Predicting Hydration Free Energies of the FreeSolv Database of Drug-like Molecules with Molecular Density Functional Theory

被引:12
|
作者
Luukkonen, Sohvi [2 ]
Belloni, Luc [3 ]
Borgis, Daniel [1 ,2 ]
Levesque, Maximilien [1 ]
机构
[1] PSL Univ, CNRS, Sorbonne Univ, PASTEUR,Dept Chim,Ecole Normale Super, F-75005 Paris, France
[2] Univ Paris Saclay, Maison Simulat, CNRS, CEA, F-91191 Gif Sur Yvette, France
[3] Univ Paris Saclay, CNRS, CEA, LIONS,NIMBE, F-91191 Gif Sur Yvette, France
关键词
SOLVATION FREE-ENERGIES; EFFICIENT GENERATION; INVARIANT EXPANSION; AM1-BCC MODEL; SOLVENT; THERMODYNAMICS; EQUATION; FORCE; RECOGNITION; 3D-RISM-KH;
D O I
10.1021/acs.jcim.0c00526
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
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.
引用
收藏
页码:3558 / 3565
页数:8
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