Dipartimento di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy.
ENEA, Portici Research Centre, DTE-ICT-HPC, P.le E. Fermi, 1, I-80055 Portici (NA), Italy.
J Chem Phys. 2023 Mar 28;158(12):124117. doi: 10.1063/5.0143824.
We present our blind prediction of the toluene-water partition coefficients in the context of the SAMPL9 challenge. For the calculation of the solvation free energies in water, toluene, and 1-octanol, we used an efficient MD-based nonequilibrium alchemical technique relying on the GAFF2 non-polarizable force field. The method is based on the fast-growth of an initially decoupled solute. Canonical sampling of the associated end-state is efficiently obtained by performing a Hamiltonian replica exchange simulation of the gas-phase solute molecule alone, combined with equilibrium configurations of the solvent. Before submitting the prediction, a pre-assessment of the method and of the force field was made by comparing with the known experimental counterpart the calculated octanol-water partition coefficients using different set of atomic charges. The analysis allowed to optimize our blind prediction for the toluene-water partition coefficients, providing at the same time valid clues for improving the performance and reliability of the non-polarizable force field in free energy calculations of drug-receptor systems.
我们在 SAMPL9 挑战赛的背景下,对甲苯-水分配系数进行了盲法预测。为了计算水、甲苯和 1-辛醇中的溶剂化自由能,我们使用了一种基于 MD 的非平衡热力学计算方法,该方法依赖于 GAFF2 非极化力场。该方法基于最初解耦的溶质的快速生长。通过单独对气相溶质分子进行 Hamilton 复制交换模拟,并结合溶剂的平衡构型,有效地获得了相关终态的正则采样。在提交预测之前,我们通过与已知实验数据的对比,对方法和力场进行了预评估,使用不同的原子电荷集计算了不同的辛醇-水分配系数。分析结果允许我们优化甲苯-水分配系数的盲法预测,同时为提高非极化力场在药物受体系统自由能计算中的性能和可靠性提供了有效的线索。