Functional imaging of CYP3A4 at multiple dimensions using an AI‐driven high performance fluorogenic substrate

Zhang, Feng, Song, Lilin, Wang, Ruixuan, Zhao, Bei, Huang, Jian, Wu, Luling, Fan, Yufan, Lin, Hong, Jiang, Zhengtao, Yang, Xiaodi, Zeng, Hairong, Yang, Xin ORCID: https://orcid.org/0000-0002-8429-7598, James, Tony D. and Ge, Guangbo 2025. Functional imaging of CYP3A4 at multiple dimensions using an AI‐driven high performance fluorogenic substrate. Small , 2412178. 10.1002/smll.202412178

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Abstract

AbstractCytochrome P450 3A4 (CYP3A4) is a key mediator in xenobiotic metabolism and drug‐drug interactions (DDI), developing orally active fluorogenic substrates for sensing and imaging of a target enzyme in biological systems remains challenging. Here, an artificial intelligence (AI)‐driven strategy is used to construct a highly specific and orally active fluorogenic substrate for imaging CYP3A4 in complex biological systems. After the fusion of an AI‐selected drug‐like fragment with a CYP3A4‐preferred fluorophore, three candidates are designed and synthesized. Among all evaluated candidates, NFa exhibits excellent isoform‐specificity, ultra‐high sensitivity, outstanding spatial resolution, favorable safety profiles, and acceptable oral bioavailability. Specifically, NFa excels at functional in situ imaging of CYP3A4 in living systems with exceptional endoplasmic reticulum (ER)‐colocalization performance and high imaging resolution, while this agent can also replace hCYP3A4 drug‐substrates for high‐throughput screening of CYP3A4 inhibitors and for assessing DDI potential in vivo. With the help of NFa, a novel CYP3A4 inhibitor (D13) was discovered, and its anti‐CYP3A4 effects are assessed in live cells, ex vivo and in vivo. Collectively, an AI‐powered strategy is adapted for developing highly‐specific and drug‐like fluorogenic substrates, resulting in the first orally available tool (NFa) for sensing and imaging CYP3A4 activities, which facilitates CYP3A4‐associated fundamental investigations and the drug discovery process.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Engineering
Publisher:	Wiley
ISSN:	1613-6810
Date of First Compliant Deposit:	1 April 2025
Date of Acceptance:	18 March 2025
Last Modified:	02 Apr 2025 13:23
URI:	https://orca.cardiff.ac.uk/id/eprint/177318

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