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Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2
A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world economy. Indeed, following the emergence of this new vir...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172298/ https://www.ncbi.nlm.nih.gov/pubmed/34124259 http://dx.doi.org/10.1155/2021/6696012 |
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author | Yassine, Rabhi Makrem, Mrabet Farhat, Fnaiech |
author_facet | Yassine, Rabhi Makrem, Mrabet Farhat, Fnaiech |
author_sort | Yassine, Rabhi |
collection | PubMed |
description | A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world economy. Indeed, following the emergence of this new virus, despite the existence of a few approved and known effective vaccines at the time of writing this original study, a sense of urgency has emerged worldwide to discover new technical tools and new drugs as soon as possible. In this context, many studies and researches are currently underway to develop new tools and therapies against SARS CoV-2 and other viruses, using different approaches. The 3-chymotrypsin (3CL) protease, which is directly involved in the cotranslational and posttranslational modifications of viral polyproteins essential for the existence and replication of the virus in the host, is one of the coronavirus target proteins that has been the subject of these extensive studies. Currently, the majority of these studies are aimed at repurposing already known and clinically approved drugs against this new virus, but this approach is not really successful. Recently, different studies have successfully demonstrated the effectiveness of artificial intelligence-based techniques to understand existing chemical spaces and generate new small molecules that are both effective and efficient. In this framework and for our study, we combined a generative recurrent neural network model with transfer learning methods and active learning-based algorithms to design novel small molecules capable of effectively inhibiting the 3CL protease in human cells. We then analyze these small molecules to find the correct binding site that matches the structure of the 3CL protease of our target virus as well as other analyses performed in this study. Based on these screening results, some molecules have achieved a good binding score close to -18 kcal/mol, which we can consider as good potential candidates for further synthesis and testing against SARS-CoV-2. |
format | Online Article Text |
id | pubmed-8172298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-81722982021-06-11 Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 Yassine, Rabhi Makrem, Mrabet Farhat, Fnaiech Biomed Res Int Research Article A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world economy. Indeed, following the emergence of this new virus, despite the existence of a few approved and known effective vaccines at the time of writing this original study, a sense of urgency has emerged worldwide to discover new technical tools and new drugs as soon as possible. In this context, many studies and researches are currently underway to develop new tools and therapies against SARS CoV-2 and other viruses, using different approaches. The 3-chymotrypsin (3CL) protease, which is directly involved in the cotranslational and posttranslational modifications of viral polyproteins essential for the existence and replication of the virus in the host, is one of the coronavirus target proteins that has been the subject of these extensive studies. Currently, the majority of these studies are aimed at repurposing already known and clinically approved drugs against this new virus, but this approach is not really successful. Recently, different studies have successfully demonstrated the effectiveness of artificial intelligence-based techniques to understand existing chemical spaces and generate new small molecules that are both effective and efficient. In this framework and for our study, we combined a generative recurrent neural network model with transfer learning methods and active learning-based algorithms to design novel small molecules capable of effectively inhibiting the 3CL protease in human cells. We then analyze these small molecules to find the correct binding site that matches the structure of the 3CL protease of our target virus as well as other analyses performed in this study. Based on these screening results, some molecules have achieved a good binding score close to -18 kcal/mol, which we can consider as good potential candidates for further synthesis and testing against SARS-CoV-2. Hindawi 2021-05-25 /pmc/articles/PMC8172298/ /pubmed/34124259 http://dx.doi.org/10.1155/2021/6696012 Text en Copyright © 2021 Rabhi Yassine et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Yassine, Rabhi Makrem, Mrabet Farhat, Fnaiech Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 |
title | Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 |
title_full | Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 |
title_fullStr | Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 |
title_full_unstemmed | Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 |
title_short | Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2 |
title_sort | active learning and the potential of neural networks accelerate molecular screening for the design of a new molecule effective against sars-cov-2 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172298/ https://www.ncbi.nlm.nih.gov/pubmed/34124259 http://dx.doi.org/10.1155/2021/6696012 |
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