Predicting hydration free energies of the freesolv database of drug-like molecules with molecular density functional theory

Sohvi Luukkonen (1) , Luc Belloni (2) , Daniel Borgis (1, 3) , Maximilien Levesque (3)

1 MDLS - Maison de la Simulation
2 LIONS - Laboratoire Interdisciplinaire sur l'Organisation Nanométrique et Supramoléculaire
3 PASTEUR - Processus d'Activation Sélective par Transfert d'Energie Uni-électronique ou Radiatif (UMR 8640)

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.

Domains: Chemical Sciences; Theoretical and/or physical chemistry

Sohvi Luukkonen, Luc Belloni, Daniel Borgis, Maximilien Levesque. Predicting hydration free energies of the freesolv database of drug-like molecules with molecular density functional theory. Journal of Chemical Information and Modeling, 2020, 60 (7), pp.3558-3565. ⟨10.1021/acs.jcim.0c00526⟩. ⟨cea-02909000⟩