Maison de la Simulation, CNRS-CEA-Université Paris-Saclay, Gif-sur-Yvette 91191, France.
LIONS, NIMBE, CEA, CNRS, Université Paris-Saclay, Gif-sur-Yvette 91191 France.
J Chem Inf Model. 2020 Jul 27;60(7):3558-3565. doi: 10.1021/acs.jcim.0c00526. Epub 2020 Jul 9.
We assess the performance of molecular density functional theory (MDFT) to predict hydration free energies of the small drug-like molecules benchmark, FreeSolv. The MDFT in the hypernetted chain approximation (HNC) coupled with a pressure correction predicts experimental hydration free energies of the FreeSolv database within 1 kcal/mol with an average computation time of 2 cpu·min per molecule. This is the same accuracy as for simulation-based free energy calculations that typically require hundreds of cpu·h or tens of gpu·h per molecule.
我们评估了分子密度泛函理论(MDFT)在预测小分子药物样分子基准 FreeSolv 的水合自由能方面的性能。在超网链逼近(HNC)下耦合压力修正的 MDFT 可以在 1 kcal/mol 的范围内预测 FreeSolv 数据库的实验水合自由能,平均每个分子的计算时间为 2 cpu·min。这与基于模拟的自由能计算的精度相同,后者通常每个分子需要数百个 cpu·h 或数十个 gpu·h。