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使用ProteinMPNNN重新设计一种与黄素结合的光蛋白

Andrey Nikolaev¹, Alexander Kuzmin¹, Elena Markeeva¹

¹Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.

Protein science : a publication of the Protein Society

|March 19, 2024

概括

机器学习蛋白质设计工具 ProteinMPNN 成功重新设计了一种光蛋白. 经过重新设计的蛋白质保留了flavin mononucleotide结合和光,证明了它对蛋白质工程的广泛适用性.

科学领域:

蛋白质工程是一种蛋白质工程.
计算生物学是一种计算生物学.
生物化学生物化学

背景情况:

机器学习的进步使新的蛋白质设计和工程方法成为可能.
蛋白MPNN是一种工具,可以预测用户定义的蛋白质结构的氨基酸序列.
之前的ProteinMPNN应用程序专注于标准蛋白和结合蛋白.

研究的目的:

评估ProteinMPNN在改造非蛋白质性联结蛋白的有效性,特别是基于黄素的光蛋白CagFbFP.
评估ProteinMPNN是否可以产生光蛋白的功能变体,同时保持连接体结合能力.

主要方法:

保持了CagFbFP的本地脊柱.
对于弗拉单核酸 (FMN) 结合至关重要的20种氨基酸保持不变.
蛋白MPNN预测了剩余氨基酸的序列.

主要成果:

蛋白MPNN建议将86个氨基酸中的36-48个取代,从而使其与原来的CagFbFP有55%-66%的序列相同.
三个经过实验测试的设计显示了不同的表达水平,但都成功结合了FMN.
工程蛋白质表现出光,热稳定性和其他与原生CagFbFP相比的特性.

结论:

蛋白MPNN是有效的产生多样化,非自然变体的光蛋白质.
该工具可以广泛应用于重新设计蛋白质,而不会影响它们的联结功能.

关键词:

弗拉文·弗拉文·弗拉文·弗拉文光蛋白是一种光蛋白质.连接器连接器连接器机器学习是机器学习.蛋白质工程工程蛋白质工程

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