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使用人工智能驱动的高性能荧光底物对CYP3A4进行多维度功能成像。

Functional Imaging of CYP3A4 at Multiple Dimensions Using an AI-Driven High Performance Fluorogenic Substrate.

作者信息

Zhang Feng, Song Lilin, Wang Ruixuan, Zhao Bei, Huang Jian, Wu Luling, Fan Yufan, Lin Hong, Jiang Zhengtao, Yang Xiaodi, Zeng Hairong, Yang Xin, James Tony D, Ge Guangbo

机构信息

State Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.

Liaoning Provincial Key Laboratory of Carbohydrates, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.

出版信息

Small. 2025 Apr;21(17):e2412178. doi: 10.1002/smll.202412178. Epub 2025 Mar 21.

DOI:10.1002/smll.202412178
PMID:40116533
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12036557/
Abstract

Cytochrome 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.

摘要

细胞色素P450 3A4(CYP3A4)是外源性物质代谢和药物-药物相互作用(DDI)的关键介质,开发用于生物系统中目标酶传感和成像的口服活性荧光底物仍然具有挑战性。在此,采用人工智能(AI)驱动策略构建一种高度特异性且口服活性的荧光底物,用于在复杂生物系统中对CYP3A4进行成像。将AI筛选出的类药物片段与CYP3A4偏好的荧光团融合后,设计并合成了三个候选物。在所有评估的候选物中,NFa表现出优异的同工型特异性、超高灵敏度、出色的空间分辨率、良好的安全性以及可接受的口服生物利用度。具体而言,NFa在活系统中对CYP3A4进行功能性原位成像方面表现出色,具有卓越的内质网(ER)共定位性能和高成像分辨率,同时该试剂还可替代hCYP3A4药物底物用于CYP3A4抑制剂的高通量筛选以及评估体内DDI潜力。借助NFa,发现了一种新型CYP3A4抑制剂(D13),并在活细胞、离体和体内评估了其抗CYP3A4的作用。总体而言,采用人工智能驱动策略开发高度特异性且类药物的荧光底物,从而得到首个可口服的用于传感和成像CYP3A4活性的工具(NFa),这有助于与CYP3A4相关的基础研究和药物发现过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/9237d67fce41/SMLL-21-2412178-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/3c59233e5b54/SMLL-21-2412178-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/34ee1579adeb/SMLL-21-2412178-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/f9784206f693/SMLL-21-2412178-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/5b72869bd06b/SMLL-21-2412178-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/00902d447057/SMLL-21-2412178-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/abb78b5f6a26/SMLL-21-2412178-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/93dd636acfb0/SMLL-21-2412178-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/f7effb03e839/SMLL-21-2412178-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/1e2e0f02362b/SMLL-21-2412178-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/9237d67fce41/SMLL-21-2412178-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/3c59233e5b54/SMLL-21-2412178-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/34ee1579adeb/SMLL-21-2412178-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/f9784206f693/SMLL-21-2412178-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/5b72869bd06b/SMLL-21-2412178-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/00902d447057/SMLL-21-2412178-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/abb78b5f6a26/SMLL-21-2412178-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/93dd636acfb0/SMLL-21-2412178-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/f7effb03e839/SMLL-21-2412178-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/1e2e0f02362b/SMLL-21-2412178-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7609/12036557/9237d67fce41/SMLL-21-2412178-g006.jpg

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本文引用的文献

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J Med Chem. 2023 May 25;66(10):6743-6755. doi: 10.1021/acs.jmedchem.3c00101. Epub 2023 May 5.
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