使用FAALPred预测FAAL酶的多样性及其基质特异性的预测
Anne Liong1,2, Leandro de Mattos Pereira1, Pedro N Leão1
1Interdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Matosinhos, Portugal.
Protein science : a publication of the Protein Society
|January 21, 2026
概括
脂肪乙-AMP连接酶 (FAALs) 对于二次代谢物产生至关重要. 一个新的AI工具FAALPred准确地预测了FAAL酶激活的脂肪酸链长度,有助于发现代谢物.
科学领域:
- 生物化学和分子生物学
- 生物信息学和计算生物学
背景情况:
- 脂肪酸-AMP酶 (FAALs) 是二次代谢物生物合成中的关键酶,负责招募和纳入脂肪酸.
- 对FAALs的多样性,分布和基质特异性尚不清楚,这阻碍了从序列数据中进行功能预测.
研究的目的:
- 在各种生命形式中调查FAAL酶的流行和多样性.
- 开发FAAL基质特异性的预测工具,特别是脂肪酸链长度.
主要方法:
- 通过使用序列数据,探索整个生命树的FAAL分布.
- 开发一个生物信息学和人工智能 (AI) 工作流程,FAALPred,用于预测FAAL基质链长度.
- 使用独立的 in vitro 和 in silico 数据集验证FAALPred.
主要成果:
- FAALs分布广泛,特别是在与二次代谢物产生相关的细菌中,通常与多基基和非核糖体通路有关.
- 在古生物和真核生物体中也发现了FAAL.
- 遗传学分析与活性脂肪酸链长度没有相关性,突出显示了对预测工具的需求.
结论:
- FAALPred准确地预测了FAAL酶的脂肪酸链长度特异性.
- 预计该工具将加速二次代谢物的发现和结构预测.
- FAALPred还可以促进脂化过程的工程.
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