Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Boulevard, Galveston, Texas 77555-0304, USA.
J Chem Phys. 2021 Sep 14;155(10):104110. doi: 10.1063/5.0062580.
The proximal distribution function (pDF) quantifies the probability of finding a solvent molecule in the vicinity of solutes. The approach constitutes a hierarchically organized theory for constructing approximate solvation structures around solutes. Given the assumption of universality of atom cluster-specific solvation, reconstruction of the solvent distribution around arbitrary molecules provides a computationally convenient route to solvation thermodynamics. Previously, such solvent reconstructions usually considered the contribution of the nearest-neighbor distribution only. We extend the pDF reconstruction algorithm to terms including next-nearest-neighbor contribution. As a test, small molecules (alanine and butane) are examined. The analysis is then extended to include the protein myoglobin in the P6 crystal unit cell. Molecular dynamics simulations are performed, and solvent density distributions around the solute molecules are compared with the results from different pDF reconstruction models. It is shown that the next-nearest-neighbor modification significantly improves the reconstruction of the solvent number density distribution in concave regions and between solute molecules. The probability densities are then used to calculate the solute-solvent non-bonded interaction energies including van der Waals and electrostatic, which are found to be in good agreement with the simulated values.
近分布函数 (pDF) 用于量化溶剂分子在溶质附近的出现概率。该方法构成了一种用于构建溶质周围近似溶剂结构的分层组织理论。基于原子簇特定溶剂化的普遍性假设，对任意分子周围溶剂分布的重建为溶剂化热力学提供了一种计算上方便的途径。以前，这种溶剂重建通常只考虑最近邻分布的贡献。我们将 pDF 重建算法扩展到包括次近邻贡献的项。作为一个测试，我们研究了小分子（丙氨酸和丁烷）。然后将分析扩展到包含 P6 晶体单元中的蛋白质肌红蛋白。进行分子动力学模拟，并将溶剂密度分布与不同 pDF 重建模型的结果进行比较。结果表明，次近邻修饰显著改善了凹陷区域和溶质分子之间溶剂数密度分布的重建。然后使用概率密度计算溶质-溶剂非键相互作用能，包括范德华和静电相互作用能，发现与模拟值吻合良好。
