ArticleNetwork modeling and analysis in health informatics and bioinformatics2021
A machine learning regression model for the screening and design of potential SARS-CoV-2 protease inhibitors.
Article in Network modeling and analysis in health informatics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Machine learning guided virtual screening of FDA approved drugs targeting GSK-3β in Alzheimer's disease.Scientific reports · 2025Article
- Bioactive compound identification without fractionation: an Ocimum spp. case study.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Reproductive Toxicity Effects of Phthalates Based on the Hypothalamic-Pituitary-Gonadal Axis: A Priority Control List Construction from Theoretical Methods.International journal of molecular sciences · 2025Article
- Herbal Medicine Usage During the COVID-19 Pandemic in Indonesia: Trends and Determinants.TheScientificWorldJournal · 2025Article
- The Experimentalist's Guide to Machine Learning for Small Molecule Design.ACS applied bio materials · 2024Review
- Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- Herbal Remedies, Nutraceuticals, and Dietary Supplements for COVID-19 Management: An Update.Clinical complementary medicine and pharmacology · 2022Review
- Generating novel molecule for target protein (SARS-CoV-2) using drug-target interaction based on graph neural network.Network modeling and analysis in health informatics and bioinformatics · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 optimized multiple linear regression model, which was trained and tested on 226 natural compounds demonstrates reliable prediction performance ( SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13721-021-00326-2.
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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.