Machine learning prediction of intestinal α-glucosidase inhibitors using a diverse set of ligands: a drug repurposing effort with drugBank database screening

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Journal
In Silico Pharmacology
Published
2025-06-25
DOI
https://doi.org/10.1007/s40203-025-00384-8
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Machine learning prediction of intestinal α-glucosidase inhibitors using a diverse set of ligands: a drug repurposing effort with drugBank database screening

Samuel Egieyeh, Clement Nyirenda, Adeshina I. Odugbemi, Alan Christoffels
In Silico Pharmacology
Computational Drug Discovery Methods
article

Machine learning prediction of intestinal α-glucosidase inhibitors using a diverse set of ligands: a drug repurposing effort with drugBank database screening

Samuel Egieyeh, Clement Nyirenda, Adeshina I. Odugbemi, Alan Christoffels
article en

Abstract

No abstract available for this paper.
In Silico PharmacologyVol. 13(2)
South African Medical Research Council (ZA), National Institute for Theoretical Physics (ZA), University of the Western Cape (ZA)
National Research Foundation, Department of Science and Technology, Ministry of Science and Technology, India, University of the Western Cape, Center for High Performance Computing
Good health and well-being
Openalex Percentile: Top 84%
Computational Drug Discovery Methods
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