APACE:AlphaFold2和先进的计算作为一种服务,以加速生物物理学的发现
Hyun Park1,2,3, Parth Patel1,4,5, Roland Haas5
1Data Science and Learning Division, Argonne National Laboratory, Lemont, IL 60439.
概括
我们开发了APACE,这是使用AlphaFold2和超级计算加速蛋白质结构预测的框架. APACE显著加快了分析速度,将计算时间从几周缩短到几分钟,以提高药物发现和基因组解释.
科学领域:
- 生物物理学的生物物理.
- 计算生物学 计算生物学
- 科学中的人工智能.
背景情况:
- 从氨基酸序列预测蛋白质的3D结构是一个重大挑战.
- 像AlphaFold这样的AI模型正在改变蛋白质结构预测.
- 现有的工具需要大量的计算资源和时间.
研究的目的:
- 介绍APACE (AlphaFold2和高级计算作为服务).
- 在超级计算环境中实现加速蛋白质结构预测分析.
- 提高人工智能驱动的蛋白质结构预测的可用性和影响.
主要方法:
- 开发了APACE,这是AlphaFold2.2.的计算框架.
- 在Delta和Polaris超级计算机上部署了APACE.
- 在200个NVIDIA A100 GPU上使用了多达300个组合,用于性能量化.
主要成果:
- 在四个样本蛋白 (6AWO,6OAN,7MEZ,6D6U) 中,APACE实现了精确的蛋白质结构预测.
- 与标准AlphaFold2.2相比,APACE显示了高达两个数量级的加速度.
- 将蛋白质结构预测时间从几周减少到几分钟.
结论:
- 对于大规模的蛋白质结构预测,APACE提供了一个高效的解决方案.
- 这种框架通过快速分析来加速科学发现.
- 整合机器人技术的潜力,用于自动化科学发现.
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