Solv-eze: Automated Placement of Explicit Water Molecules Using 3D-RISM

TL;DR

This paper introduces an automated, efficient method using 3D-RISM to accurately place water molecules around biomolecules in MD simulations, improving initial hydration accuracy without extensive sampling.

Contribution

The authors present a novel 3D-RISM-based approach for placing interfacial water molecules, integrated into AmberTools, enhancing MD system preparation.

Findings

Reproduces a large fraction of crystallographic bridging waters.

Improves agreement with experimental water positions after minimization.

Enables more accurate hydration initialization with modest computational cost.

Abstract

Molecular dynamics (MD) simulations are widely used to study biological systems, where water molecules often play a critical role in protein-ligand interactions. In conventional MD preparation protocols, water molecules are typically added from a pre-equilibrated solvent box and removed using conservative steric cutoffs, an approach that can eliminate important interfacial waters that are often not recovered during equilibration due to kinetic barriers limiting exchange with bulk solvent. In this work, we present an automated and computationally efficient method for placing water molecules around biomolecular solutes using three-dimensional reference interaction site model (3D-RISM) solvent density distributions. By identifying regions of high solvent probability, the method generates physically meaningful initial hydration structures without requiring extended sampling or specialized techniques such as grand canonical Monte Carlo (MC) or hybrid MC/MD approaches, and will be released as an update to AmberTools 26, enabling seamless integration into standard MD preparation pipelines. We validate the approach on a diverse set of protein-ligand complexes with crystallographically resolved bridging waters, showing that 3D-RISM-based placement reproduces a large fraction of these experimentally observed waters, while subsequent minimization further improves agreement as crystallographic waters relax toward positions consistent with those predicted by our approach. Overall, this method enables more accurate and practical initialization of interfacial hydration, improving the reliability of MD simulations with modest computational cost relative to routine system preparation.