Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence

The widespread infection caused by the 2019 novel corona virus (SARS-CoV-2) has initiated global efforts to search for antiviral agents. Drug discovery is the first step in the development of commercially viable pharmaceutical products to deal with novel diseases. In an effort to accelerate the scre...

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Main Author: Janairo, Gabriela Ilona B.
Format: text
Language:English
Published: Animo Repository 2021
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Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/5946
https://animorepository.dlsu.edu.ph/context/etd_masteral/article/12985/viewcontent/Janairo_Gabriela_Ilona_11885629__Screening_and_Design_of_Potential_SARS_CoV_2_Partial.pdf
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_masteral-129852022-04-27T07:49:00Z Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence Janairo, Gabriela Ilona B. The widespread infection caused by the 2019 novel corona virus (SARS-CoV-2) has initiated global efforts to search for antiviral agents. Drug discovery is the first step in the development of commercially viable pharmaceutical products to deal with novel diseases. In an effort to accelerate the screening and drug discovery workflow for potential SARS-CoV-2 protease inhibitors, a machine learning model that can predict the binding free energies of compounds to the SARS-CoV-2 main protease is presented. The regression model, which was trained and tested on 226 compounds demonstrates reliable prediction performance (r2 test = 0.81, RMSE test = 0.43), while only requiring five topological descriptors. The externally validated model can help conserve and maximize available resources by limiting biological assays to compounds that yielded favorable outcomes from the model. Moreover, the model was used to design molecular modifications on the compound rutin to enhance its binding activity with the main protease. The emergence of highly infectious diseases will always be a threat to human health and development, which is why the development of computational tools for rapid response is very important. 2021-02-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_masteral/5946 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/12985/viewcontent/Janairo_Gabriela_Ilona_11885629__Screening_and_Design_of_Potential_SARS_CoV_2_Partial.pdf Master's Theses English Animo Repository COVID-19 (Disease) Antiviral agents Chemistry
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic COVID-19 (Disease)
Antiviral agents
Chemistry
spellingShingle COVID-19 (Disease)
Antiviral agents
Chemistry
Janairo, Gabriela Ilona B.
Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence
description The widespread infection caused by the 2019 novel corona virus (SARS-CoV-2) has initiated global efforts to search for antiviral agents. Drug discovery is the first step in the development of commercially viable pharmaceutical products to deal with novel diseases. In an effort to accelerate the screening and drug discovery workflow for potential SARS-CoV-2 protease inhibitors, a machine learning model that can predict the binding free energies of compounds to the SARS-CoV-2 main protease is presented. The regression model, which was trained and tested on 226 compounds demonstrates reliable prediction performance (r2 test = 0.81, RMSE test = 0.43), while only requiring five topological descriptors. The externally validated model can help conserve and maximize available resources by limiting biological assays to compounds that yielded favorable outcomes from the model. Moreover, the model was used to design molecular modifications on the compound rutin to enhance its binding activity with the main protease. The emergence of highly infectious diseases will always be a threat to human health and development, which is why the development of computational tools for rapid response is very important.
format text
author Janairo, Gabriela Ilona B.
author_facet Janairo, Gabriela Ilona B.
author_sort Janairo, Gabriela Ilona B.
title Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence
title_short Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence
title_full Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence
title_fullStr Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence
title_full_unstemmed Screening and design of potential SARS-CoV-2 inhibitors through chemical artificial intelligence
title_sort screening and design of potential sars-cov-2 inhibitors through chemical artificial intelligence
publisher Animo Repository
publishDate 2021
url https://animorepository.dlsu.edu.ph/etd_masteral/5946
https://animorepository.dlsu.edu.ph/context/etd_masteral/article/12985/viewcontent/Janairo_Gabriela_Ilona_11885629__Screening_and_Design_of_Potential_SARS_CoV_2_Partial.pdf
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