Free energy drives a wide range of molecular processes such as solvation, binding, chemical reactions and conformational change. Given the central importance of binding, a wide range of methods exist to calculate it, whether based on scoring functions, machine-learning, classical or electronic structure methods, alchemy, or explicit evaluation of energy and entropy. Here we present a new energy–entropy (EE) method to calculate the host–guest binding free energy directly from molecular dynamics (MD) simulation. Entropy is evaluated using Multiscale Cell Correlation (MCC) which uses force and torque covariance and contacts at two different length scales. The method is tested on a series of seven host–guest complexes in the SAMPL8 (Statistical Assessment of the Modeling of Proteins and Ligands) “Drugs of Abuse” Blind Challenge. The EE-MCC binding free energies are found to agree with experiment with an average error of 0.9 kcal mol⁻¹. MCC makes clear the origin of the entropy changes, showing that the large loss of positional, orientational, and to a lesser extent conformational entropy of each binding guest is compensated for by a gain in orientational entropy of water released to bulk, combined with smaller decreases in vibrational entropy of the host, guest and contacting water.

自由能驱动广泛的分子过程，例如溶剂化、结合、化学反应和构象变化。鉴于结合的核心重要性，存在多种计算方法，无论是基于评分函数、机器学习、经典或电子结构方法、炼金术还是能量和熵的显式评估。在这里，我们提出了一种新的能量熵（EE）方法，可以直接从分子动力学（MD）模拟中计算主客体结合自由能。使用多尺度单元相关性 (MCC) 评估熵，该相关性使用力和扭矩协方差以及两个不同长度尺度的接触。该方法在 SAMPL8（蛋白质和配体建模的统计评估）“滥用药物”盲挑战中的一系列七个主客体复合物上进行了测试。发现EE-MCC结合自由能与实验一致，平均误差为0.9 kcal mol ^-1 。 MCC 明确了熵变化的根源，表明每个结合客体的位置、取向和较小程度的构象熵的大量损失通过释放到本体的水的取向熵的增加以及较小的减少来补偿在主、客和接触水的振动熵中。