High-throughput free energies and water maps for drug discovery by molecular density functional theory

TL;DR

This paper introduces a molecular density functional theory approach that accurately predicts hydration free energies and water maps for drug-like molecules, enabling fast and reliable screening in drug discovery.

Contribution

It presents a novel probabilistic method that achieves near-atomistic accuracy in hydration free energy predictions with computational efficiency suitable for high-throughput screening.

Findings

Predicts hydration free energies within 0.5 kJ/mol of atomistic simulations

Provides detailed water and polarization maps

Achieves computational speed compatible with drug screening workflows

Abstract

The hydration or binding free energy of a drug-like molecule is a key data for early stage drug discovery. Hundreds of thousands of evaluations are needed, which rules out the exhaustive use of atomistic simulations and free energy methods. Instead, the current docking and screening processes are today relying on numerically efficient scoring functions that lose much of the atomic scale information and hence remain error-prone. In this article, we show how a probabilistic description of molecular liquids as implemented in the molecular density functional theory predicts hydration free energies of a state-of-the-art benchmark of small drug-like molecules within 0.5 kJ/mol (0.1 kcal/mol) of atomistic simulations, along with water and polarization maps, for a computation time compatible with screening and docking.