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COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19.

ABSTRACT: The COVID-19 pandemic poses a huge problem of public health that requires the implementation of all available means to contrast it, and drugs are one of them. In this context, we observed an unmet need of depicting the continuously evolving scenario of the ongoing drug clinical trials through an easy-to-use, freely accessible online tool. Starting from this consideration, we developed COVIDrugNet ( http://compmedchem.unibo.it/covidrugnet ), a web application that allows users to capture a holistic view and keep up to date on how the clinical drug research is responding to the SARS-CoV-2 infection. Here, we describe the web app and show through some examples how one can explore the whole landscape of medicines in clinical trial for the treatment of COVID-19 and try to probe the consistency of the current approaches with the available biological and pharmacological evidence. We conclude that careful analyses of the COVID-19 drug-target system based on COVIDrugNet can help to understand the biological implications of the proposed drug options, and eventually improve the search for more effective therapies.

SUBMITTER: Menestrina L

PROVIDER: S-EPMC8484553 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19.

Menestrina Luca L Cabrelle Chiara C Recanatini Maurizio M

Scientific reports 20210930 1

The COVID-19 pandemic poses a huge problem of public health that requires the implementation of all available means to contrast it, and drugs are one of them. In this context, we observed an unmet need of depicting the continuously evolving scenario of the ongoing drug clinical trials through an easy-to-use, freely accessible online tool. Starting from this consideration, we developed COVIDrugNet ( http://compmedchem.unibo.it/covidrugnet ), a web application that allows users to capture a holist ...[more]

PMID: 34593915

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Project description:ObjectiveTo review evidence on routinely prescribed drugs in the UK that could upregulate or downregulate ACE2 and potentially affect COVID-19 disease.DesignSystematic review.Data sourceMEDLINE, EMBASE, CINAHL, the Cochrane Library and Web of Science.Study selectionAny design with animal or human models examining a currently prescribed UK drug compared with a control, placebo or sham group, and reporting an effect on ACE2 level, activity or gene expression.Data extraction and synthesisMEDLINE, EMBASE, CINAHL, the Cochrane Library, Web of Science and OpenGrey from inception to 1 April 2020. Methodological quality was assessed using the SYstematic Review Centre for Laboratory animal Experimentation (SYRCLE) risk-of-bias tool for animal studies and Cochrane risk-of-bias tool for human studies.ResultsWe screened 3360 titles and included 112 studies with 21 different drug classes identified as influencing ACE2 activity. Ten studies were in humans and one hundred and two were in animal models None examined ACE2 in human lungs. The most frequently examined drugs were angiotensin receptor blockers (ARBs) (n=55) and ACE inhibitors (ACE-I) (n=22). More studies reported upregulation than downregulation with ACE-I (n=22), ARBs (n=55), insulin (n=8), thiazolidinedione (n=7) aldosterone agonists (n=3), statins (n=5), oestrogens (n=5) calcium channel blockers (n=3) glucagon-like peptide 1 (GLP-1) agonists (n=2) and Non-steroidal anti-inflammatory drugs (NSAIDs) (n=2).ConclusionsThere is an abundance of the academic literature and media reports on the potential of drugs that could attenuate or exacerbate COVID-19 disease. This is leading to trials of repurposed drugs and uncertainty among patients and clinicians concerning continuation or cessation of prescribed medications. Our review indicates that the impact of currently prescribed drugs on ACE2 has been poorly studied in vivo, particularly in human lungs where the SARS-CoV-2 virus appears to enact its pathogenic effects. We found no convincing evidence to justify starting or stopping currently prescribed drugs to influence outcomes of COVID-19 disease.

Project description:Background The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets. Results We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach’s effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients. Conclusions Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases. Supplementary Information The online version contains supplementary material available at 10.1186/s13062-023-00410-9. Key points Extend network structural controllability to total network controllability, providing a practical method for identifying critical nodes that must be protected to maintain network controllability. Extend and apply the new method to identifying drug targets in human protein-protein interaction networks. Apply the new method to identify drugs that can be reused for Covid-19 treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s13062-023-00410-9.

Project description:As the outbreak of novel coronavirus disease (COVID-19) continues to spread throughout the world, steps are being taken to limit the impact on public health. In the realm of infectious diseases like COVID-19, social distancing is one of the effective measures to avoid exposure to the virus and reduce its spread. Traveling on public transport can meaningfully facilitate the propagation of the transmission of infectious diseases. Accordingly, responsive actions taken by public transit agencies against risk factors can effectively limit the risk and make transit systems safe. Among the multitude of risk factors that can affect infection spread on public transport, the likelihood of exposure is a major factor that depends on the number of people riding the public transport and can be reduced by socially distanced settings. Considering that many individuals may not act in the socially optimal manner, the necessity of public transit agencies to implement measures and restrictions is vital. In this study, we present a novel web-based application, T-Ridership, based on a hybrid optimized dynamic programming inspired by neural networks algorithm to optimize public transit for safety with respect to COVID-19. Two main steps are taken in the analysis through Metropolitan Transportation Authority (MTA): detecting high-density stations by input data normalization, and then, using these results, the T-Ridership tool automatically determines optimal station order to avoid overcrowded transit vehicles. Effectively our proposed web tool helps public transit to be safe to ride under risk of infections by reducing the density of riders on public transit vehicles as well as trip duration. These results can be used in expanding on and improving policy in public transit, to better plan the scheduled time of trains and buses in a way that prevents high-volume human contact, increases social distance, and reduces the possibility of disease transmission (available at:http://t-ridership.com and GitHub at: https://github.com/Imani-Saba/TRidership).

Project description:BackgroundWorld Health Organization expert groups recommended mortality trials of four repurposed antiviral drugs - remdesivir, hydroxychloroquine, lopinavir, and interferon beta-1a - in patients hospitalized with coronavirus disease 2019 (Covid-19).MethodsWe randomly assigned inpatients with Covid-19 equally between one of the trial drug regimens that was locally available and open control (up to five options, four active and the local standard of care). The intention-to-treat primary analyses examined in-hospital mortality in the four pairwise comparisons of each trial drug and its control (drug available but patient assigned to the same care without that drug). Rate ratios for death were calculated with stratification according to age and status regarding mechanical ventilation at trial entry.ResultsAt 405 hospitals in 30 countries, 11,330 adults underwent randomization; 2750 were assigned to receive remdesivir, 954 to hydroxychloroquine, 1411 to lopinavir (without interferon), 2063 to interferon (including 651 to interferon plus lopinavir), and 4088 to no trial drug. Adherence was 94 to 96% midway through treatment, with 2 to 6% crossover. In total, 1253 deaths were reported (median day of death, day 8; interquartile range, 4 to 14). The Kaplan-Meier 28-day mortality was 11.8% (39.0% if the patient was already receiving ventilation at randomization and 9.5% otherwise). Death occurred in 301 of 2743 patients receiving remdesivir and in 303 of 2708 receiving its control (rate ratio, 0.95; 95% confidence interval [CI], 0.81 to 1.11; P = 0.50), in 104 of 947 patients receiving hydroxychloroquine and in 84 of 906 receiving its control (rate ratio, 1.19; 95% CI, 0.89 to 1.59; P = 0.23), in 148 of 1399 patients receiving lopinavir and in 146 of 1372 receiving its control (rate ratio, 1.00; 95% CI, 0.79 to 1.25; P = 0.97), and in 243 of 2050 patients receiving interferon and in 216 of 2050 receiving its control (rate ratio, 1.16; 95% CI, 0.96 to 1.39; P = 0.11). No drug definitely reduced mortality, overall or in any subgroup, or reduced initiation of ventilation or hospitalization duration.ConclusionsThese remdesivir, hydroxychloroquine, lopinavir, and interferon regimens had little or no effect on hospitalized patients with Covid-19, as indicated by overall mortality, initiation of ventilation, and duration of hospital stay. (Funded by the World Health Organization; ISRCTN Registry number, ISRCTN83971151; ClinicalTrials.gov number, NCT04315948.).

Dataset Information

COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19.

Publications

COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19.

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