scholarly journals Pathogenetic profiling of COVID-19 and SARS-like viruses

2020 ◽  
Author(s):  
Zulkar Nain ◽  
Humayan Kabir Rana ◽  
Pietro Liò ◽  
Sheikh Mohammed Shariful Islam ◽  
Matthew A Summers ◽  
...  
Keyword(s):  
Viral Infections ◽  
Chemical Interaction ◽  
Interaction Analysis ◽  
Control Measures ◽  
Functional Enrichment ◽  
Drug Candidates ◽  
Prospective Control ◽  
Genetic Mechanisms ◽  
Novel Coronavirus ◽  
Novel Drug

Abstract The novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significant societal/global disruption. Importantly, COVID-19 infection resembles SARS-like complications. However, the lack of knowledge about the underlying genetic mechanisms of COVID-19 warrants the development of prospective control measures. In this study, we employed whole-genome alignment and digital DNA–DNA hybridization analyses to assess genomic linkage between 2019-nCoV and other coronaviruses. To understand the pathogenetic behavior of 2019-nCoV, we compared gene expression datasets of viral infections closest to 2019-nCoV with four COVID-19 clinical presentations followed by functional enrichment of shared dysregulated genes. Potential chemical antagonists were also identified using protein–chemical interaction analysis. Based on phylogram analysis, the 2019-nCoV was found genetically closest to SARS-CoVs. In addition, we identified 562 upregulated and 738 downregulated genes (adj. P ≤ 0.05) with SARS-CoV infection. Among the dysregulated genes, SARS-CoV shared ≤19 upregulated and ≤22 downregulated genes with each of different COVID-19 complications. Notably, upregulation of BCL6 and PFKFB3 genes was common to SARS-CoV, pneumonia and severe acute respiratory syndrome, while they shared CRIP2, NSG1 and TNFRSF21 genes in downregulation. Besides, 14 genes were common to different SARS-CoV comorbidities that might influence COVID-19 disease. We also observed similarities in pathways that can lead to COVID-19 and SARS-CoV diseases. Finally, protein–chemical interactions suggest cyclosporine, resveratrol and quercetin as promising drug candidates against COVID-19 as well as other SARS-like viral infections. The pathogenetic analyses, along with identified biomarkers, signaling pathways and chemical antagonists, could prove useful for novel drug development in the fight against the current global 2019-nCoV pandemic.

scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

Screening novel drug candidates for Alzheimer’s disease by an integrated network and transcriptome analysis

2020 ◽  
Vol 36 (17) ◽  
pp. 4626-4632
Author(s):  
Yonglin Peng ◽  
Meng Yuan ◽  
Juncai Xin ◽  
Xinhua Liu ◽  
Ju Wang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Supplementary Information ◽  
Integrated Network ◽  
Drug Candidates ◽  
Novel Drug

Abstract Motivation Alzheimer’s disease (AD) is a serious degenerative brain disease and the most common cause of dementia. The current available drugs for AD provide symptomatic benefit, but there is no effective drug to cure the disease. The emergence of large-scale genomic, pharmacological data provides new opportunities for drug discovery and drug repositioning as a promising strategy in searching novel drug for AD. Results In this study, we took advantage of our increasing understanding based on systems biology approaches on the pathway and network levels and perturbation datasets from the Library of Integrated Network-Based Cellular Signatures to introduce a systematic computational process to discover new drugs implicated in AD. First, we collected 561 genes that have reported to be risk genes of AD, and applied functional enrichment analysis on these genes. Then, by quantifying proximity between 5595 molecule drugs and AD based on human interactome, we filtered out 1092 drugs that were proximal to the disease. We further performed an Inverted Gene Set Enrichment analysis on these drug candidates, which allowed us to estimate effect of perturbations on gene expression and identify 24 potential drug candidates for AD treatment. Results from this study also provided insights for understanding the molecular mechanisms underlying AD. As a useful systematic method, our approach can also be used to identify efficacious therapies for other complex diseases. Availability and implementation The source code is available at https://github.com/zer0o0/drug-repo.git. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Rapid Identification of Potential Inhibitors of SARS-CoV-2 Main Protease by Deep Docking of 1.3 Billion Compounds

2020 ◽  
Author(s):  
Anh-Tien Ton ◽  
Francesco Gentile ◽  
Michael Hsing ◽  
Fuqiang Ban ◽  
Artem Cherkasov
Keyword(s):  
Rapid Identification ◽  
Molecular Structures ◽  
Drug Candidates ◽  
Learning Platform ◽  
Main Protease ◽  
The World ◽  
Novel Coronavirus ◽  
Potential Inhibitors ◽  
Small Molecule Therapeutics ◽  
Novel Drug

<div>The recently emerged 2019 Novel Coronavirus (SARS-CoV-2) and associated COVID-19 disease cause serious or even fatal respiratory tract infection and yet no FDA-approved therapeutics or effective treatment is currently available to effectively combat the outbreak. This urgent situation is pressing the world to respond with the development of novel vaccine or a small molecule therapeutics for SARS-CoV-2. Along these efforts, the structure of SARS-CoV-2 main protease (Mpro) has been rapidly resolved and made publicly available to facilitate global efforts to develop novel drug candidates.</div><div>In recent month, our group has developed a novel deep learning platform – Deep Docking (DD) which enables very fast docking of billions of molecular structures and provides up to 6,000X enrichment on the top-predicted ligands compared to conventional docking workflow (without notable loss of information on potential hits). In the current work we applied DD to entire 1.3 billion compounds from ZINC15 library to identify top 1,000 potential ligands for SARS-CoV-2 Mpro. The compounds are made publicly available for further characterization and development by scientific community.</div>

scholarly journals CRISPR Screening: Molecular Tools for Studying Virus–Host Interactions

Viruses ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2258
Author(s):  
Vladimir Chulanov ◽  
Anastasiya Kostyusheva ◽  
Sergey Brezgin ◽  
Natalia Ponomareva ◽  
Vladimir Gegechkori ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Viral Infections ◽  
Whole Genome ◽  
Molecular Tools ◽  
Host Interactions ◽  
Drug Candidates ◽  
Complex Interactions ◽  
Recent Developments ◽  
Novel Drug

CRISPR/Cas is a powerful tool for studying the role of genes in viral infections. The invention of CRISPR screening technologies has made it possible to untangle complex interactions between the host and viral agents. Moreover, whole-genome and pathway-specific CRISPR screens have facilitated identification of novel drug candidates for treating viral infections. In this review, we highlight recent developments in the fields of CRISPR/Cas with a focus on the use of CRISPR screens for studying viral infections and identifying new candidate genes to aid development of antivirals.

Identification of novel drug candidates for the inhibition of catalytic cleavage activity of coronavirus 3CL-like protease enzyme

2021 ◽  
Vol 22 ◽  
Author(s):  
Arun Bahadur Gurung ◽  
Khalid Mashay Al-Anazi ◽  
Mohammad Ajmal Ali ◽  
Joongku Lee ◽  
Mohammad Abul Farah
Keyword(s):  
New Drugs ◽  
Amino Acid Residues ◽  
Chemical Library ◽  
Healthcare Facilities ◽  
Drug Candidates ◽  
Protease Enzyme ◽  
Recent Emergence ◽  
Novel Coronavirus ◽  
Novel Drug ◽  
Coronavirus Infections

Background: There has been tremendous pressure on healthcare facilities globally due to the recent emergence of novel coronavirus infections known as COVID-19 and its rapid spread across the continents. The lack of effective therapeutics for the management of the pandemic calls for the discovery of new drugs and vaccines. Objective: In the present study, a chemical library was screened for molecules against three coronavirus 3CL-like protease enzymes (SARS-CoV-2 3CLpro, SARS-CoV 3CLpro and MERS-CoV 3CLpro), which are a key player in the viral replication cycle. Methods: Extensive computational methods, such as virtual screening and molecular docking, were employed in this study. Results: Two lead molecules- ZINC08825480 (4-bromo-N'-(E)-[1-phenyl-3-(pyridin-3-yl)-1H-pyrazol-4-yl]methylidenebenzene-1-sulfonohydrazide) and ZINC72009942 (N-[[2-[[(3S)-3-methyl-1-piperidyl]methyl]phenyl]methyl]-6-oxo-1-(p-tolyl)-4,5-dihydro-1,2,4-triazine-3-carboxamide) were identified with better affinity with the three target enzymes as compared to the approved antiviral drugs. Both the lead molecules possess favourable drug-like properties, fit well into the active site pocket close to His-Cys dyad and show a good number of hydrogen bonds with the backbone as well as side chains of key amino acid residues. Conclusion: Thus, the present study offers two novel chemical entities against coronavirus infections, which can be validated through various biological assays.

scholarly journals Rapid Identification of Potential Inhibitors of SARS-CoV-2 Main Protease by Deep Docking of 1.3 Billion Compounds

2020 ◽  
Author(s):  
Anh-Tien Ton ◽  
Francesco Gentile ◽  
Michael Hsing ◽  
Fuqiang Ban ◽  
Artem Cherkasov
Keyword(s):  
Rapid Identification ◽  
Molecular Structures ◽  
Drug Candidates ◽  
Learning Platform ◽  
Main Protease ◽  
The World ◽  
Novel Coronavirus ◽  
Potential Inhibitors ◽  
Small Molecule Therapeutics ◽  
Novel Drug

<div>The recently emerged 2019 Novel Coronavirus (SARS-CoV-2) and associated COVID-19 disease cause serious or even fatal respiratory tract infection and yet no FDA-approved therapeutics or effective treatment is currently available to effectively combat the outbreak. This urgent situation is pressing the world to respond with the development of novel vaccine or a small molecule therapeutics for SARS-CoV-2. Along these efforts, the structure of SARS-CoV-2 main protease (Mpro) has been rapidly resolved and made publicly available to facilitate global efforts to develop novel drug candidates.</div><div>In recent month, our group has developed a novel deep learning platform – Deep Docking (DD) which enables very fast docking of billions of molecular structures and provides up to 6,000X enrichment on the top-predicted ligands compared to conventional docking workflow (without notable loss of information on potential hits). In the current work we applied DD to entire 1.3 billion compounds from ZINC15 library to identify top 1,000 potential ligands for SARS-CoV-2 Mpro. The compounds are made publicly available for further characterization and development by scientific community.</div>

scholarly journals African and Asian Medicinal Plants as a Repository for Prospective Antiviral Metabolites Against HIV-1 and SARS CoV-2: A Mini Review

2021 ◽  
Vol 12 ◽  
Author(s):  
Godwin Anywar ◽  
Muhammad Akram ◽  
Muhammad Amjad Chishti
Keyword(s):  
Medicinal Plants ◽  
Plant Species ◽  
Viral Infections ◽  
Antiviral Agents ◽  
Natural Compounds ◽  
Drug Candidates ◽  
Novel Coronavirus ◽  
Hiv 1

Introduction: The worldwide burden of viral infections has triggered a resurgence in the search for new and more efficient antiviral drugs. Scientists are also repurposing existing natural compounds such as the antimalarial drug artemisinin from Artemesia annua L. as potential drug candidates for some of the emerging and re-emerging viral infections such as covid-19Aim: The aim of this review was to analyse the existing literature to explore the actual or potential natural antiviral compounds from African and Asian medicinal plants as lead compounds in the drug discovery process.Methods: We searched the literature on African and Asian medicinal plant species as antiviral agents for HIV-1 and the novel coronavirus (SARS-CoV-2) in various databases and search engines such as Web of Science, Google Scholar and PubMed. The search was limited to in vitro, in vivo, and clinical studies and excluded in silico studies.Results: We present 16 plant species with actual or potential antiviral activity against HIV-1 and SARS-CoV-2. These plant species span the continents of Africa and Asia where they are widely used for treating several other ailments.Conclusion: Natural compounds from plants can play a significant role in the clinical management of HIV/AIDS and the covid-19 pandemic. More research needs to be conducted to investigate the potential toxicities of the various compounds and their efficacies in clinical settings.

Coronavirus: Towards controlling of the pandemic - Indian scenario

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 462-468
Author(s):  
Latika kothari ◽  
Sanskruti Wadatkar ◽  
Roshni Taori ◽  
Pavan Bajaj ◽  
Diksha Agrawal
Keyword(s):  
Control Measures ◽  
The Novel ◽  
Medical Treatments ◽  
Health Crisis ◽  
The Public ◽  
Infection Control Measures ◽  
The Social ◽  
Asking Questions ◽  
The Government ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) is a communicable infection caused by the novel coronavirus resulting in severe acute respiratory syndrome coronavirus 2 (SARS-CoV). It was recognized to be a health crisis for the general population of international concern on 30th January 2020 and conceded as a pandemic on 11th March 2020. India is taking various measures to fight this invisible enemy by adopting different strategies and policies. To stop the COVID-19 from spreading, the Home Affairs Ministry and the health ministry, of India, has issued the nCoV 19 guidelines on travel. Screening for COVID-19 by asking questions about any symptoms, recent travel history, and exposure. India has been trying to get testing kits available. The government of India has enforced various laws like the social distancing, Janata curfew, strict lockdowns, screening door to door to control the spread of novel coronavirus. In this pandemic, innovative medical treatments are being explored, and a proper vaccine is being hunted to deal with the situation. Infection control measures are necessary to prevent the virus from further spreading and to help control the current situation. Thus, this review illustrates and explains the criteria provided by the government of India to the awareness of the public to prevent the spread of COVID-19.

scholarly journals Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Anna C. Aschenbrenner ◽  
◽  
Maria Mouktaroudi ◽  
Benjamin Krämer ◽  
Marie Oestreich ◽  
...  
Keyword(s):  
Immune System ◽  
Disease Severity ◽  
Whole Blood ◽  
Viral Infections ◽  
Inflammatory Diseases ◽  
Target Prediction ◽  
Data Driven ◽  
Host Responses ◽  
Drug Candidates ◽  
Drug Target Prediction

Abstract Background The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. Methods In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. Results Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. Conclusions Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.

scholarly journals Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qinglong Zhao ◽  
Yao Wang ◽  
Meng Yang ◽  
Meina Li ◽  
Zeyu Zhao ◽  
...  
Keyword(s):  
Prevention And Control ◽  
Good Control ◽  
Asymptomatic Infection ◽  
Jilin Province ◽  
Control Measures ◽  
First Case ◽  
Before And After ◽  
Novel Coronavirus ◽  
Reported Data ◽  
And Control

Abstract Background Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of measures to control the disease in Jilin Province, China. Methods The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible–Exposed–Infectious–Asymptomatic–Recovered/Removed (SEIAR) model was developed to fit the data, and the effective reproduction number (Reff) was calculated at different stages in the province. Finally, the effectiveness of the measures was assessed. Results A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit the reported data well (R2 = 0.593, P < 0.001). The Reff of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would have reached a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would have been 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus’s spread. Conclusions COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proven effective; increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease.

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