Characterizing ABC-transporter substrate-likeness using a clean-slate genetic background

Sokolov, Artem and Ashenden, Stephanie and Şahin, Nil and Lewis, Richard and Erdem, Nurdan and Ozaltan, Elif and Bender, Andreas and Roth, Frederick P. and Çokol, Murat (2019) Characterizing ABC-transporter substrate-likeness using a clean-slate genetic background. Frontiers in Pharmacology, 10 . ISSN 1663-9812

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Mutations in ATP Binding Cassette (ABC)-transporter genes can have major effects on the bioavailability and toxicity of the drugs that are ABC-transporter substrates. Consequently, methods to predict if a drug is an ABC-transporter substrate are useful for drug development. Such methods traditionally relied on literature curated collections of ABC-transporter dependent membrane transfer assays. Here, we used a single large-scale dataset of 376 drugs with relative efficacy on an engineered yeast strain with all ABC-transporter genes deleted (ABC-16), to explore the relationship between a drug's chemical structure and ABC-transporter substrate-likeness. We represented a drug's chemical structure by an array of substructure keys and explored several machine learning methods to predict the drug's efficacy in an ABC-16 yeast strain. Gradient-Boosted Random Forest models outperformed all other methods with an AUC of 0.723. We prospectively validated the model using new experimental data and found significant agreement with predictions. Our analysis expands the previously reported chemical substructures associated with ABC-transporter substrates and provides an alternative means to investigate ABC-transporter substrate-likeness.
Item Type: Article
Uncontrolled Keywords: ABC transport protein; Cheminformatics; Drug structure; Machine learning; Membrane transport
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Murat Çokol
Date Deposited: 24 Jul 2023 15:22
Last Modified: 24 Jul 2023 15:22

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