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一种基于mRNA结构预测的新方法,用于识别骨形态遗传蛋白2的改进信号
Piers Wilkinson1, Brian Jackson2, Hazel Fermor3
1Department of Mechanical Engineering, Institute of Medical and Biological Engineering, University of Leeds, Leeds, UK. mnpw@leeds.ac.uk.
BMC biotechnology
|May 23, 2024
概括
为蛋白质生产而进行信号工程具有挑战性. 使用mRNA结构的信号的in silico选显示出希望,但需要进一步开发以在合成生物学应用中进行可靠的预测.
科学领域:
- 合成生物学 合成生物学
- 蛋白质工程是指蛋白质工程.
- 计算生物学 计算生物学
背景情况:
- 信号 (SP) 工程提高了蛋白质的生产,但很费力,依赖于试验和错误.
- 翻译开始部位的mRNA结构影响翻译启动,并且可以作为SP选择的预测工具.
- 预测SP活动,局部化和mRNA结构的in silico方法正在进步.
研究的目的:
- 开发一种系统的 in silico 方法来选候选SP序列.
- 评估SP氨基酸和核酸序列的实用性,包括mRNA结构,用于预测SP功能.
- 测试骨形态遗传蛋白2 (BMP2) 的计算选择的SP,以改善其生产和基因治疗应用.
主要方法:
- 使用的计算工具:SignalP用于SP活动,DeepLoc用于目标定位,MXFold2用于mRNA结构预测.
- 根据氨基酸序列,选了2,611个TGF-β超级家族SP,以确定BMP2的兼容性.
- 根据预测的SP活动,本地化和转化开始地点可访问性来选择最佳候选人进行体外验证.
主要成果:
- 氨基酸分析预测了BMP2.2的2611个功能SP.
- mRNA结构预测显示了翻译开始地点的高变异性.
- 在体外试验中,在HEK293T细胞中,选择的SPs没有显著改善BMP2分泌;在C2C12细胞中,分泌量有所减少.
结论:
- 基于序的in silico工具对于合成生物学中基本的SP活动预测是有用的.
- 为了在SP选择中可靠应用,mRNA结构预测工具需要进一步改进.
- 阴优化,mRNA结构和细胞环境是影响SP活动的关键因素,BMP2变异在C2C12细胞中的表现不佳证明了这一点.
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