Concurrent Identification and Characterization of Protein Structure and Continuous Internal Dynamics with REDCRAFT

Area of Science:

• Biochemistry
• Computational Biology
• Structural Biology

Background:

• Protein internal dynamics are crucial for biological function, yet experimental separation from structure is challenging.
• Existing methods struggle to meaningfully deconvolute protein structure and dynamics from experimental data.

Purpose of the Study:

• To present REDCRAFT, a novel computational approach for concurrent characterization of protein structure and dynamics.
• To demonstrate REDCRAFT's ability to identify and analyze distinct dynamical regions within a protein.

Main Methods:

• Applied REDCRAFT to dihydrofolate reductase (DHFR) with a simulated mixed-mode internal dynamics model.
• Generated Nuclear Magnetic Resonance (NMR) Residual Dipolar Coupling (RDC) data from simulated molecular trajectories.
• Utilized traditional and context-specific restraints for structure calculations.

Main Results:

• REDCRAFT successfully identified distinct dynamical regions and recovered protein fragments with high accuracy (bb-rmsd < 1 Å).
• Compared to traditional restraints, context-specific restraints improved fragment structure recovery (bb-rmsd < 3 Å).
• The REDCRAFT Dynamic Profile enabled accurate assembly of identified protein domains based on their dynamical behavior.

Conclusions:

• REDCRAFT effectively identifies protein dynamical domains and recovers meaningful structural information.
• The approach facilitates the relative assembly of protein domains based on their dynamic profiles.
• REDCRAFT offers a powerful computational tool for analyzing protein structure-dynamics relationships.