ArticleNature communications2025
MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Water, water, every where-the advent of hydrated pili structure.The FEBS journal · 2026Article
- Structure of NO16, a marine non-tailed vibriophage with an unusual symmetry-mismatched vertex arrangement.PLoS pathogens · 2026Article
- Predicting water at the protein interface in cryo-EM structures from MD-excess chemical potential.Biophysical journal · 2026Article
- Structures of the sodium-coupled phosphate importer SLC34A2 reveal a distinct architecture and gating mechanism.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Direct lipid interactions control SARS-CoV-2 M protein conformational dynamics and virus assembly.Nature communications · 2026Article
- Single-Sequence Deep Learning Delivers Crystal-Quality Models of Covalent K-Ras G12 Hotspot Complexes.IUBMB life · 2026Article
- Structural insights into coffee bitter taste perception by TAS2R43 receptor.Nature structural & molecular biology · 2026Article
- Structural analysis reveals that water molecules mediate self-activation of GPR99.Communications biology · 2026Article
- Towards patient-relevant structures: reviewing body-temperature biological macromolecules and their ligands for pharmaceutical applications.Acta crystallographica. Section D, Structural biology · 2026Review
- Transient ion-mediated interactions regulate subunit rotation in a eukaryotic ribosome.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
At sufficiently high resolution, x-ray crystallography and cryogenic electron microscopy are capable of resolving small spherical map features corresponding to either water or ions. Correct classification of these sites provides crucial insight for understanding structure and function as well as guiding downstream design tasks, including structure-based drug discovery and de novo biomolecule design. However, direct identification of these sites from experimental data can prove challenging, and existing empirical approaches leveraging the local environment can only characterize limited ion types. We present a representation of chemical environments using interaction fingerprints and develop a machine learning model to predict the identity of input water and ion sites. We validate the method, named Metric Ion Classification (MIC), on a wide variety of biomolecular examples to demonstrate its utility, identifying many probable mismodeled ions deposited in the PDB. Compared to existing methods, MIC achieves superior accuracy for uniquely classifying water/ion sites while expanding the set of potential site identities. Finally, we collect all steps of this approach into an easy-to-use open-source package that can integrate with existing structure determination pipelines, and we provide a ChimeraX implementation to further enable use of the tool.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.