MDZip:神经压缩分子动力学轨迹可扩展存储和集体重建
Namindu De Silva1, Alberto Perez1
1Department of Chemistry, Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States.
The journal of physical chemistry. B
|October 31, 2025
概括
MDZip是一种新型的神经压缩框架,可显著降低分子动力学 (MD) 轨迹文件大小超过95%. 这使得有效的数据共享和分析,而不会丢失关键的动态信息.
科学领域:
- 计算化学计算化学
- 生物物理学的生物物理.
- 数据科学数据科学数据科学
背景情况:
- 分子动力学 (MD) 轨迹对于理解生物分子行为至关重要,但也带来了重大的存储和共享挑战.
- 目前的数据减少方法,如子采样或减少原子表示,损害了轨迹效用.
研究的目的:
- 开发一个新的神经压缩框架,MDZip,以有效地存储和共享MD轨迹.
- 从紧的潜伏表示实现高几何准确度的重建.
主要方法:
- MDZip使用一个卷积式自动编码器框架,训练每个系统,以压缩和重建原子轨迹.
- 研究了一种残留 (跳过连接) 自动编码器变体,以提高重建的准确性.
主要成果:
- 在各种分子系统 (蛋白质,复合物,核酸) 中,MDZip实现了超过95%的存储减少.
- 重建的轨迹保留了关键的集体级特征,如RMSD波动和组件投影.
- 剩余变种提高了准确性,降低了异常值,能源最小化部分恢复了能量保真.
结论:
- MDZip为MD数据存储和传播提供了一个可扩展的解决方案,克服了当前的局限性.
- 该框架允许可定制的压缩精度权衡,促进更广泛的数据共享,而不会丢失必要的动态信息.
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