Comparative evaluation of explicit solvent models for RNA-ligand docking
Loading...
Date issued
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Reuse License
Description of rights: CC-BY-4.0
Abstract
The interest in targeting RNA with small molecules is increasing continuously. However, structure-based drug design approaches have been reported rarely so far. Major challenges in RNA-ligand docking include ligand-induced conformational changes, ions and solvation which hamper successful applications in prospective virtual screenings. We examined the influence of explicit solvent inclusion on RNA-ligand docking performance using crystallographic water sites as well as the computational solvation models 3D-RISM, GalaxyWater-CNN and waterdock_fxx in combination with FlexX, FlexX with HYDE rescoring, GOLD and LeadIT docking. The redocking study with 92 RNA-ligand complexes underlined that the benefit of solvent consideration is highly target-specific and resolution-dependent reaching on average accurate pose predictions of around 70% for all structures and only 35% for low-resolution structures for FlexX, GOLD and LeadIT. HYDE performed slightly worse on average with an overall 50% accurate pose prediction and varying impact of predicted solvent. Success rates of structures lacking experimental solvent information were improved by involving predicted water sites. 3D-RISM predictions showed most robust results across all resolutions, improving success rates by up to 30% for low-resolution structures in combination with LeadIT. In addition, NMR and ion-free structures were found to be more challenging in pose prediction accuracy compared to ion-containing X-ray structures. Cross-docking studies across five representative RNA targets demonstrated improvements for hydrated dockings, while different binding site conformations indicated RNA dynamics as an additional challenge. The best cross-docking setup was partially deducible from the corresponding redocking setup revealing great potential to advance virtual screenings by the inclusion of explicit solvent sites.
Description
Keywords
Citation
Published in
Journal of chemical information and modeling, 66, 11, ACS, Washington, DC, 2026, https://doi.org/10.1021/acs.jcim.6c00498
