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Aaron J Oakley¹

¹School of Chemistry and Molecular Bioscience, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW 2522, Australia.

|August 26, 2023

概括

人工智能识别了39种具有细胞质谷转移酶 (cGST) 折叠的人类蛋白质,揭示了它们作为酶,离子通道和相互作用介质的作用. 人工智能模型还预测了这些cGST蛋白质的潜在同型和异型分子.

科学领域:

结构生物学是结构生物学.
生物信息学是一种生物信息学.
计算生物学是一种计算生物学.

背景情况:

人工智能 (AI) 和精确的蛋白质结构预测算法正在改变结构生物学.
人工智能分析了大量的蛋白质序列数据,比如人类蛋白质组,补充了蛋白质数据库等资源中的实验数据.
在EBI的AlphaFold蛋白质结构数据库中,有超过2.3亿个预测的蛋白质结构.

研究的目的:

使用人工智能驱动的分析来识别所有预测含有细胞质谷转移酶 (cGST) 折叠的人类蛋白质.
探索具有cGST折叠的蛋白质的功能作用和潜在相互作用.
评估人工智能预测结构在理解蛋白质功能的实用性和局限性.

主要方法:

来自基于AI的结构预测资源的大规模蛋白质序列数据的分析.
识别含有细胞质谷转移酶 (cGST) 折叠的蛋白质.
使用AlphaFold-multimer来预测cGST域的对组合结构,以识别潜在的同型和异型分子.
实验生化和结构数据的整合用于验证.

主要成果:

总共有39种含有或预测含有cGST折叠的人类蛋白质被确定.
这些蛋白质包括各种类型的谷氨转移酶 (alpha,mu,pi,sigma,zeta,omega),细胞内化物通道,甲素,以及多合成酶和延长因子1复合物的组成部分.
三个主要的功能主题出现了:cGST域作为酶,离子通道或蛋白质-蛋白质相互作用的调解者.
人工智能预测的潜在同型和异型分子的结构被生成.

结论:

人工智能驱动的分析在识别蛋白质折叠和预测大型蛋白质组内的潜在功能方面是有效的.
cGST折叠是多功能性的,参与酶活性,离子运输和蛋白质复合体的形成.
人工智能预测的结构,特别是二维蛋白,提供了宝贵的见解,但需要对实验数据进行验证.

关键词:

单核细胞延长因子1 1 失败的轴突连接同类的轴突连接甘地化物诱导的分化相关蛋白质谷氨酸S转移酶C终端域含有蛋白质的蛋白质.谷氨转移酶的作用细胞内化物道是细胞内化物道.甲素甲素的使用方法多重tRNA合成酶复合体结构预测结构预测

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