在真菌中揭示III型多基合成酶的功能多样性
Nika Sokolova1, Stepan S Denisov2, Thomas Hackl3
1Department of Chemical and Pharmaceutical Biology, University of Groningen, Antonius Deusinglaan 1, Groningen, 9713AV, The Netherlands.
Angewandte Chemie (International ed. in English)
|September 4, 2025
概括
我们开发了一种新方法来描述真菌III型多基合成酶 (T3PKS), 发现了新的酶特异性, 并创建了一个用于预测其活性的机器学习模型.
科学领域:
- 生物化学和分子生物学
- 酵素学
- 生物信息学
背景情况:
- 第三类多基合成酶 (T3PKS) 是产生生态和临床相关的多种化合物的关键酶.
- 虽然在植物中进行了广泛的研究,但真菌T3PKS在很大程度上仍然没有特征,这限制了我们对其潜力的理解.
- 需要一个全面的方法来探索真菌T3PKS的巨大酶潜力.
研究的目的:
- 建立一个全域的工作流程来描述真菌III型多基合成酶 (T3PKSs).
- 研究真菌T3PKS的基质特异性和产品范围.
- 开发T3PKS活动的预测机器学习模型并识别新型酶.
主要方法:
- 从公众的真菌基因组中采集超过1000个假定T3PKS酶的生物信息.
- 对酶活性部位结构和基因组邻域的分析.
- 用各种基质对37种代表性T3PKS候选物进行无细胞表达和原型化.
- 使用生成的酶基质对数据进行特异性预测的机器学习模型开发.
- 用自然和非自然基质对模型进行实验验证.
主要成果:
- 在特征的真菌T3PKS中识别独特的基质和循环特异性.
- 确定不同酶的首选malonyl-Coenzyme A扩展号.
- 开发和成功验证用于预测T3PKS基质特异性的机器学习模型.
- 使用预测模型在真菌中发现了两个额外的乱交T3PKS.
结论:
- 开发的工作流程可以全面描述真菌T3PKS.
- 机器学习模型为T3PKS的选和发现提供了强大的工具.
- 对真菌T3PKS产品范围的洞察为自然产品发现和合成生物学应用提供了有价值的起点.
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