Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candida...
Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease
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Publisher
Switzerland: MDPI AG
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Language
English
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Publisher
Switzerland: MDPI AG
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In this study, we utilized machine learning techniques to identify potential inhibitors of the MERS-CoV 3CL protease. Among the models evaluated, the Random Forest (RF) algorithm exhibited the highest predictive performance, achieving an accuracy of 0.97, an ROC-AUC score of 0.98, and an F1-score of 0.98. Following model validation, we applied it t...
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Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11988297
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11988297
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ISSN
1422-0067,1661-6596
E-ISSN
1422-0067
DOI
10.3390/ijms26073047
