Issue 28, 2024

A general graph neural network based implicit solvation model for organic molecules in water

Abstract

The dynamical behavior of small molecules in their environment can be studied with classical molecular dynamics (MD) simulations to gain deeper insight on an atomic level and thus complement and rationalize the interpretation of experimental findings. Such approaches are of great value in various areas of research, e.g., in the development of new therapeutics. The accurate description of solvation effects in such simulations is thereby key and has in consequence been an active field of research since the introduction of MD. So far, the most accurate approaches involve computationally expensive explicit solvent simulations, while widely applied models using an implicit solvent description suffer from reduced accuracy. Recently, machine learning (ML) approaches that provide a probabilistic representation of solvation effects have been proposed as potential alternatives. However, the associated computational costs and minimal or lack of transferability render them unusable in practice. Here, we report the first example of a transferable ML-based implicit solvent model trained on a diverse set of 3 000 000 molecular structures that can be applied to organic small molecules for simulations in water. Extensive testing against reference calculations demonstrated that the model delivers on par accuracy with explicit solvent simulations while providing an up to 18-fold increase in sampling rate.

Graphical abstract: A general graph neural network based implicit solvation model for organic molecules in water

Supplementary files

Article information

Article type
Edge Article
Submitted
12 Кві 2024
Accepted
24 Тра 2024
First published
19 Чер 2024
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2024,15, 10794-10802

A general graph neural network based implicit solvation model for organic molecules in water

P. Katzberger and S. Riniker, Chem. Sci., 2024, 15, 10794 DOI: 10.1039/D4SC02432J

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