使用ai驱动的高性能荧光基板在多个维度上对CYP3A4进行功能成像

IF 11.8 2区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY Small Pub Date : 2025-03-21 DOI:10.1002/smll.202412178
Feng Zhang, Lilin Song, Ruixuan Wang, Bei Zhao, Jian Huang, Luling Wu, Yufan Fan, Hong Lin, Zhengtao Jiang, Xiaodi Yang, Hairong Zeng, Xin Yang, Tony D. James, Guangbo Ge
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引用次数: 0

摘要

细胞色素P450 3A4 (CYP3A4)是异种代谢和药物-药物相互作用(DDI)的关键介质,开发用于生物系统中靶酶的传感和成像的口服活性荧光底物仍然具有挑战性。在这里,人工智能(AI)驱动的策略用于构建高度特异性和口服活性的荧光底物,用于在复杂的生物系统中成像CYP3A4。在ai选择的药物样片段与cyp3a4首选荧光团融合后,设计并合成了三种候选物质。在所有评估的候选药物中,NFa具有优异的同型特异性、超高灵敏度、出色的空间分辨率、良好的安全性和可接受的口服生物利用度。具体来说,NFa在活体系统中具有出色的内质网(ER)共定位性能和高成像分辨率的CYP3A4功能原位成像方面表现出色,同时该药物还可以替代hCYP3A4药物底物,用于CYP3A4抑制剂的高通量筛选和体内DDI潜力评估。在NFa的帮助下,发现了一种新的CYP3A4抑制剂(D13),并在活细胞、离体和体内评估了其抗CYP3A4的作用。总的来说,人工智能驱动的策略适用于开发高度特异性和药物样荧光底物,从而产生第一个用于感知和成像CYP3A4活性的口服可用工具(NFa),这有助于CYP3A4相关的基础研究和药物发现过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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.

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来源期刊
Small
Small 工程技术-材料科学:综合
CiteScore
17.70
自引率
3.80%
发文量
1830
审稿时长
2.1 months
期刊介绍: Small serves as an exceptional platform for both experimental and theoretical studies in fundamental and applied interdisciplinary research at the nano- and microscale. The journal offers a compelling mix of peer-reviewed Research Articles, Reviews, Perspectives, and Comments. With a remarkable 2022 Journal Impact Factor of 13.3 (Journal Citation Reports from Clarivate Analytics, 2023), Small remains among the top multidisciplinary journals, covering a wide range of topics at the interface of materials science, chemistry, physics, engineering, medicine, and biology. Small's readership includes biochemists, biologists, biomedical scientists, chemists, engineers, information technologists, materials scientists, physicists, and theoreticians alike.
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