Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy

Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy

Abstract For understanding a chemical compound’s mechanism of action and its side effects, as well as for drug discovery, it is crucial to predict its possible protein targets. This study examines 15 developed target-centric models (TCM) employing different molecular descriptions and machine learnin...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Karina Jimenes-Vargas, Alejandro Pazos, Cristian R. Munteanu, Yunierkis Perez-Castillo, Eduardo Tejera
Aineistotyyppi: Artikkeli
Kieli:English
Julkaistu: BMC 2024-03-01
Sarja:Journal of Cheminformatics
Aiheet:
Target identification
Target fishing
Ligan-based modeling
Machine learning
QSAR
Linkit:https://doi.org/10.1186/s13321-024-00816-1

Internet

https://doi.org/10.1186/s13321-024-00816-1

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