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Discovery of new drug indications for COVID-19: A drug repurposing approach

MOTIVATION: The outbreak of coronavirus health issues caused by COVID-19(SARS-CoV-2) creates a global threat to public health. Therefore, there is a need for effective remedial measures using existing and approved therapies with proven safety measures has several advantages. Dexamethasone (Pubchem I...

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Autores principales: Kumari, Priyanka, Pradhan, Bikram, Koromina, Maria, Patrinos, George P., Steen, Kristel Van
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129022/
https://www.ncbi.nlm.nih.gov/pubmed/35609015
http://dx.doi.org/10.1371/journal.pone.0267095
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author Kumari, Priyanka
Pradhan, Bikram
Koromina, Maria
Patrinos, George P.
Steen, Kristel Van
author_facet Kumari, Priyanka
Pradhan, Bikram
Koromina, Maria
Patrinos, George P.
Steen, Kristel Van
author_sort Kumari, Priyanka
collection PubMed
description MOTIVATION: The outbreak of coronavirus health issues caused by COVID-19(SARS-CoV-2) creates a global threat to public health. Therefore, there is a need for effective remedial measures using existing and approved therapies with proven safety measures has several advantages. Dexamethasone (Pubchem ID: CID0000005743), baricitinib(Pubchem ID: CID44205240), remdesivir (PubchemID: CID121304016) are three generic drugs that have demonstrated in-vitro high antiviral activity against SARS-CoV-2. The present study aims to widen the search and explore the anti-SARS-CoV-2 properties of these potential drugs while looking for new drug indications with optimised benefits via in-silico research. METHOD: Here, we designed a unique drug-similarity model to repurpose existing drugs against SARS-CoV-2, using the anti-Covid properties of dexamethasone, baricitinib, and remdesivir as references. Known chemical-chemical interactions of reference drugs help extract interactive compounds withimprovedanti-SARS-CoV-2 properties. Here, we calculated the likelihood of these drug compounds treating SARS-CoV-2 related symptoms using chemical-protein interactions between the interactive compounds of the reference drugs and SARS-CoV-2 target genes. In particular, we adopted a two-tier clustering approach to generate a drug similarity model for the final selection of potential anti-SARS-CoV-2 drug molecules. Tier-1 clustering was based on t-Distributed Stochastic Neighbor Embedding (t-SNE) and aimed to filter and discard outlier drugs. The tier-2 analysis incorporated two cluster analyses performed in parallel using Ordering Points To Identify the Clustering Structure (OPTICS) and Hierarchical Agglomerative Clustering (HAC). As a result, itidentified clusters of drugs with similar actions. In addition, we carried out a docking study for in-silico validation of top candidate drugs. RESULT: Our drug similarity model highlighted ten drugs, including reference drugs that can act as potential therapeutics against SARS-CoV-2. The docking results suggested that doxorubicin showed the least binding energy compared to reference drugs. Their practical utility as anti-SARS-CoV-2 drugs, either individually or in combination, warrants further investigation.
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spelling pubmed-91290222022-05-25 Discovery of new drug indications for COVID-19: A drug repurposing approach Kumari, Priyanka Pradhan, Bikram Koromina, Maria Patrinos, George P. Steen, Kristel Van PLoS One Research Article MOTIVATION: The outbreak of coronavirus health issues caused by COVID-19(SARS-CoV-2) creates a global threat to public health. Therefore, there is a need for effective remedial measures using existing and approved therapies with proven safety measures has several advantages. Dexamethasone (Pubchem ID: CID0000005743), baricitinib(Pubchem ID: CID44205240), remdesivir (PubchemID: CID121304016) are three generic drugs that have demonstrated in-vitro high antiviral activity against SARS-CoV-2. The present study aims to widen the search and explore the anti-SARS-CoV-2 properties of these potential drugs while looking for new drug indications with optimised benefits via in-silico research. METHOD: Here, we designed a unique drug-similarity model to repurpose existing drugs against SARS-CoV-2, using the anti-Covid properties of dexamethasone, baricitinib, and remdesivir as references. Known chemical-chemical interactions of reference drugs help extract interactive compounds withimprovedanti-SARS-CoV-2 properties. Here, we calculated the likelihood of these drug compounds treating SARS-CoV-2 related symptoms using chemical-protein interactions between the interactive compounds of the reference drugs and SARS-CoV-2 target genes. In particular, we adopted a two-tier clustering approach to generate a drug similarity model for the final selection of potential anti-SARS-CoV-2 drug molecules. Tier-1 clustering was based on t-Distributed Stochastic Neighbor Embedding (t-SNE) and aimed to filter and discard outlier drugs. The tier-2 analysis incorporated two cluster analyses performed in parallel using Ordering Points To Identify the Clustering Structure (OPTICS) and Hierarchical Agglomerative Clustering (HAC). As a result, itidentified clusters of drugs with similar actions. In addition, we carried out a docking study for in-silico validation of top candidate drugs. RESULT: Our drug similarity model highlighted ten drugs, including reference drugs that can act as potential therapeutics against SARS-CoV-2. The docking results suggested that doxorubicin showed the least binding energy compared to reference drugs. Their practical utility as anti-SARS-CoV-2 drugs, either individually or in combination, warrants further investigation. Public Library of Science 2022-05-24 /pmc/articles/PMC9129022/ /pubmed/35609015 http://dx.doi.org/10.1371/journal.pone.0267095 Text en © 2022 Kumari et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kumari, Priyanka
Pradhan, Bikram
Koromina, Maria
Patrinos, George P.
Steen, Kristel Van
Discovery of new drug indications for COVID-19: A drug repurposing approach
title Discovery of new drug indications for COVID-19: A drug repurposing approach
title_full Discovery of new drug indications for COVID-19: A drug repurposing approach
title_fullStr Discovery of new drug indications for COVID-19: A drug repurposing approach
title_full_unstemmed Discovery of new drug indications for COVID-19: A drug repurposing approach
title_short Discovery of new drug indications for COVID-19: A drug repurposing approach
title_sort discovery of new drug indications for covid-19: a drug repurposing approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129022/
https://www.ncbi.nlm.nih.gov/pubmed/35609015
http://dx.doi.org/10.1371/journal.pone.0267095
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