MEN: leveraging explainable multimodal encoding network for precision prediction of CYP450 inhibitors

MEN: leveraging explainable multimodal encoding network for precision prediction of CYP450 inhibitors

Abstract Drug–drug interactions (DDIs) present serious risks in clinical settings, especially for patients who are prescribed multiple medications. A major factor contributing to these interactions is the inhibition of cytochrome P450 (CYP450) enzymes, which are vital for drug metabolism. As a resul...

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Main Authors: Abena Achiaa Atwereboannah, Wei-Ping Wu, Mugahed A. Al-antari, Sophyani B. Yussif, Chukwuebuka J. Ejiyi, Edwin K. Tenagyei, Grace-Mercure B. Kissanga, Gyarteng S. A. Emmanuel, Yeong Hyeon Gu, Emmanuel Ahene
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Inhibitor
Cytochrome P450
Residual multi local attention (ReMLA)
Attentive hierarchical graph isomorphism network (AHGIN)
Self-attention
Interpretable artificial intelligence (IAI)
Online Access:https://doi.org/10.1038/s41598-025-04982-6
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https://doi.org/10.1038/s41598-025-04982-6

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