Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modeling tool to interpret experimental measurements, and to use experimental data to refine our biophysical models. Thus, explicit integration and synergy between molecular simulations and experiments is fundamental for furthering our understanding of biological processes. This is especially true in the case where discrepancies between measured and simulated observables emerge. In this chapter, we provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions. We distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where experiments are used more generally to refine transferable models. We discuss different philosophies and attempt to unify them in a single framework. Until now, such integration between experiments and simulations have mostly been applied to equilibrium data, and we discuss more recent developments aimed to analyze time-dependent or time-resolved data.

分子模拟和生物物理实验可用于提供对生物过程的分子起源的独立且互补的见解。一种特别有用的策略是使用分子模拟作为建模工具来解释实验测量结果，并使用实验数据来完善我们的生物物理模型。因此，分子模拟与实验之间的显式整合和协同作用是加深我们对生物学过程的理解的基础。在实测和模拟观测值之间出现差异的情况下尤其如此。在本章中，我们将概述为提高实验信息和数值预测之间的一致性而开发的方法背后的一些核心思想。我们区分使用实验来完善我们对特定系统的理解和模型的情况，以及用于更广泛地使用实验来改进可转移模型的情况。我们讨论了不同的哲学，并试图将它们统一在一个框架中。到目前为止，实验和模拟之间的这种集成大部分已应用于平衡数据，并且我们讨论了旨在分析时间相关或时间分辨数据的最新进展。