scholarly journals A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mahnaz Habibi ◽  
Golnaz Taheri ◽  
Rosa Aghdam
Keyword(s):  
Biological Networks ◽  
Drug Repurposing ◽  
Diabetes Type 2 ◽  
Minimum Size ◽  
Essential Proteins ◽  
Fast Recognition ◽  
Associated Proteins ◽  
Significant Enrichment ◽  
Effective Drugs ◽  
Clinical Drug

AbstractThe Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus needs a fast recognition of effective drugs to save lives. In the COVID-19 situation, finding targets for drug repurposing can be an effective way to present new fast treatments. We have designed a two-step solution to address this approach. In the first step, we identify essential proteins from virus targets or their associated modules in human cells as possible drug target candidates. For this purpose, we apply two different algorithms to detect some candidate sets of proteins with a minimum size that drive a significant disruption in the COVID-19 related biological networks. We evaluate the resulted candidate proteins sets with three groups of drugs namely Covid-Drug, Clinical-Drug, and All-Drug. The obtained candidate proteins sets approve 16 drugs out of 18 in the Covid-Drug, 273 drugs out of 328 in the Clinical-Drug, and a large number of drugs in the All-Drug. In the second step, we study COVID-19 associated proteins sets and recognize proteins that are essential to disease pathology. This analysis is performed using DAVID to show and compare essential proteins that are contributed between the COVID-19 comorbidities. Our results for shared proteins show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases.

scholarly journals Topological network based drug repurposing for coronavirus 2019

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255270
Author(s):  
Mahnaz Habibi ◽  
Golnaz Taheri
Keyword(s):  
Clinical Trials ◽  
Protein Interaction ◽  
Interaction Network ◽  
Drug Repurposing ◽  
Diabetes Type 2 ◽  
Host Cells ◽  
Health Concern ◽  
Virus Protein ◽  
Human Virus ◽  
Fast Recognition

The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become the current health concern and threat to the entire world. Thus, the world needs the fast recognition of appropriate drugs to restrict the spread of this disease. The global effort started to identify the best drug compounds to treat COVID-19, but going through a series of clinical trials and our lack of information about the details of the virus’s performance has slowed down the time to reach this goal. In this work, we try to select the subset of human proteins as candidate sets that can bind to approved drugs. Our method is based on the information on human-virus protein interaction and their effect on the biological processes of the host cells. We also define some informative topological and statistical features for proteins in the protein-protein interaction network. We evaluate our selected sets with two groups of drugs. The first group contains the experimental unapproved treatments for COVID-19, and we show that from 17 drugs in this group, 15 drugs are approved by our selected sets. The second group contains the external clinical trials for COVID-19, and we show that 85% of drugs in this group, target at least one protein of our selected sets. We also study COVID-19 associated protein sets and identify proteins that are essential to disease pathology. For this analysis, we use DAVID tools to show and compare disease-associated genes that are contributed between the COVID-19 comorbidities. Our results for shared genes show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases. In the last part of this work, we recommend 56 potential effective drugs for further research and investigation for COVID-19 treatment. Materials and implementations are available at: https://github.com/MahnazHabibi/Drug-repurposing.

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 Clinical connectivity map for drug repurposing: using laboratory results to bridge drugs and diseases

2021 ◽  
Vol 21 (S8) ◽  
Author(s):  
Qianlong Wen ◽  
Ruoqi Liu ◽  
Ping Zhang
Keyword(s):  
Drug Effect ◽  
Drug Repurposing ◽  
Clinical Disease ◽  
Therapeutic Effects ◽  
Connectivity Map ◽  
Electronic Health Record Data ◽  
Chemical Structures ◽  
Laboratory Results ◽  
Clinical Drug ◽  
Disease Sign

Abstract Background Drug repurposing, the process of identifying additional therapeutic uses for existing drugs, has attracted increasing attention from both the pharmaceutical industry and the research community. Many existing computational drug repurposing methods rely on preclinical data (e.g., chemical structures, drug targets), resulting in translational problems for clinical trials. Results In this study, we propose a novel framework based on clinical connectivity mapping for drug repurposing to analyze therapeutic effects of drugs on diseases. We firstly establish clinical drug effect vectors (i.e., drug-laboratory results associations) by applying a continuous self-controlled case series model on a longitudinal electronic health record data, then establish clinical disease sign vectors (i.e., disease-laboratory results associations) by applying a Wilcoxon rank sum test on a large-scale national survey data. Eventually, a repurposing possibility score for each drug-disease pair is computed by applying a dot product-based scoring function on clinical disease sign vectors and clinical drug effect vectors. During the experiment, we comprehensively evaluate 392 drugs for 6 important chronic diseases (include asthma, coronary heart disease, congestive heart failure, heart attack, type 2 diabetes, and stroke). The experiment results not only reflect known associations between diseases and drugs, but also include some hidden drug-disease associations. The code for this paper is available at: https://github.com/HoytWen/CCMDR Conclusions The proposed clinical connectivity map framework uses laboratory results found from electronic clinical information to bridge drugs and diseases, which make their relations explainable and has better translational power than existing computational methods. Experimental results demonstrate the effectiveness of our proposed framework, further case analysis also proves our method can be used to repurposing existing drugs opportunities.

scholarly journals SARS-CoV-2 meta-interactome suggests disease-specific, autoimmune pathophysiologies and therapeutic targets

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 992 ◽  
Author(s):  
Gianmarco Bellucci ◽  
Chiara Ballerini ◽  
Rosella Mechelli ◽  
Rachele Bigi ◽  
Virginia Rinaldi ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Strong Association ◽  
Therapeutic Targets ◽  
Drug Repurposing ◽  
Therapeutic Strategies ◽  
Type I Interferons ◽  
Type I ◽  
Inflammatory State ◽  
Significant Enrichment ◽  
Human Coronaviruses

Background: Severe coronavirus disease 2019 (COVID-19) is associated with multiple comorbidities and is characterized by an auto-aggressive inflammatory state leading to massive collateral damage. To identify preventive and therapeutic strategies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is important to ascertain the molecular interactions between virus and host, and how they translate into disease pathophysiology. Methods: We matched virus-human protein interactions of human coronaviruses and other respiratory viruses with lists of genes associated with autoimmune diseases and comorbidities associated to worse COVID-19 course. We then selected the genes included in the statistically significant intersection between SARS-CoV-2 network and disease associated gene sets, identifying a meta-interactome. We analyzed the meta-interactome genes expression in samples derived from lungs of infected humans, and their regulation by IFN-β. Finally, we performed a drug repurposing screening to target the network’s most critical nodes. Results: We found a significant enrichment of SARS-CoV-2 interactors in immunological pathways and a strong association with autoimmunity and three prognostically relevant conditions (type 2 diabetes, coronary artery diseases, asthma), that present more independent physiopathological subnetworks. We observed a reduced expression of meta-interactome genes in human lungs after SARS-CoV-2 infection, and a regulatory potential of type I interferons. We also underscored multiple repurposable drugs to tailor the therapeutic strategies. Conclusions: Our data underscored a plausible genetic background that may contribute to the distinct observed pathophysiologies of severe COVID-19. Also, these results may help identify the most promising therapeutic targets and treatments for this condition.

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>

Tackling Alzheimer’s Disease with Existing Drugs: Playing Dirty for Bypassing Obstacles

2020 ◽  
Vol 27 ◽  
Author(s):  
Angela Rampa ◽  
Silvia Gobbi ◽  
Federica Belluti ◽  
Alessandra Bisi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Unmet Need ◽  
Drug Repurposing ◽  
Development Programs ◽  
Disease Pathogenesis ◽  
Structural Modifications ◽  
Beneficial Effects ◽  
Multifunctional Compounds ◽  
Effective Drugs

: The unmet need for the development of effective drugs to treat Alzheimer's disease has been steadily growing, representing a major challenge in drug discovery. In this context, drug repurposing, namely the identification of novel therapeutic indications for approved or investigational compounds, can be seen as an attractive attempt to obtain new medications reducing both the time and the economic burden usually required for research and development programs. In the last years, several classes of drugs have evidenced promising beneficial effects in neurodegenerative diseases, and for some of them preliminary clinical trials have been started. This review aims to illustrate some of the most recent examples of drugs reprofiled for Alzheimer’s disease, considering not only the finding of new uses for existing drugs, but also the new hypotheses on disease pathogenesis, that could promote previously unconsidered therapeutic regimens. Moreover, some examples of structural modifications performed on existing drugs in order to obtain multifunctional compounds will also be described.

scholarly journals Screening of Natural Extracts for Inhibitors against Japanese Encephalitis Virus Infection

2019 ◽  
Vol 64 (3) ◽  
Author(s):  
Jiao Guo ◽  
Xiaoying Jia ◽  
Yang Liu ◽  
Shaobo Wang ◽  
Junyuan Cao ◽  
...  
Keyword(s):  
Japanese Encephalitis Virus ◽  
Japanese Encephalitis ◽  
Antiviral Agents ◽  
Drug Repurposing ◽  
Encephalitis Virus ◽  
Morbidity And Mortality ◽  
High Morbidity ◽  
Japanese Encephalitis Virus Infection ◽  
Natural Extracts ◽  
Effective Drugs

ABSTRACT The mosquito-borne Japanese encephalitis virus (JEV) causes serious illness worldwide that is associated with high morbidity and mortality. Currently, there are no effective drugs approved for the treatment of JEV infection. Drug-repurposing screening is an alternative approach to discover potential antiviral agents. In this study, high-content screening (HCS) of a natural extracts library was performed, and two hit FDA-approved Na+/K+-ATPase inhibitors, ouabain and digoxin, were identified as having robust efficiency against JEV infection with the selectivity indexes over 1,000. The results indicated that ouabain and digoxin blocked the JEV infection at the replication stage by targeting the Na+/K+-ATPase. Furthermore, it was proven that ouabain significantly reduced the morbidity and mortality caused by JEV in a BALB/c mouse model. This work demonstrated that Na+/K+-ATPase could serve as the target of treatment of JEV infection, and ouabain has the potential to be developed as an effective anti-JEV drug.

Drug Repurposing for Parkinson’s Disease by Integrating Knowledge Graph Completion Model and Knowledge Fusion of Medical Literature

2021 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Xiaolin Zhang ◽  
Chao Che
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Knowledge Base ◽  
Medical Literature ◽  
Medical Knowledge ◽  
Drug Repurposing ◽  
New Drugs ◽  
Knowledge Graph ◽  
Knowledge Fusion ◽  
Effective Drugs

The prevalence of Parkinson’s disease increases a tremendous medical and economic burden to society. Therefore, the effective drugs are urgently required. However, the traditional development of effective drugs is costly and risky. Drug repurposing, which identifies new applications for existing drugs, is a feasible strategy for discovering new drugs for Parkinson’s disease. Drug repurposing is based on sufficient medical knowledge. The local medical knowledge base with manually labeled data contains a large number of accurate, but not novel, medical knowledge, while the medical literature containing the latest knowledge is difficult to utilize, because of unstructured data. This paper proposes a framework, named Drug Repurposing for Parkinson’s disease by integrating Knowledge Graph Completion method and Knowledge Fusion of medical literature data (DRKF) in order to make full use of a local medical knowledge base containing accurate knowledge and medical literature with novel knowledge. DRKF first extracts the relations that are related to Parkinson’s disease from medical literature and builds a medical literature knowledge graph. After that, the literature knowledge graph is fused with a local medical knowledge base that integrates several specific medical knowledge sources in order to construct a fused medical knowledge graph. Subsequently, knowledge graph completion methods are leveraged to predict the drug candidates for Parkinson’s disease by using the fused knowledge graph. Finally, we employ classic machine learning methods to repurpose the drug for Parkinson’s disease and compare the results with the method only using the literature-based knowledge graph in order to confirm the effectiveness of knowledge fusion. The experiment results demonstrate that our framework can achieve competitive performance, which confirms the effectiveness of our proposed DRKF for drug repurposing against Parkinson’s disease. It could be a supplement to traditional drug discovery methods.

scholarly journals In silico drug repurposing of anticancer drug 5-FU and analogues against SARS-CoV-2 main protease

2021 ◽  
Author(s):  
Aristote Matondo ◽  
Washington Dendera ◽  
Bienfait K. Isamura ◽  
Koto-te-Nyiwa Ngbolua ◽  
Hilaire V.S. Mambo ◽  
...  
Keyword(s):  
Drug Repurposing ◽  
Pharmacological Action ◽  
Time Saving ◽  
Therapeutic Uses ◽  
Main Protease ◽  
Approved Drugs ◽  
Effective Drugs ◽  
Therapeutic Profile

The pressing need to find effective drugs against the current deadly COVID-19 disease has recently motivated numerous studies using different approaches to address the problem. One time-saving and less costly strategy is the drug repurposing, which consists in finding new therapeutic uses for approved drugs. Following the same trend, this study has investigated the potential inhibitory activity of 5-FU and its analogues against the SARS-CoV-2 main protease as well as their profile of druggability using molecular docking and ADMET methods. From the calculations performed, four candidates showed promising results with respect to the binding affinity to the target protease, 3CLpro, the therapeutic profile of druggability and safety. Further in-vitro and in-vivo investigations are needed that may clarify their possible mechanism of the pharmacological action to combat COVID-19.

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