PPIscreenML:使用AlphaFold进行蛋白质蛋白相互作用的基于结构的选
Victoria Mischley1,2, Johannes Maier3, Jesse Chen3
1Cancer Signaling & Microenvironment Program, Fox Chase Cancer Center, Philadelphia PA 19111.
bioRxiv : the preprint server for biology
|April 1, 2024
概括
我们开发了PPIscreenML,这是一种机器学习模型,用于从结构模型中识别真正的蛋白质-蛋白质相互作用. PPIscreenML准确地区分互动对与诱,优于现有的方法.
科学领域:
- 结构生物学是结构生物学.
- 计算生物学是一种计算生物学.
- 生物信息学是一种生物信息学.
背景情况:
- 蛋白与蛋白相互作用 (PPI) 是细胞功能的基础.
- 蛋白质结构预测的进步,比如AlphaFold2 (AF2),可以生成蛋白质复合体的准确模型.
- 一个关键的挑战是确定预测的蛋白质对的生物相关性,并选网络构建的潜在相互作用.
结论:
- PPIscreenML提供了一个强大的,基准的方法来从结构模型中推断蛋白质-蛋白质相互作用.
- 该模型广泛适用于使用AF2生成的结构数据发现新型蛋白质复合体.
- 这个工具有助于通过过可靠的相互作用来建立更准确的蛋白质相互作用网络.
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