McGibbon Robert T, Beauchamp Kyle A, Harrigan Matthew P, Klein Christoph, Swails Jason M, Hernández Carlos X, Schwantes Christian R, Wang Lee-Ping, Lane Thomas J, Pande Vijay S
Department of Chemistry, Stanford University, Stanford, California.
Computational Biology Program, Sloan-Kettering Institute, New York, New York.
Biophys J. 2015 Oct 20;109(8):1528-32. doi: 10.1016/j.bpj.2015.08.015.
As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing MD simulations. MDTraj reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between MD data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. MDTraj is a powerful and user-friendly software package that simplifies the analysis of MD data and connects these datasets with the modern interactive data science software ecosystem in Python.
随着分子动力学（MD）模拟不断发展成为研究复杂生物分子系统的强大计算工具，用于分析这些模拟的灵活且易于使用的软件工具的需求也在不断增长。我们开发了MDTraj，这是一个用于分析MD模拟的现代、轻量级且快速的软件包。MDTraj以多种常用格式读取和写入轨迹数据。它提供了大量的轨迹分析功能，包括最小均方根偏差计算、二级结构分配以及常见序参量的提取。该软件包非常注重与更广泛的科学Python生态系统的互操作性，弥合了MD数据与Python中快速增长的行业标准统计分析和可视化工具集之间的差距。MDTraj是一个功能强大且用户友好的软件包，它简化了MD数据的分析，并将这些数据集与Python中的现代交互式数据科学软件生态系统连接起来。
