Gilardoni Ivan, Piomponi Valerio, Fröhlking Thorben, Bussi Giovanni
Scuola Internazionale Superiore di Studi Avanzati, SISSA, Via Bonomea, 265, 34136 Trieste, Italy.
Area Science Park, Località Padriciano, 99, 34149 Trieste, Italy.
J Chem Phys. 2025 May 21;162(19). doi: 10.1063/5.0256841.
Molecular dynamics (MD) simulations play a crucial role in resolving the underlying conformational dynamics of molecular systems. However, their capability to correctly reproduce and predict dynamics in agreement with experiments is limited by the accuracy of the force-field model. This capability can be improved by refining the structural ensembles or the force-field parameters. Furthermore, discrepancies with experimental data can be due to imprecise forward models, namely, functions mapping simulated structures to experimental observables. Here, we introduce MDRefine, a Python package aimed at implementing the refinement of the ensemble, the force field, and/or the forward model by comparing MD-generated trajectories with the experimental data. The software consists of several tools that can be employed separately from each other or combined together in different ways, providing a seamless interpolation between these three different types of refinement. We use some benchmark cases to show that the combined approach is superior to separately applied refinements. MDRefine has been released as an open-source package under the LGPLv2+ license. Source code, documentation, and examples are available at https://pypi.org/project/MDRefine and https://github.com/bussilab/MDRefine.
分子动力学（MD）模拟在解析分子系统潜在的构象动力学方面发挥着关键作用。然而，其与实验结果一致地正确再现和预测动力学的能力受到力场模型准确性的限制。通过优化结构系综或力场参数可以提高这种能力。此外，与实验数据的差异可能归因于不精确的正向模型，即把模拟结构映射到实验可观测量的函数。在此，我们介绍MDRefine，一个Python软件包，旨在通过将MD生成的轨迹与实验数据进行比较，实现对系综、力场和/或正向模型的优化。该软件由几个工具组成，这些工具可以彼此独立使用或以不同方式组合在一起，在这三种不同类型的优化之间提供无缝插值。我们使用一些基准案例表明，组合方法优于单独应用的优化方法。MDRefine已作为开源软件包在LGPLv2+许可下发布。源代码、文档和示例可在https://pypi.org/project/MDRefine和https://github.com/bussilab/MDRefine获取。
