Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1)
Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identified several existing drugs with potential to combat SARS-CoV-2. However, moving these hits fo...
| Autores principales: | , , , |
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| Formato: | Preimpreso |
| Lenguaje: | Español |
| Publicado: |
Cambridge University Press. ChemRxiv
2021
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/11086/20029 https://chemrxiv.org/engage/chemrxiv/article-details/60d4e352e211334430e0a008 |
| Aporte de: |
| id |
I10-R14111086-20029 |
|---|---|
| record_format |
dspace |
| institution |
Universidad Nacional de Córdoba |
| institution_str |
I-10 |
| repository_str |
R-141 |
| collection |
Repositorio Digital Universitario (UNC) |
| language |
Español |
| topic |
Covid 19 SARS-CoV-2 High-throughput Inverse docking Docking software |
| spellingShingle |
Covid 19 SARS-CoV-2 High-throughput Inverse docking Docking software Ribone, Sergio P. Paz, S. Alexis Abrams, Cameron F. Villarreal, Marcos A. Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1) |
| topic_facet |
Covid 19 SARS-CoV-2 High-throughput Inverse docking Docking software |
| description |
Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identified several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifically against this pathogen requires unambiguous identification of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank order targets for each of several existing drugs for which a plurality of recent hight-hroughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets. |
| format |
Preimpreso |
| author |
Ribone, Sergio P. Paz, S. Alexis Abrams, Cameron F. Villarreal, Marcos A. |
| author_facet |
Ribone, Sergio P. Paz, S. Alexis Abrams, Cameron F. Villarreal, Marcos A. |
| author_sort |
Ribone, Sergio P. |
| title |
Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1) |
| title_short |
Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1) |
| title_full |
Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1) |
| title_fullStr |
Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1) |
| title_full_unstemmed |
Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking (version 1) |
| title_sort |
target identification for repurposed drugs active against sars-cov-2 via high-throughput inverse docking (version 1) |
| publisher |
Cambridge University Press. ChemRxiv |
| publishDate |
2021 |
| url |
http://hdl.handle.net/11086/20029 https://chemrxiv.org/engage/chemrxiv/article-details/60d4e352e211334430e0a008 |
| work_keys_str_mv |
AT ribonesergiop targetidentificationforrepurposeddrugsactiveagainstsarscov2viahighthroughputinversedockingversion1 AT pazsalexis targetidentificationforrepurposeddrugsactiveagainstsarscov2viahighthroughputinversedockingversion1 AT abramscameronf targetidentificationforrepurposeddrugsactiveagainstsarscov2viahighthroughputinversedockingversion1 AT villarrealmarcosa targetidentificationforrepurposeddrugsactiveagainstsarscov2viahighthroughputinversedockingversion1 |
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Repositorios |
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