Force fields based on molecular mechanics (MM) are the main computational tool to study the relationship between protein structure and function at the molecular level. To validate the quality of such force fields, high-level quantum-mechanical (QM) data are employed to test their capability to reproduce the features of all major conformational substates of a series of blocked amino acids. The phase-space overlap between MM and QM is quantified in terms of the average structural reorganization energies over all energy minima. Here, the structural reorganization energy is the MM potential-energy difference between the structure of the respective QM energy minimum and the structure of the closest MM energy minimum. Thus, it serves as a measure for the relative probability of visiting the QM minimum during an MM simulation. We evaluate variants of the AMBER, CHARMM, GROMOS and OPLS biomolecular force fields. In addition, the two blocked amino acids alanine and serine are used to demonstrate the dependence of the measured agreement on the QM method, the phase, and the conformational preferences. Blocked serine serves as an example to discuss possible improvements of the force fields, such as including polarization with Drude particles, or using tailored force fields. The results show that none of the evaluated force fields satisfactorily reproduces all energy minima. By decomposing the average structural reorganization energies in terms of individual energy terms, we can further assess the individual weaknesses of the parametrization strategies of each force field. The dominant problem for most force fields appears to be the van der Waals parameters, followed to a lesser degree by dihedral and bonded terms. Our results show that performing a simple QM energy optimization from an MM-optimized structure can be a first test of the validity of a force field for a particular target molecule.

基于分子力学（MM）的力场是在分子水平上研究蛋白质结构与功能之间关系的主要计算工具。为了验证这种力场的质量，我们使用高级量子力学 (QM) 数据来测试它们再现一系列封闭氨基酸的所有主要构象亚状态特征的能力。MM 和 QM 之间的相空间重叠根据所有能量最小值的平均结构重组能量进行量化。这里，结构重组能是相应 QM 能量最小值的结构与最近的 MM 能量最小值的结构之间的 MM 势能差。因此，它用作在 MM 模拟期间访问 QM 最小值的相对概率的度量。我们评估了 AMBER、CHARMM、GROMOS 和 OPLS 生物分子力场的变体。此外，两个封闭的氨基酸丙氨酸和丝氨酸用于证明测量的一致性对 QM 方法、相位和构象偏好的依赖性。封闭丝氨酸作为一个例子来讨论力场的可能改进，例如包括德鲁德粒子的极化，或使用定制的力场。结果表明，评估的力场中没有一个能令人满意地再现所有能量最小值。通过将平均结构重组能量分解为个体能量项，我们可以进一步评估每个力场参数化策略的个体弱点。大多数力场的主要问题似乎是范德瓦尔斯参数，其次是二面角和键合术语。我们的结果表明，从 MM 优化结构执行简单的 QM 能量优化可以是对特定目标分子的力场有效性的首次测试。