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Abstract The stability and function of biomolecules are directly influenced by their myriad interactions with water1–16. Here we investigated water through cryogenic electron microscopy (cryo-EM) on a highly solvated molecule: theTetrahymenaribozyme. By using segmentation-guided water and ion modelling (SWIM)17,18, an approach combining resolvability and chemical parameters, we automatically modelled and cross-validated water molecules and Mg2+ions in the ribozyme core, revealing the extensive involvement of water in mediating RNA non-canonical interactions. Unexpectedly, in regions where SWIM does not model ordered water, we observed highly similar densities in both cryo-EM maps. In many of these regions, the cryo-EM densities superimpose with complex water networks predicted by molecular dynamics, supporting their assignment as water and suggesting a biophysical explanation for their elusiveness to conventional atomic coordinate modelling. Our study demonstrates an approach to unveil both rigid and flexible waters that surround biomolecules through cryo-EM map densities, statistical and chemical metrics, and molecular dynamics simulations.
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This content will become publicly available on January 1, 2027
Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16
ABSTRACT Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo‐EM densities observed around theTetrahymenaribozyme at 2.2–2.3 Å resolution, collected through target R1260 in the CASP16 competition. Twenty‐six groups participated in this solvation “cryo‐ensemble” prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo‐EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo‐EM densities using Pearson correlation, Spearman correlation, mutual information, and precision‐recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo‐EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo‐EM maps. We propose that further community‐wide blind challenges can drive and evaluate progress in modeling water, ions, and other previously hidden components of biomolecular systems.
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- PAR ID:
- 10663184
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Proteins: Structure, Function, and Bioinformatics
- Volume:
- 94
- Issue:
- 1
- ISSN:
- 0887-3585
- Page Range / eLocation ID:
- 381 to 402
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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