scholarly journals Virtual Screening of Some Antivirals That Can Be Repurposed As Potential Effective Drugs against SARS-CoV-2

2020 ◽  
Author(s):  
Mohammad Rejaur Rahman ◽  
Anik Banik ◽  
Ishtiak Malique Chowdhury ◽  
Emran Sajib ◽  
Sanchita Sarkar
Keyword(s):  
Rna Binding ◽  
Viral Infections ◽  
Toxicity Testing ◽  
Drug Repurposing ◽  
Drug Candidates ◽  
Docking Method ◽  
Speed Up ◽  
Coronavirus Infection ◽  
Effective Drugs ◽  
Drug Similarity

<p>SARS-CoV-2 has triggered a big epidemic among people around the world and it is the newest in the sequence to be prevalent among other infectious diseases. Drug repurposing concept has been utilized effectively for numerous viral infections. Considering the situation and the urgency, the idea of drug repurposing for coronavirus infection (COVID-19) is also being studied. Screening with molecular docking method for 29 antiviral drugs was performed against SARSCoV-2 primary protease proteins (MPP), spike ecto-domain, spike receptor binding domain, Nsp9 RNA binding protein,and HR2 domain. Among these drugs, Indinavir, Sorivudine, Cidofovir and Darunavir show minimum docking scores with all key proteins in terms of least binding energy. For ADME (Absorption, Distribution, Metabolism, and Excretion) analysis, the top 4 drug candidates were further used to examine their drug profiles for suitability against SARS-CoV-2. The toxicity testing of top drug candidates showed no significant carcinogenic, mutagenic or skin irritating impacts. Indinavir may possess some complexity to heart. In addition, the drug similarity prediction revealed several approved structural analogues such as Telbivudine, Tenofovir, Amprenavir, Fosamprenavir etc which also could be used to treat viral infections. The study may speed up the findings of therapeutics against SARS-CoV-2. <br></p>

scholarly journals Virtual Screening of Some Antivirals That Can Be Repurposed As Potential Effective Drugs against SARS-CoV-2

2020 ◽  
Author(s):  
Mohammad Rejaur Rahman ◽  
Anik Banik ◽  
Ishtiak Malique Chowdhury ◽  
Emran Sajib ◽  
Sanchita Sarkar
Keyword(s):  
Rna Binding ◽  
Viral Infections ◽  
Toxicity Testing ◽  
Drug Repurposing ◽  
Drug Candidates ◽  
Docking Method ◽  
Speed Up ◽  
Coronavirus Infection ◽  
Effective Drugs ◽  
Drug Similarity

<p>SARS-CoV-2 has triggered a big epidemic among people around the world and it is the newest in the sequence to be prevalent among other infectious diseases. Drug repurposing concept has been utilized effectively for numerous viral infections. Considering the situation and the urgency, the idea of drug repurposing for coronavirus infection (COVID-19) is also being studied. Screening with molecular docking method for 29 antiviral drugs was performed against SARSCoV-2 primary protease proteins (MPP), spike ecto-domain, spike receptor binding domain, Nsp9 RNA binding protein,and HR2 domain. Among these drugs, Indinavir, Sorivudine, Cidofovir and Darunavir show minimum docking scores with all key proteins in terms of least binding energy. For ADME (Absorption, Distribution, Metabolism, and Excretion) analysis, the top 4 drug candidates were further used to examine their drug profiles for suitability against SARS-CoV-2. The toxicity testing of top drug candidates showed no significant carcinogenic, mutagenic or skin irritating impacts. Indinavir may possess some complexity to heart. In addition, the drug similarity prediction revealed several approved structural analogues such as Telbivudine, Tenofovir, Amprenavir, Fosamprenavir etc which also could be used to treat viral infections. The study may speed up the findings of therapeutics against SARS-CoV-2. <br></p>

scholarly journals Prioritization of Potential Drugs Targeting the SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Yanjin Li ◽  
Yu Zhang ◽  
Yikai Han ◽  
Tengfei Zhang ◽  
Ranran Du
Keyword(s):  
Large Scale ◽  
Drug Repurposing ◽  
Drug Candidates ◽  
Neural Activities ◽  
Main Protease ◽  
Global Threat ◽  
Potential Inhibitors ◽  
Molecular Patterns ◽  
Effective Drugs ◽  
Large Scale Screening

<p> Since its outbreak in 2019, the acute respiratory syndrome caused by SARS-Cov-2 has become a severe global threat to human. The lack of effective drugs strongly limits the therapeutic treatment against this pandemic disease. Here we employed a computational approach to prioritize potential inhibitors that directly target the core enzyme of SARS-Cov-2, the main protease, which is responsible for processing the viral RNA-translated polyprotein into functional proteins for viral replication. Based on a large-scale screening of over 13, 000 drug-like molecules, we have identified the most potential drugs that may suffice drug repurposing for SARS-Cov-2. Importantly, the second top hit is Beclabuvir, a known replication inhibitor of hepatitis C virus (HCV), which is recently reported to inhibit SARS-Cov-2 as well. We also noted several neurotransmitter-related ligands among the top candidates, suggesting a novel molecular similarity between this respiratory syndrome and neural activities. Our approach not only provides a comprehensive list of prioritized drug candidates for SARS-Cov-2, but also reveals intriguing molecular patterns that are worth future explorations.</p>

scholarly journals Identification of Potential Phytochemical Inhibitors as Promising Therapeutics Against SARS-CoV-2 and Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Anik Banik ◽  
Emran Sajib ◽  
Anamika Deb ◽  
Sheikh Rashel Ahmed ◽  
Md- Tariqul Islam ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Rna Binding ◽  
Viral Infections ◽  
Dynamics Simulation ◽  
Screening Methods ◽  
Plant Metabolites ◽  
Target Class ◽  
Drug Candidates ◽  
Preventive Medication

The high infectivity and mortality of novel coronavirus has caused a serious concern all over the world. Still, there is no specific drug or preventive medication to treat SARS-CoV-2 infection despite comprehensive analysis by the researchers. This study was designed to demonstrate the efficacy of some phyto-chemical compounds against SARS-CoV-2 by using both structure and ligand based virtual screening methods. A total of 33 plant metabolites were screened against SARS-CoV-2 main protease proteins (MPP), Nsp9 RNA binding protein, spike receptor binding domain and HR2 domain using a molecular docking approach. Results showed that three metabolites, i.e., Limonin, Isoflavone, and Coumadin conferred maximum binding affinity with all key proteins of SARS-CoV-2. For each viral protein, the critical binding sites and drug surface hotspots have been unraveled. ADME analysis indicated that none of the compounds have adverse effects that could decrease their drug-like properties. Moreover, toxicity pattern analysis also unmasked the non-toxic nature of the top drug candidates. The RMSD values of top ligandmacromolecule complexes were less than 2 Å, while RMSF values showed regular atomic fluctuations in the molecular dynamics study. Notably, most of the target class by top drug candidates belonged to enzyme groups (e.g. oxidoreductases, protease, Kinase). Results of drug similarity prediction revealed two approved structural analogs of Coumadin named Warfarin (DB00682) and Phenprocoumon (DB00946) from DrugBank. In addition, Isoformononetin an experimental drug analog of isoflavone could also be an option for the treatment of viral infections. For limonin there was no analog found in drugbank. The study can pave the way for the creation of effective SARS-CoV-2 medications and preventive measures. We highly recommend further in vivo trials for the experimental validation of our findings

Application of Artificial Intelligence in Drug Repurposing: A mini-review

2021 ◽  
Vol 01 ◽  
Author(s):  
Gurudeeban Selvaraj ◽  
Satyavani Kaliamurthi ◽  
Gilles H. Peslherbe ◽  
Dong-Qing Wei
Keyword(s):  
Artificial Intelligence ◽  
Drug Repositioning ◽  
Target Identification ◽  
Drug Repurposing ◽  
Search Term ◽  
Biomedical Data ◽  
Drug Candidates ◽  
Drug Target Identification ◽  
Speed Up ◽  
Tools And Techniques

Background and aim: Advancement of extra-ordinary biomedical data (genomics, proteomics, metabolomics, drug libraries, and patient care data), evolution of super-computers, and continuous development of new algorithms that lead to a generous revolution in artificial intelligence (AI). Currently, many biotech and pharmaceutical companies made reasonable investments in and have co-operation with AI companies and increasing the chance of better healthcare tools development, includes biomarker and drug target identification, designing a new class of drugs and drug repurposing. Thus, the study is intended to project the pros and cons of AI in the application of drug repositioning. Methods: Using the search term “AI” and “drug repurposing” the relevant literatures retrieved and reviewed from different sources includes PubMed, Google Scholar, and Scopus. Results: Drug discovery is a lengthy process, however, leveraging the AI approaches in drug repurposing via quick virtual screening may enhance and speed-up the identification of potential drug candidates against communicable and non-communicable diseases. Therefore, in this mini-review, we have discussed different algorithms, tools and techniques, advantages, limitations on predicting the target in repurposing a drug. Conclusions: AI technology in drug repurposing with the association of pharmacology can efficiently identify drug candidates against pandemic diseases.

Prioritization of Potential Drugs Targeting the SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Yanjin Li ◽  
Yu Zhang ◽  
Yikai Han ◽  
Tengfei Zhang ◽  
Ranran Du
Keyword(s):  
Large Scale ◽  
Drug Repurposing ◽  
Drug Candidates ◽  
Neural Activities ◽  
Main Protease ◽  
Global Threat ◽  
Potential Inhibitors ◽  
Molecular Patterns ◽  
Effective Drugs ◽  
Large Scale Screening

<p> Since its outbreak in 2019, the acute respiratory syndrome caused by SARS-Cov-2 has become a severe global threat to human. The lack of effective drugs strongly limits the therapeutic treatment against this pandemic disease. Here we employed a computational approach to prioritize potential inhibitors that directly target the core enzyme of SARS-Cov-2, the main protease, which is responsible for processing the viral RNA-translated polyprotein into functional proteins for viral replication. Based on a large-scale screening of over 13, 000 drug-like molecules, we have identified the most potential drugs that may suffice drug repurposing for SARS-Cov-2. Importantly, the second top hit is Beclabuvir, a known replication inhibitor of hepatitis C virus (HCV), which is recently reported to inhibit SARS-Cov-2 as well. We also noted several neurotransmitter-related ligands among the top candidates, suggesting a novel molecular similarity between this respiratory syndrome and neural activities. Our approach not only provides a comprehensive list of prioritized drug candidates for SARS-Cov-2, but also reveals intriguing molecular patterns that are worth future explorations.</p>

scholarly journals Extensive Reliability Evaluation of Docking-Based Target-Fishing Strategies

2019 ◽  
Vol 20 (5) ◽  
pp. 1023 ◽  
Author(s):  
Margherita Lapillo ◽  
Tiziano Tuccinardi ◽  
Adriano Martinelli ◽  
Marco Macchia ◽  
Antonio Giordano ◽  
...  
Keyword(s):  
Small Molecule ◽  
Protein Structures ◽  
Drug Repurposing ◽  
Protein Targets ◽  
Drug Candidates ◽  
Fishing Strategies ◽  
Benchmark Database ◽  
Speed Up ◽  
Actual Target ◽  
Target Fishing

The development of target-fishing approaches, aimed at identifying the possible protein targets of a small molecule, represents a hot topic in medicinal chemistry. A successful target-fishing approach would allow for the elucidation of the mechanism of action of all therapeutically interesting compounds for which the actual target is still unknown. Moreover, target-fishing would be essential for preventing adverse effects of drug candidates, by predicting their potential off-targets, and it would speed up drug repurposing campaigns. However, due to the huge number of possible protein targets that a small-molecule might interact with, experimental target-fishing approaches are out of reach. In silico target-fishing represents a valuable alternative, and examples of receptor-based approaches, exploiting the large number of crystallographic protein structures determined to date, have been reported in the literature. To the best of our knowledge, no proper evaluation of such approaches is, however, reported yet. In the present work, we extensively assessed the reliability of docking-based target-fishing strategies. For this purpose, a set of X-ray structures belonging to different targets was selected, and a dataset of compounds, including 10 experimentally active ligands for each target, was created. A target-fishing benchmark database was then obtained, and used to assess the performance of 13 different docking procedures, in identifying the correct target of the dataset ligands. Moreover, a consensus docking-based target-fishing strategy was developed and evaluated. The analysis highlighted that specific features of the target proteins could affect the reliability of the protocol, which however, proved to represent a valuable tool in the proper applicability domain. Our study represents the first extensive performance assessment of docking-based target-fishing approaches, paving the way for the development of novel efficient receptor-based target fishing strategies.

scholarly journals A Computational-Based Drug Repurposing Method Targeting SARS-CoV-2 and its Neurological Manifestations Genes and Signaling Pathways

2021 ◽  
Vol 15 ◽  
pp. 117793222110267
Author(s):  
Ali Sepehrinezhad ◽  
Fariborz Rezaeitalab ◽  
Ali Shahbazi ◽  
Sajad Sahab-Negah
Keyword(s):  
Clinical Trials ◽  
Neurological Disorders ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Neurological Manifestations ◽  
Multiple Organs ◽  
Gene Sets ◽  
Speed Up ◽  
Global Concern ◽  
Effective Drugs

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a global concern involves infections in multiple organs. Much of the research up to now has been descriptive on neurological manifestations followed by SARS-CoV-2 infection. Despite considerable efforts on effective SARS-CoV-2 vaccine, novel therapeutic options for COVID-19 comorbidities are warranted. One of the fast ways to introduce possible effective drugs for clinical trials is bioinformatics methods. We have conducted a comprehensive enrichment analysis of genes involved in SARS-CoV-2 and neurological disorders associated with COVID-19. For this purpose, gene sets were extracted from the GeneWeaver database. To find out some significant enriched findings for common genes between SARS-CoV-2 and its neurological disorders, several practical databases were used. Finally, to repurpose an efficient drug, DrugBank databases were used. Overall, we detected 139 common genes concerning SARS-CoV-2 and their neurological disorders. Interestingly, our study predicted around 6 existing drugs (ie, carvedilol, andrographolide, 2-methoxyestradiol, etanercept, polaprezinc, and arsenic trioxide) that can be used for repurposing. We found that polaprezinc (zinc l-carnosine) drug is not investigated in the context of COVID-19 till now and it could be used for the treatment of COVID-19 and its neurological manifestations. To summarize, enrichment and network data get us a coherent picture to predict drug repurposing to speed up clinical trials.

scholarly journals A phenomics approach for antiviral drug discovery

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jonne Rietdijk ◽  
Marianna Tampere ◽  
Aleksandra Pettke ◽  
Polina Georgiev ◽  
Maris Lapins ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Viral Infection ◽  
Drug Screening ◽  
Viral Infections ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Host Cells ◽  
Lung Fibroblasts ◽  
Morphological Properties ◽  
Drug Candidates

Abstract Background The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections. Results We combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. Conclusions The phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery.

scholarly journals Identification of Potential Phytochemical Inhibitors as Promising Therapeutics Against SARS-CoV-2 and Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Anik Banik ◽  
Emran Sajib ◽  
Anamika Deb ◽  
Sheikh Rashel Ahmed ◽  
Md- Tariqul Islam ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Rna Binding ◽  
Viral Infections ◽  
Dynamics Simulation ◽  
Screening Methods ◽  
Plant Metabolites ◽  
Target Class ◽  
Drug Candidates ◽  
Preventive Medication

The high infectivity and mortality of novel coronavirus has caused a serious concern all over the world. Still, there is no specific drug or preventive medication to treat SARS-CoV-2 infection despite comprehensive analysis by the researchers. This study was designed to demonstrate the efficacy of some phyto-chemical compounds against SARS-CoV-2 by using both structure and ligand based virtual screening methods. A total of 33 plant metabolites were screened against SARS-CoV-2 main protease proteins (MPP), Nsp9 RNA binding protein, spike receptor binding domain and HR2 domain using a molecular docking approach. Results showed that three metabolites, i.e., Limonin, Isoflavone, and Coumadin conferred maximum binding affinity with all key proteins of SARS-CoV-2. For each viral protein, the critical binding sites and drug surface hotspots have been unraveled. ADME analysis indicated that none of the compounds have adverse effects that could decrease their drug-like properties. Moreover, toxicity pattern analysis also unmasked the non-toxic nature of the top drug candidates. The RMSD values of top ligandmacromolecule complexes were less than 2 Å, while RMSF values showed regular atomic fluctuations in the molecular dynamics study. Notably, most of the target class by top drug candidates belonged to enzyme groups (e.g. oxidoreductases, protease, Kinase). Results of drug similarity prediction revealed two approved structural analogs of Coumadin named Warfarin (DB00682) and Phenprocoumon (DB00946) from DrugBank. In addition, Isoformononetin an experimental drug analog of isoflavone could also be an option for the treatment of viral infections. For limonin there was no analog found in drugbank. The study can pave the way for the creation of effective SARS-CoV-2 medications and preventive measures. We highly recommend further in vivo trials for the experimental validation of our findings

scholarly journals Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

2021 ◽  
Author(s):  
Michael Sugiyama ◽  
Haotian Cui ◽  
Dar'ya S Redka ◽  
Mehran Karimzadeh ◽  
Edurne Rujas ◽  
...  
Keyword(s):  
Antiviral Activity ◽  
Drug Targets ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Human Coronavirus ◽  
Independent Manner ◽  
Drug Candidates ◽  
Convolutional Networks ◽  
Target Drug ◽  
Coronavirus Infection

The COVID-19 pandemic has led to an urgent need for the identification of new antiviral drug therapies that can be rapidly deployed to treat patients with this disease. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of COVID-19. 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 repurposing drug 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.

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