Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development
SARS-COV-2 has roused the scientific community with a call to action to combat the growing pandemic. At the time of this writing, there are as yet no novel antiviral agents or approved vaccines available for deployment as a frontline defense. Understanding the pathobiology of COVID-19 could aid scie...
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doaj-dc313295629747798bfad07f2859c2802020-11-25T03:41:11ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122020-08-01310.3389/frai.2020.00065560670Artificial Intelligence for COVID-19 Drug Discovery and Vaccine DevelopmentArash Keshavarzi Arshadi0Julia Webb1Milad Salem2Emmanuel Cruz3Stacie Calad-Thomson4Niloofar Ghadirian5Jennifer Collins6Elena Diez-Cecilia7Brendan Kelly8Hani Goodarzi9Jiann Shiun Yuan10Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United StatesBurnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United StatesDepartment of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, United StatesA2A Pharmaceuticals, Cambridge, MA, United StatesAtomwise Inc., San Francisco, CA, United StatesDepartment of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, United StatesBurnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United StatesA2A Pharmaceuticals, Cambridge, MA, United StatesA2A Pharmaceuticals, Cambridge, MA, United StatesDepartment of Biochemistry and Biophysics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, United StatesDepartment of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, United StatesSARS-COV-2 has roused the scientific community with a call to action to combat the growing pandemic. At the time of this writing, there are as yet no novel antiviral agents or approved vaccines available for deployment as a frontline defense. Understanding the pathobiology of COVID-19 could aid scientists in their discovery of potent antivirals by elucidating unexplored viral pathways. One method for accomplishing this is the leveraging of computational methods to discover new candidate drugs and vaccines in silico. In the last decade, machine learning-based models, trained on specific biomolecules, have offered inexpensive and rapid implementation methods for the discovery of effective viral therapies. Given a target biomolecule, these models are capable of predicting inhibitor candidates in a structural-based manner. If enough data are presented to a model, it can aid the search for a drug or vaccine candidate by identifying patterns within the data. In this review, we focus on the recent advances of COVID-19 drug and vaccine development using artificial intelligence and the potential of intelligent training for the discovery of COVID-19 therapeutics. To facilitate applications of deep learning for SARS-COV-2, we highlight multiple molecular targets of COVID-19, inhibition of which may increase patient survival. Moreover, we present CoronaDB-AI, a dataset of compounds, peptides, and epitopes discovered either in silico or in vitro that can be potentially used for training models in order to extract COVID-19 treatment. The information and datasets provided in this review can be used to train deep learning-based models and accelerate the discovery of effective viral therapies.https://www.frontiersin.org/article/10.3389/frai.2020.00065/fullCOVID-19SARS-COV-2drugvaccineartificial intelligencedeep learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arash Keshavarzi Arshadi Julia Webb Milad Salem Emmanuel Cruz Stacie Calad-Thomson Niloofar Ghadirian Jennifer Collins Elena Diez-Cecilia Brendan Kelly Hani Goodarzi Jiann Shiun Yuan |
spellingShingle |
Arash Keshavarzi Arshadi Julia Webb Milad Salem Emmanuel Cruz Stacie Calad-Thomson Niloofar Ghadirian Jennifer Collins Elena Diez-Cecilia Brendan Kelly Hani Goodarzi Jiann Shiun Yuan Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development Frontiers in Artificial Intelligence COVID-19 SARS-COV-2 drug vaccine artificial intelligence deep learning |
author_facet |
Arash Keshavarzi Arshadi Julia Webb Milad Salem Emmanuel Cruz Stacie Calad-Thomson Niloofar Ghadirian Jennifer Collins Elena Diez-Cecilia Brendan Kelly Hani Goodarzi Jiann Shiun Yuan |
author_sort |
Arash Keshavarzi Arshadi |
title |
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development |
title_short |
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development |
title_full |
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development |
title_fullStr |
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development |
title_full_unstemmed |
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development |
title_sort |
artificial intelligence for covid-19 drug discovery and vaccine development |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Artificial Intelligence |
issn |
2624-8212 |
publishDate |
2020-08-01 |
description |
SARS-COV-2 has roused the scientific community with a call to action to combat the growing pandemic. At the time of this writing, there are as yet no novel antiviral agents or approved vaccines available for deployment as a frontline defense. Understanding the pathobiology of COVID-19 could aid scientists in their discovery of potent antivirals by elucidating unexplored viral pathways. One method for accomplishing this is the leveraging of computational methods to discover new candidate drugs and vaccines in silico. In the last decade, machine learning-based models, trained on specific biomolecules, have offered inexpensive and rapid implementation methods for the discovery of effective viral therapies. Given a target biomolecule, these models are capable of predicting inhibitor candidates in a structural-based manner. If enough data are presented to a model, it can aid the search for a drug or vaccine candidate by identifying patterns within the data. In this review, we focus on the recent advances of COVID-19 drug and vaccine development using artificial intelligence and the potential of intelligent training for the discovery of COVID-19 therapeutics. To facilitate applications of deep learning for SARS-COV-2, we highlight multiple molecular targets of COVID-19, inhibition of which may increase patient survival. Moreover, we present CoronaDB-AI, a dataset of compounds, peptides, and epitopes discovered either in silico or in vitro that can be potentially used for training models in order to extract COVID-19 treatment. The information and datasets provided in this review can be used to train deep learning-based models and accelerate the discovery of effective viral therapies. |
topic |
COVID-19 SARS-COV-2 drug vaccine artificial intelligence deep learning |
url |
https://www.frontiersin.org/article/10.3389/frai.2020.00065/full |
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