通过结构建模使用目标结合倾向对工程蛋白质进行快速,准确的排名
Xiaozhe Ding1, Xinhong Chen1, Erin E Sullivan1
1Division of Biology and Biological Engineering, California Institute of Technology, 1200 E California, Boulevard, Pasadena, CA 91125, USA.
概括
我们开发了APPRAISE,这是一种新的计算方法,用于预测蛋白质结合亲和力. 该工具通过精确选工程蛋白质以检测目标结合潜力来加速蛋白质工程,从而有助于生物医学应用.
科学领域:
- 计算生物学 计算生物学
- 蛋白质工程是指蛋白质工程.
- 生物物理学的生物物理.
背景情况:
- 深度学习推进了蛋白质结构预测的准确性.
- 在预测蛋白质结构和优先考虑蛋白质工程的结合潜力之间存在差距.
研究的目的:
- 引入用于选工程蛋白质的自动配对受体分析 (APPRAISE).
- 开发一种方法来预测工程蛋白质的目标结合倾向.
- 弥合蛋白质结构预测和蛋白质结合剂优先级之间的差距.
主要方法:
- 使用已建立的结构预测工具 (例如,AlphaFold-Multimer,ESMFold) 来生成结构模型.
- 在考虑生物物理和几何约束的情况下,进行快速评分分析 (每模型低于1个CPU秒).
- 在Google Colaboratory.上通过基于Web的笔记本电脑界面实现APPRAISE.
主要成果:
- APPRAISE准确地分类了受体依赖的与独立的腺相关病毒载体.
- 成功选了各种工程蛋白质,包括针对SARS-CoV-2尖端的微蛋白,纳米体和与特定受体 (转激素受体,PD-L1) 结合的.
- 证明了评估方法的准确性,可解释性和通用性.
结论:
- APPRAISE有效地预测了工程蛋白质的目标结合倾向.
- 该方法通过提高蛋白质结构预测的实用性来加速生物医学应用中的蛋白质工程.
- 评估为选蛋白质结合剂提供了可概括和可解释的解决方案.
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