Source 1review2025MED
Toolkit/cryo-electron microscopy
cryo-electron microscopy
Also known as: cryo-EM
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Recent breakthroughs in cryo-electron microscopy (cryo-EM) and artificial intelligence (AI)-based structure prediction have revolutionized protein modeling by enabling near-atomic resolution visualization.
Usefulness & Problems
No literature-backed usefulness or problem-fit explainer has been materialized for this record yet.
Published Workflows
Objective: Integrate experimental cryo-EM data with AI-based structure prediction to accelerate protein structure-function analysis and modeling of challenging targets.
Why it works: The review describes cryo-EM and AI as complementary, with cryo-EM providing experimental structural information and AI providing accurate computational predictions from sequence.
near-atomic experimental visualizationsequence-to-structure predictionmap-guided model integrationcryo-EMadvanced image processingdeep learning structure prediction
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete method used to build, optimize, or evolve an engineered system.
Mechanisms
Conformational UncagingTarget processes
No target processes tagged yet.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
Cryo-EM and AI-based structure prediction have revolutionized protein modeling by enabling near-atomic resolution visualization and highly accurate computational predictions from amino acid sequences.
Cryo-EM and AI have complementary roles in modern protein structural biology.
AlphaFold predictions have been combined with cryo-EM maps to explore conformational diversity in cytochrome P450 enzymes.
These technologies facilitate detailed insights into challenging protein targets including membrane proteins, flexible and intrinsically disordered proteins, and large macromolecular complexes.
Approval Evidence
1 source4 linked approval claimsfirst-pass slug cryo-electron-microscopy
Recent breakthroughs in cryo-electron microscopy (cryo-EM) and artificial intelligence (AI)-based structure prediction have revolutionized protein modeling by enabling near-atomic resolution visualization.
Source:
capability summarysupports
Cryo-EM and AI-based structure prediction have revolutionized protein modeling by enabling near-atomic resolution visualization and highly accurate computational predictions from amino acid sequences.
Source:
complementaritysupports
Cryo-EM and AI have complementary roles in modern protein structural biology.
Source:
integration examplesupports
AlphaFold predictions have been combined with cryo-EM maps to explore conformational diversity in cytochrome P450 enzymes.
Source:
use case scopesupports
These technologies facilitate detailed insights into challenging protein targets including membrane proteins, flexible and intrinsically disordered proteins, and large macromolecular complexes.
Source:
Comparisons
No literature-backed comparison notes have been materialized for this record yet.
Ranked Citations
- 1.