16(9): e0257784, 2021.
Article in English | MEDLINE | ID: covidwho-1440991

ABSTRACT

Drug repurposing has the potential to bring existing de-risked drugs for effective intervention in an ongoing pandemic-COVID-19 that has infected over 131 million, with 2.8 million people succumbing to the illness globally (as of April 04, 2021). We have used a novel `gene signature'-based drug repositioning strategy by applying widely accepted gene ranking algorithms to prioritize the FDA approved or under trial drugs. We mined publically available RNA sequencing (RNA-Seq) data using CLC Genomics Workbench 20 (QIAGEN) and identified 283 differentially expressed genes (FDR<0.05, log2FC>1) after a meta-analysis of three independent studies which were based on severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection in primary human airway epithelial cells. Ingenuity Pathway Analysis (IPA) revealed that SARS-CoV-2 activated key canonical pathways and gene networks that intricately regulate general anti-viral as well as specific inflammatory pathways. Drug database, extracted from the Metacore and IPA, identified 15 drug targets (with information on COVID-19 pathogenesis) with 46 existing drugs as potential-novel candidates for repurposing for COVID-19 treatment. We found 35 novel drugs that inhibit targets (ALPL, CXCL8, and IL6) already in clinical trials for COVID-19. Also, we found 6 existing drugs against 4 potential anti-COVID-19 targets (CCL20, CSF3, CXCL1, CXCL10) that might have novel anti-COVID-19 indications. Finally, these drug targets were computationally prioritized based on gene ranking algorithms, which revealed CXCL10 as the common and strongest candidate with 2 existing drugs. Furthermore, the list of 283 SARS-CoV-2-associated proteins could be valuable not only as anti-COVID-19 targets but also useful for COVID-19 biomarker development.


Subject(s)
COVID-19/drug therapy , Drug Repositioning/methods , SARS-CoV-2/genetics , Antiviral Agents/therapeutic use , Drug Evaluation, Preclinical/methods , Epithelial Cells/drug effects , Epithelium/drug effects , Humans , Respiratory Mucosa/drug effects , Respiratory Mucosa/metabolism , Respiratory Mucosa/virology , Respiratory System/drug effects , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity
10.
Sci Rep ; 11(1): 18985, 2021 09 23.
Article in English | MEDLINE | ID: covidwho-1437690

ABSTRACT

The COVID-19 pandemic is raging. It revealed the importance of rapid scientific advancement towards understanding and treating new diseases. To address this challenge, we adapt an explainable artificial intelligence algorithm for data fusion and utilize it on new omics data on viral-host interactions, human protein interactions, and drugs to better understand SARS-CoV-2 infection mechanisms and predict new drug-target interactions for COVID-19. We discover that in the human interactome, the human proteins targeted by SARS-CoV-2 proteins and the genes that are differentially expressed after the infection have common neighbors central in the interactome that may be key to the disease mechanisms. We uncover 185 new drug-target interactions targeting 49 of these key genes and suggest re-purposing of 149 FDA-approved drugs, including drugs targeting VEGF and nitric oxide signaling, whose pathways coincide with the observed COVID-19 symptoms. Our integrative methodology is universal and can enable insight into this and other serious diseases.


Subject(s)
COVID-19/drug therapy , Drug Evaluation, Preclinical/methods , SARS-CoV-2/genetics , Antiviral Agents/therapeutic use , Artificial Intelligence , COVID-19/genetics , COVID-19/metabolism , Drug Repositioning/methods , Gene Regulatory Networks/genetics , Humans , Models, Theoretical , Pandemics , Pharmaceutical Preparations , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , Signal Transduction/genetics
11.
IEEE Trans Neural Netw Learn Syst ; 32(11): 4770-4780, 2021 11.
Article in English | MEDLINE | ID: covidwho-1429437

ABSTRACT

The coronavirus disease 2019 (COVID-19) has continued to spread worldwide since late 2019. To expedite the process of providing treatment to those who have contracted the disease and to ensure the accessibility of effective drugs, numerous strategies have been implemented to find potential anti-COVID-19 drugs in a short span of time. Motivated by this critical global challenge, in this review, we detail approaches that have been used for drug repurposing for COVID-19 and suggest improvements to the existing deep learning (DL) approach to identify and repurpose drugs to treat this complex disease. By optimizing hyperparameter settings, deploying suitable activation functions, and designing optimization algorithms, the improved DL approach will be able to perform feature extraction from quality big data, turning the traditional DL approach, referred to as a "black box," which generalizes and learns the transmitted data, into a "glass box" that will have the interpretability of its rationale while maintaining a high level of prediction accuracy. When adopted for drug repurposing for COVID-19, this improved approach will create a new generation of DL approaches that can establish a cause and effect relationship as to why the repurposed drugs are suitable for treating COVID-19. Its ability can also be extended to repurpose drugs for other complex diseases, develop appropriate treatment strategies for new diseases, and provide precision medical treatment to patients, thus paving the way to discover new drugs that can potentially be effective for treating COVID-19.


Subject(s)
COVID-19/drug therapy , Deep Learning/trends , Drug Repositioning/methods , Drug Repositioning/trends , Neural Networks, Computer , Antiviral Agents/administration & dosage , COVID-19/epidemiology , Drug Discovery/methods , Drug Discovery/trends , Humans
12.
Molecules ; 26(18)2021 Sep 16.
Article in English | MEDLINE | ID: covidwho-1410350

ABSTRACT

Drug repositioning is a successful approach in medicinal research. It significantly simplifies the long-term process of clinical drug evaluation, since the drug being tested has already been approved for another condition. One example of drug repositioning involves cardiac glycosides (CGs), which have, for a long time, been used in heart medicine. Moreover, it has been known for decades that CGs also have great potential in cancer treatment and, thus, many clinical trials now evaluate their anticancer potential. Interestingly, heart failure and cancer are not the only conditions for which CGs could be effectively used. In recent years, the antiviral potential of CGs has been extensively studied, and with the ongoing SARS-CoV-2 pandemic, this interest in CGs has increased even more. Therefore, here, we present CGs as potent and promising antiviral compounds, which can interfere with almost any steps of the viral life cycle, except for the viral attachment to a host cell. In this review article, we summarize the reported data on this hot topic and discuss the mechanisms of antiviral action of CGs, with reference to the particular viral life cycle phase they interfere with.


Subject(s)
Antiviral Agents/therapeutic use , Cardiac Glycosides/therapeutic use , Antiviral Agents/pharmacology , COVID-19 , Cardiac Glycosides/metabolism , Digitoxin , Digoxin , Drug Repositioning/methods , Heart Failure/drug therapy , Heart Failure/virology , Humans , Neoplasms/drug therapy , Ouabain , Pandemics , SARS-CoV-2 , Sodium-Potassium-Exchanging ATPase , Virus Internalization/drug effects , Virus Replication/drug effects
14.
Clin Pharmacol Ther ; 108(4): 775-790, 2020 10.
Article in English | MEDLINE | ID: covidwho-1384148

ABSTRACT

There is a rapidly expanding literature on the in vitro antiviral activity of drugs that may be repurposed for therapy or chemoprophylaxis against severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). However, this has not been accompanied by a comprehensive evaluation of the target plasma and lung concentrations of these drugs following approved dosing in humans. Accordingly, concentration 90% (EC90 ) values recalculated from in vitro anti-SARS-CoV-2 activity data was expressed as a ratio to the achievable maximum plasma concentration (Cmax ) at an approved dose in humans (Cmax /EC90 ratio). Only 14 of the 56 analyzed drugs achieved a Cmax /EC90 ratio above 1. A more in-depth assessment demonstrated that only nitazoxanide, nelfinavir, tipranavir (ritonavir-boosted), and sulfadoxine achieved plasma concentrations above their reported anti-SARS-CoV-2 activity across their entire approved dosing interval. An unbound lung to plasma tissue partition coefficient (Kp Ulung ) was also simulated to derive a lung Cmax /half-maximal effective concentration (EC50 ) as a better indicator of potential human efficacy. Hydroxychloroquine, chloroquine, mefloquine, atazanavir (ritonavir-boosted), tipranavir (ritonavir-boosted), ivermectin, azithromycin, and lopinavir (ritonavir-boosted) were all predicted to achieve lung concentrations over 10-fold higher than their reported EC50 . Nitazoxanide and sulfadoxine also exceeded their reported EC50 by 7.8-fold and 1.5-fold in lung, respectively. This analysis may be used to select potential candidates for further clinical testing, while deprioritizing compounds unlikely to attain target concentrations for antiviral activity. Future studies should focus on EC90 values and discuss findings in the context of achievable exposures in humans, especially within target compartments, such as the lungs, in order to maximize the potential for success of proposed human clinical trials.


Subject(s)
Antiviral Agents/administration & dosage , Betacoronavirus/drug effects , Coronavirus Infections/drug therapy , Drug Delivery Systems/methods , Drug Repositioning/methods , Pneumonia, Viral/drug therapy , Antiviral Agents/blood , COVID-19 , Coronavirus Infections/blood , Humans , Pandemics , Pneumonia, Viral/blood , SARS-CoV-2
15.
Proc Natl Acad Sci U S A ; 118(36)2021 09 07.
Article in English | MEDLINE | ID: covidwho-1366851

ABSTRACT

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10 to 15 y from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 US Food and Drug Administration (FDA)-approved compounds and clinical candidates, we identified 17 hits that inhibited SARS-CoV-2 infection and analyzed their antiviral activity across multiple cell lines, including lymph node carcinoma of the prostate (LNCaP) cells and a physiologically relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein found in secretory fluids including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.


Subject(s)
Antiviral Agents/pharmacology , Immunologic Factors/pharmacology , Lactoferrin/pharmacology , SARS-CoV-2/drug effects , Virus Internalization/drug effects , Virus Replication/drug effects , Animals , COVID-19/drug therapy , COVID-19/immunology , COVID-19/prevention & control , COVID-19/virology , Caco-2 Cells , Cell Line, Tumor , Chlorocebus aethiops , Dose-Response Relationship, Drug , Drug Discovery , Drug Repositioning/methods , Epithelial Cells , Heparitin Sulfate/antagonists & inhibitors , Heparitin Sulfate/immunology , Heparitin Sulfate/metabolism , Hepatocytes , High-Throughput Screening Assays , Humans , SARS-CoV-2/growth & development , SARS-CoV-2/pathogenicity , Vero Cells
16.
Brief Bioinform ; 22(2): 946-962, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1352109

ABSTRACT

Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, or 2019-nCoV), there is an urgent need to identify therapeutics that are effective against COVID-19 before vaccines are available. Since the current rate of SARS-CoV-2 knowledge acquisition via traditional research methods is not sufficient to match the rapid spread of the virus, novel strategies of drug discovery for SARS-CoV-2 infection are required. Structure-based virtual screening for example relies primarily on docking scores and does not take the importance of key residues into consideration, which may lead to a significantly higher incidence rate of false-positive results. Our novel in silico approach, which overcomes these limitations, can be utilized to quickly evaluate FDA-approved drugs for repurposing and combination, as well as designing new chemical agents with therapeutic potential for COVID-19. As a result, anti-HIV or antiviral drugs (lopinavir, tenofovir disoproxil, fosamprenavir and ganciclovir), antiflu drugs (peramivir and zanamivir) and an anti-HCV drug (sofosbuvir) are predicted to bind to 3CLPro in SARS-CoV-2 with therapeutic potential for COVID-19 infection by our new protocol. In addition, we also propose three antidiabetic drugs (acarbose, glyburide and tolazamide) for the potential treatment of COVID-19. Finally, we apply our new virus chemogenomics knowledgebase platform with the integrated machine-learning computing algorithms to identify the potential drug combinations (e.g. remdesivir+chloroquine), which are congruent with ongoing clinical trials. In addition, another 10 compounds from CAS COVID-19 antiviral candidate compounds dataset are also suggested by Molecular Complex Characterizing System with potential treatment for COVID-19. Our work provides a novel strategy for the repurposing and combinations of drugs in the market and for prediction of chemical candidates with anti-COVID-19 potential.


Subject(s)
Antiviral Agents/pharmacology , SARS-CoV-2/drug effects , Drug Discovery , Drug Repositioning/methods , Molecular Docking Simulation
17.
IEEE/ACM Trans Comput Biol Bioinform ; 18(4): 1290-1298, 2021.
Article in English | MEDLINE | ID: covidwho-1349906

ABSTRACT

An outbreak of COVID-19 that began in late 2019 was caused by a novel coronavirus(SARS-CoV-2). It has become a global pandemic. As of June 9, 2020, it has infected nearly 7 million people and killed more than 400,000, but there is no specific drug. Therefore, there is an urgent need to find or develop more drugs to suppress the virus. Here, we propose a new nonlinear end-to-end model called LUNAR. It uses graph convolutional neural networks to automatically learn the neighborhood information of complex heterogeneous relational networks and combines the attention mechanism to reflect the importance of the sum of different types of neighborhood information to obtain the representation characteristics of each node. Finally, through the topology reconstruction process, the feature representations of drugs and targets are forcibly extracted to match the observed network as much as possible. Through this reconstruction process, we obtain the strength of the relationship between different nodes and predict drug candidates that may affect the treatment of COVID-19 based on the known targets of COVID-19. These selected candidate drugs can be used as a reference for experimental scientists and accelerate the speed of drug development. LUNAR can well integrate various topological structure information in heterogeneous networks, and skillfully combine attention mechanisms to reflect the importance of neighborhood information of different types of nodes, improving the interpretability of the model. The area under the curve(AUC) of the model is 0.949 and the accurate recall curve (AUPR) is 0.866 using 10-fold cross-validation. These two performance indexes show that the model has superior predictive performance. Besides, some of the drugs screened out by our model have appeared in some clinical studies to further illustrate the effectiveness of the model.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , COVID-19/virology , Drug Evaluation, Preclinical/methods , Neural Networks, Computer , SARS-CoV-2/drug effects , COVID-19/epidemiology , Computational Biology , Databases, Pharmaceutical/statistics & numerical data , Drug Development/methods , Drug Development/statistics & numerical data , Drug Evaluation, Preclinical/statistics & numerical data , Drug Repositioning/methods , Drug Repositioning/statistics & numerical data , Host Microbial Interactions/drug effects , Humans , Nonlinear Dynamics , Pandemics
18.
Assay Drug Dev Technol ; 19(6): 373-385, 2021.
Article in English | MEDLINE | ID: covidwho-1349762

ABSTRACT

Recent reports have highlighted the possible role of the antipsychotic chlorpromazine and the antidepressant fluvoxamine as anti-coronavirus disease 2019 (COVID-19) agents. The objective of this narrative review is to explore what is known about the activity of psychotropic medications against viruses in addition to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). PubMed was queried for "drug repurposing, antiviral activity," and for "antiviral activity" with "psychotropic drugs" and individual agents, through November 2020. Of more than 100 psychotropic agents, 37 drugs, including 27 with a history of pediatric use were identified, which had been studied in the preclinical setting and found to have activity against viruses which are human pathogens. Effects were evaluated by type of virus and by category of psychotropic agent. Activity was identified both against viruses known to cause epidemics such as SARS-CoV-2 and Ebola and against those that are the cause of rare disorders such as Human Papillomatosis Virus-related respiratory papillomatosis. Individual drugs and classes of psychotropics often had activity against multiple viruses, with promiscuity explained by shared viral or cellular targets. Safety profiles of psychotropics may be more tolerable in this context than when they are used long-term in the setting of psychiatric illness. Nonetheless, translation of in vitro results to the clinical arena has been slow. Psychotropic medications as a class deserve further study, including in clinical trials for repurposing as antiviral drugs for children and adults.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/drug therapy , Drug Repositioning/methods , Psychotropic Drugs/therapeutic use , COVID-19/immunology , COVID-19/metabolism , Drug Repositioning/trends , Humans
19.
Biomed Pharmacother ; 142: 112023, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1347502

ABSTRACT

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is the most recent coronaviruses, which has infected humans, and caused the disease COVID-19. The World Health Organization has declared COVID-19 as a pandemic in March 2020. The SARS-CoV-2 enters human hosts majorly via the respiratory tract, affecting the lungs first. In few critical cases, the infection progresses to failure of the respiratory system known as acute respiratory distress syndrome acute respiratory distress syndrome may be further associated with multi-organ failure and vasoplegic shock. Currently, the treatment of COVID-19 involves use of antiviral and anti-cytokine drugs. However, both the drugs have low efficacy because they cannot inhibit the production of free radicals and cytokines at the same time. Recently, some researchers have reported the use of methylene blue (MB) in COVID-19 management. MB has been used since a long time as a therapeutic agent, and has been approved by the US FDA for the treatment of other diseases. The additional advantage of MB is its low cost. MB is a safe drug when used in the dose of < 2 mg/kg. In this review, the applicability of MB in COVID-19 and its mechanistic aspects have been explored and compiled. The clinical studies have been explained in great detail. Thus, the potential of MB in the management of COVID-19 has been examined.


Subject(s)
COVID-19 , Drug Repositioning/methods , Methylene Blue/pharmacology , SARS-CoV-2 , Antiviral Agents/pharmacology , COVID-19/drug therapy , COVID-19/metabolism , COVID-19/virology , Enzyme Inhibitors/pharmacology , Humans , SARS-CoV-2/drug effects , SARS-CoV-2/physiology
20.
Brief Bioinform ; 22(2): 701-713, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1343637

ABSTRACT

The stratification of patients at risk of progression of COVID-19 and their molecular characterization is of extreme importance to optimize treatment and to identify therapeutic options. The bioinformatics community has responded to the outbreak emergency with a set of tools and resource to identify biomarkers and drug targets that we review here. Starting from a consolidated corpus of 27 570 papers, we adopt latent Dirichlet analysis to extract relevant topics and select those associated with computational methods for biomarker identification and drug repurposing. The selected topics span from machine learning and artificial intelligence for disease characterization to vaccine development and to therapeutic target identification. Although the way to go for the ultimate defeat of the pandemic is still long, the amount of knowledge, data and tools generated so far constitutes an unprecedented example of global cooperation to this threat.


Subject(s)
Biomarkers/blood , COVID-19/drug therapy , Drug Delivery Systems , Antiviral Agents/therapeutic use , COVID-19/blood , COVID-19/virology , Drug Repositioning/methods , Humans , Machine Learning , SARS-CoV-2/isolation & purification
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