Predicting hydration free energies of the FreeSolv database of druglike molecules with molecular density functional theory

TL;DR

This paper demonstrates that molecular density functional theory (MDFT) can accurately predict hydration free energies of drug-like molecules in the FreeSolv database within 1 kcal/mol, with significantly reduced computational time.

Contribution

The study shows MDFT with HNC approximation and pressure correction achieves comparable accuracy to simulation-based methods but with much faster computation.

Findings

MDFT predicts hydration free energies within 1 kcal/mol of experimental values.

MDFT requires only two CPU minutes per molecule.

The method matches the accuracy of traditional free energy calculations.

Abstract

We assess the performance of molecular densityfunctional theory (MDFT) to predict hydration freeenergies of the small drug-like molecules benchmark,FreeSolv. MDFT in the hyper-netted chain approx-imation (HNC) coupled with a pressure correctionpredicts experimental hydration free energies of theFreeSolv database within 1 kcal/mol with an averagecomputation time of two cpu.min per molecule. Thisis the same accuracy as for simulation based free en-ergy calculations that typically require hundreds ofcpu.h or tens of gpu.h per molecule.