维纳-CUDA:一个高效的程序,深入利用GPU加速分子对接
Chunfeng Li1, Yizhuo Wang1, Hongbo Xing1
1School of Computer Science and Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing 100081, China.
我们开发了Vina-CUDA,这是一个GPU加速的分子对接工具,以加快药物发现速度. 这种增强的计算能力显著加速了大型化学库的虚拟选,提高了药物开发效率.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- 生物信息学是一种生物信息学.
背景情况:
- 分子对接对于识别药物线索至关重要.
- 越来越多的化学数据库挑战了现有的对接工具.
- 有效的虚拟查对于药物开发至关重要.
研究的目的:
- 使用GPU硬件加速分子对接.
- 为了优化AutoDock Vina的核心算法以提高速度.
- 为大规模的虚拟选开发一个多GPU框架.
主要方法:
- 利用GPU功能来提高计算能力,内存访问和资源利用.
- 实施了混合并行优化策略.
- 开发了Vina-CUDA,QuickVina2-CUDA,以及QuickVina-W-CUDA. 这三种语言的开发人员包括:
主要成果:
- Vina-CUDA的平均加速度是3.71×,QuickVina2-CUDA的平均加速度是6.19×,QuickVina-W-CUDA的平均加速度是1.46×.
- 加速度达到了6.89×,而不会影响对接的准确性.
- 展示了与基线程序相比较的对接,得分和排名能力.
结论:
- 维纳-CUDA及其衍生物显著提高分子对接效率.
- 这些工具为虚拟选提供了出色的可扩展性和可移植性.
- GPU 加速是克服大型化学数据库带来的挑战的关键.
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