Fragon: rapid high-resolution structure determination from ideal protein fragments

Area of Science:

• Structural biology
• X-ray crystallography
• Computational methods

Background:

• Molecular replacement (MR) is crucial for determining protein structures, but requires a known homologous structure.
• Existing pipelines for MR using ideal fragments have limitations.
• There is a need for efficient methods to solve protein structures without templates.

Purpose of the Study:

• To introduce Fragon, a novel computational pipeline for protein structure determination.
• To utilize ideal protein fragments (alpha-helices, beta-strands) for phasing in the absence of template structures.
• To improve phase accuracy through density modification for automated model building.

Main Methods:

• Fragon employs Phaser for placing ideal protein fragments.
• Phases derived from fragment placement are refined using ACORN density modification.
• ACORN's scoring algorithm reliably identifies successful phasing outcomes.

Main Results:

• Fragon achieved success rates of 61% for mixed alpha/beta folds and 30% for all-beta folds.
• The pipeline was evaluated on datasets with resolutions between 1.0 and 1.7 Å.
• In 70% of successful cases, structure solution was completed in under 30 minutes on standard hardware.

Conclusions:

• Fragon provides a rapid and effective method for protein structure solution using molecular replacement with ideal fragments.
• The generated phases are of sufficient quality to enable complete automated model building.
• This pipeline offers a valuable tool for structural biology, particularly when template structures are unavailable.