蛋白质嵌入改善了菌体与宿主相互作用的预测
Mark Edward M Gonzales1,2, Jennifer C Ureta1,2, Anish M S Shrestha1,3,2
1Bioinformatics Laboratory, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines.
PloS one
|July 24, 2023
概括
预测菌体与宿主相互作用对于对抗抗菌素耐药性至关重要. 使用蛋白质语言模型来分析菌体受体结合蛋白可以显著提高比传统方法的预测准确度.
科学领域:
- 微生物学 微生物学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 菌体治疗是对抗抗菌素耐药性的有希望的策略.
- 准确预测菌体与宿主相互作用对于选择有效的菌体至关重要.
- 当前的计算方法往往需要手动的功能工程,限制效率.
研究的目的:
- 开发一种更有效的计算方法来预测菌体与宿主之间的相互作用.
- 利用蛋白质语言模型从菌体蛋白中自动提取特征.
- 评估受体结合蛋白嵌入在宿主预测中的性能.
主要方法:
- 作为一个多类分类任务的菌体与宿主相互作用预测.
- 从蛋白质语言模型 (例如,ProtT5) 中使用了用于受体结合蛋白的嵌入.
- 与使用手工制作的基因组和蛋白质序列特征的模型进行性能比较.
主要成果:
- 蛋白质语言模型嵌入器在宿主预测方面表现优于手工制作的功能.
- ProtT5型号实现了最高的精度.
- 观察到ProtT5嵌入时,加权F1和召回分数增加了3%至4%.
结论:
- 受体结合蛋白嵌入为菌体与宿主相互作用预测模型提供了强大的输入.
- 使用蛋白质语言模型的自动特征提取提高了预测性能.
- 这种方法提供了一种更有效,更准确的方法来识别候选菌体.
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