RosettaES

RosettaES performs de novo model completion of macromolecular structures within cryo-electron microscopy (cryo-EM) density maps at moderate resolutions (3–5 Å) using enumerative fragment-based sampling.

Key Features:

• Enumerative fragment-based sampling: Employs fragment-based enumerative sampling to position smaller structural fragments into cryo-EM density for de novo model completion.
• Moderate-resolution targeting: Specifically addresses atom-placement ambiguity in cryo-EM maps at 3–5 Å resolution.
• Automated operation: Executes automated computational sampling and model completion workflows without manual fragment placement steps.
• Benchmark performance: Identified near-native conformations in 85% of segments on a benchmark set of nine proteins.
• Application to challenging structures: Has been applied to determine models for three particularly challenging macromolecular structures.

Scientific Applications:

• Atomic-level model building: Enables construction of atomic-detail models from moderate-resolution cryo-EM density maps.
• Protein structure determination: Supports de novo reconstruction of protein segments when templates are unavailable or incomplete.
• Structure-function studies: Facilitates investigation of protein structure and inferred functional mechanisms from EM-derived models.
• Drug design and molecular interactions: Provides structural models useful for analyzing molecular interactions and supporting structure-based drug design hypotheses.

Methodology:

Uses enumerative fragment-based sampling applied to cryo-EM density maps for automated de novo model completion, validated on a nine-protein benchmark and applied to three challenging structures.