Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Bioinformatics. 2018 Nov 15;34(22):3945-3947. doi: 10.1093/bioinformatics/bty484.
Molecular dynamics simulations have found use in a wide variety of biomolecular applications, from protein folding kinetics to computational drug design to refinement of molecular structures. Two areas where users and developers frequently need to extend the built-in capabilities of most software packages are implementing custom interactions, for instance biases derived from experimental data, and running ensembles of simulations. We present a Python high-level interface for the popular simulation package GROMACS that i) allows custom potential functions without modifying the simulation package code, ii) maintains the optimized performance of GROMACS and iii) presents an abstract interface to building and executing computational graphs that allows transparent low-level optimization of data flow and task placement. Minimal dependencies make this integrated API for the GROMACS simulation engine simple, portable and maintainable. We demonstrate this API for experimentally-driven refinement of protein conformational ensembles.
LGPLv2.1 source and instructions are available at https://github.com/kassonlab/gmxapi.
Supplementary data are available at Bioinformatics online.
分子动力学模拟在广泛的生物分子应用中得到了应用，从蛋白质折叠动力学到计算药物设计再到分子结构的精修。用户和开发人员经常需要扩展大多数软件包的内置功能的两个领域是实现自定义交互，例如基于实验数据的偏差，以及运行模拟的集合。我们为流行的模拟包 GROMACS 提供了一个 Python 高级接口，该接口：i）允许使用自定义势函数而无需修改模拟包代码，ii）保持 GROMACS 的优化性能，iii）提供构建和执行计算图的抽象接口，允许对数据流和任务放置进行透明的低级优化。最小的依赖关系使这个 GROMACS 模拟引擎的集成 API 简单、可移植和可维护。我们展示了这个 API 在实验驱动的蛋白质构象集合精修中的应用。
LGPLv2.1 源代码和说明可在 https://github.com/kassonlab/gmxapi 获得。
补充数据可在生物信息学在线获得。
