ArticleBiomolecules2022
Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model.
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models.Database : the journal of biological databases and curation · 2025Pooled it
- Emerging role of artificial intelligence in therapeutics for COVID-19: a systematic review.Journal of biomolecular structure & dynamics · 2022Pooled it
- Pooled it
- Advances in Drug Design and Development for Human Therapeutics Using Artificial Intelligence-II.Biomolecules · 2023Article
- Application of big data and artificial intelligence in epidemic surveillance and containment.Intelligent medicine · 2023Review
- A review of SARS-CoV-2 drug repurposing: databases and machine learning models.Frontiers in pharmacology · 2023Review
- Using Artificial Intelligence for Drug Discovery: A Bibliometric Study and Future Research Agenda.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Review on the COVID-19 pandemic prevention and control system based on AI.Engineering applications of artificial intelligence · 2022Review
- A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2022Review
- Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2.Chemical reviews · 2022Review
- Covid-19 and Artificial Intelligence: Genome sequencing, drug development and vaccine discovery.Journal of infection and public health · 2022Review
- A novel statistical method predicts mutability of the genomic segments of the SARS-CoV-2 virus.QRB discovery · 2022Article
- A novel framework integrating AI model and enzymological experiments promotes identification of SARS-CoV-2 3CL protease inhibitors and activity-based probe.Briefings in bioinformatics · 2021Article
- Investigating the binding affinity, interaction, and structure-activity-relationship of 76 prescription antiviral drugs targeting RdRp and Mpro of SARS-CoV-2.Journal of biomolecular structure & dynamics · 2021Article
- Exploring the interaction of quercetin-3-O-sophoroside with SARS-CoV-2 main proteins by theoretical studies: A probable prelude to control some variants of coronavirus including Delta.Arabian journal of chemistry · 2021Article
- An update on novel approaches for diagnosis and treatment of SARS-CoV-2 infection.Cell & bioscience · 2021Review
- A review on the interaction of nucleoside analogues with SARS-CoV-2 RNA dependent RNA polymerase.International journal of biological macromolecules · 2021Review
- Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance.Journal of biomedical informatics · 2021Article
- Scope of adjuvant therapy using roflumilast, a PDE-4 inhibitor against COVID-19.Pulmonary pharmacology & therapeutics · 2021Review
- Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions.International journal of environmental research and public health · 2021Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The outbreak of COVID-19 caused millions of deaths worldwide, and the number of total infections is still rising. It is necessary to identify some potentially effective drugs that can be used to prevent the development of severe symptoms, or even death for those infected. Fortunately, many efforts have been made and several effective drugs have been identified. The rapidly increasing amount of data is of great help for training an effective and specific deep learning model. In this study, we propose a multi-task deep learning model for the purpose of screening commercially available and effective inhibitors against SARS-CoV-2. First, we pretrained a model on several heterogenous protein-ligand interaction datasets. The model achieved competitive results on some benchmark datasets. Next, a coronavirus-specific dataset was collected and used to fine-tune the model. Then, the fine-tuned model was used to select commercially available drugs against SARS-CoV-2 protein targets. Overall, twenty compounds were listed as potential inhibitors. We further explored the model interpretability and exhibited the predicted important binding sites. Based on this prediction, molecular docking was also performed to visualize the binding modes of the selected inhibitors.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.