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Article Dans Une Revue Journal of Chemical Information and Modeling Année : 2020

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

Résumé

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.
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Dates et versions

cea-02909000 , version 1 (04-03-2024)

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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⟩
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