纳米体的结构建模:最先进的人工智能程序的基准
Mario S Valdés-Tresanco1, Mario E Valdés-Tresanco2, Daiver E Jiménez-Gutiérrez1
1Faculty of Basic Sciences, University of Medellin, Medellin 050026, Colombia.
Molecules (Basel, Switzerland)
|May 27, 2023
概括
人工智能 (AI) 工具对建模纳米体具有前景,但准确预测CDR3结构仍然是这些生物分子面临的重大挑战.
科学领域:
- 生物技术是生物技术.
- 结构生物学 结构生物学
- 蛋白质科学中的人工智能
背景情况:
- 纳米体正在快速扩展生物产品,具有多样化的应用.
- 准确的结构模型对于纳米体蛋白质工程至关重要.
- 纳米体结构建模具有与抗体相似的挑战.
研究的目的:
- 评估用于纳米体结构建模的最先进的人工智能程序的性能.
- 将一般蛋白质建模人工智能工具与专门用于抗体建模的工具进行比较.
- 在纳米体结构预测中识别当前人工智能方法的优缺点.
主要方法:
- 基于人工智能的多个蛋白质建模程序的比较:AlphaFold2,OmegaFold,ESMFold,Yang-Server,IgFold和Nanonet. 这些都是基于人工智能的蛋白质建模程序.
- 对纳米体框架和互补性确定区域 (CDR) 的模型准确性评估.
- 对专门设计用于应用在纳米体上的抗体建模的AI模型的评估.
主要成果:
- 所有测试的AI程序在建模纳米体框架和CDR1/CDR2区域方面表现良好.
- 对于所有评估的AI方法来说,CDR3区域的建模是具有挑战性的.
- 专门为抗体建模量身定制的人工智能方法并没有始终优于纳米体建模的一般工具.
结论:
- 当前的人工智能工具为纳米体结构建模提供了宝贵的功能,特别是在框架区域.
- 纳米体CDR3预测仍然是AI驱动蛋白质建模改进的关键领域.
- 人工智能模型对抗体的专业化并不能保证纳米体的优越性能.
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