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Sci Adv ; 7(27)2021 06.
Article in English | MEDLINE | ID: covidwho-1290607


The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates the rapid development of new therapies against coronavirus disease 2019 (COVID-19) infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein network, based on disease signatures defined by COVID-19 multiomics datasets, and cross-examined these pathways against approved drugs. This analysis identified 200 drugs predicted to target SARS-CoV-2-induced pathways, 40 of which are already in COVID-19 clinical trials, testifying to the validity of the approach. Using artificial neural network analysis, we classified these 200 drugs into nine distinct pathways, within two overarching mechanisms of action (MoAs): viral replication (126) and immune response (74). Two drugs (proguanil and sulfasalazine) implicated in viral replication were shown to inhibit replication in cell assays. This unbiased and validated analysis opens new avenues for the rapid repurposing of approved drugs into clinical trials.

Drug Repositioning , SARS-CoV-2/physiology , Antiviral Agents/metabolism , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/pathology , COVID-19/virology , Humans , Neural Networks, Computer , Proguanil/pharmacology , Proguanil/therapeutic use , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Sulfasalazine/pharmacology , Virus Replication/drug effects
Adv Drug Deliv Rev ; 172: 249-274, 2021 05.
Article in English | MEDLINE | ID: covidwho-1064699


SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.

COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Computational Biology/methods , Drug Development/methods , SARS-CoV-2/drug effects , Animals , B-Lymphocytes/drug effects , B-Lymphocytes/immunology , COVID-19/genetics , COVID-19/immunology , COVID-19 Vaccines/genetics , COVID-19 Vaccines/immunology , Computational Biology/trends , Drug Development/trends , Epitopes/genetics , Epitopes/immunology , Gene Expression Profiling/methods , Gene Expression Profiling/trends , Humans , SARS-CoV-2/genetics , SARS-CoV-2/metabolism