MAINMAST
MAINMAST constructs complete three-dimensional protein models directly from cryo-electron microscopy (cryo-EM) density maps to enable de novo interpretation of near-atomic-resolution EM data (~4–4.5 Å).
Key Features:
- De Novo Modeling: Performs reference-free model building directly from EM density maps without requiring known structures.
- Fully Automated Pipeline: Executes model construction and analysis without manual intervention.
- Initial C-alpha Model Generation: Produces reliable initial C-alpha backbone models as the basis for atomic-level model building.
- Backbone Tracing and Main-Chain Identification: Traces protein backbone paths and identifies main-chain structures from density maps.
- Amino Acid Sequence Assignment: Assigns amino acid sequences to traced main-chain positions based on the density.
- Candidate Model Pooling: Generates multiple candidate models to represent alternative interpretations of the density.
- Near-Atomic Resolution Capability: Tailored for interpreting EM maps at near-atomic resolution (~4–4.5 Å) to recover backbone structures.
Scientific Applications:
- Interpretation of cryo-EM Density Maps: Enables building atomic models from near-atomic-resolution EM maps for structural analysis.
- Structural Biology and Model Building: Facilitates determination of protein architecture without prior structural information.
- Drug Discovery Support: Provides structural models that can inform structure-based drug design and ligand interpretation.
- Enzyme Mechanism Elucidation: Supplies models to investigate catalytic sites and mechanistic hypotheses.
- Study of Complex Biological Assemblies: Aids characterization of subunit organization and interfaces within macromolecular complexes.
Methodology:
Traces protein backbone directly from EM density maps, generates initial C-alpha backbone models, identifies main-chain structures, assigns amino acid sequences, and produces multiple candidate models using a fully automated de novo modeling protocol tailored for near-atomic-resolution cryo-EM data.
Topics
Details
- Tool Type:
- command-line tool
- Added:
- 1/18/2021
- Last Updated:
- 2/19/2021
Operations
Publications
Terashi G, Zha Y, Kihara D. Protein Structure Modeling from Cryo-EM Map Using MAINMAST and MAINMAST-GUI Plugin. Methods in Molecular Biology. 2020. doi:10.1007/978-1-0716-0708-4_19. PMID:32621234.
PMID: 32621234
Downloads
- Downloads pagehttp://kiharalab.org/mainmast/Downloads.html