ArticleMatter2021
CryoFold: determining protein structures and data-guided ensembles from cryo-EM density maps.
Article in Matter, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- From possibility to precision in macromolecular ensemble prediction.Nature methods · 2026Article
- Transient protein structure guides surface diffusion pathways for electron transport in membrane supercomplexes.Nature communications · 2026Article
- CryoAtom improves model building for cryo-EM.Nature structural & molecular biology · 2026Article
- A novel cereblon variant with both exon 8 and 10 deletions in newly diagnosed and relapsed multiple myeloma.Blood neoplasia · 2025Article
- Article
- Unveiling Cas8 dynamics and regulation within a transposon-encoded Cascade-TniQ complex.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025Review
- Structural mechanism of HP1⍺-dependent transcriptional repression and chromatin compaction.Structure (London, England : 1993) · 2024Article
- MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search.Journal of chemical information and modeling · 2024Article
- Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge.Nature methods · 2024Article
- CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2.Nature methods · 2024Article
- DeepMainmast: integrated protocol of protein structure modeling for cryo-EM with deep learning and structure prediction.Nature methods · 2024Article
- Structural insights into the modulation of coronavirus spike tilting and infectivity by hinge glycans.Nature communications · 2023Article
- Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy.Micromachines · 2023Review
- Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike.Biophysical journal · 2023Review
- Guide for determination of protein structural ensembles by combining cryo-EM data with metadynamics.FEBS open bio · 2023Article
- Dynamic conformational switching underlies TFIIH function in transcription and DNA repair and impacts genetic diseases.Nature communications · 2023Article
- Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps.Structure (London, England : 1993) · 2023Article
- Development of hidden Markov modeling method for molecular orientations and structure estimation from high-speed atomic force microscopy time-series images.PLoS computational biology · 2022Article
- Progressive assembly of multi-domain protein structures from cryo-EM density maps.Nature computational science · 2022Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Cryo-electron microscopy (EM) requires molecular modeling to refine structural details from data. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins that cannot be resolved by cryo-EM. Here, we introduce CryoFold - a pipeline of molecular dynamics simulations that determines ensembles of protein structures directly from sequence by integrating density data of varying sparsity at 3-5 Å resolution with coarse-grained topological knowledge of the protein folds. We present six examples showing its broad applicability for folding proteins between 72 to 2000 residues, including large membrane and multi-domain systems, and results from two EMDB competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations, unseen by traditional methods, are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python GUI.
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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.