Brewing COFFEE: A Sequence-Specific Coarse-Grained Energy Function for Simulations of DNA-Protein Complexes

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• DNA-protein interactions are crucial for fundamental biological processes like transcription and chromosome folding.
• Accurate computational models are needed to understand the structural and dynamic properties of these interactions.

Purpose of the Study:

• Introduce COFFEE (Coarse-grained Force Field for Energy Estimation), a new computational framework for simulating DNA-protein complexes.
• Develop a transferable model that accurately predicts structural and dynamic properties without recalibrating existing force fields.

Main Methods:

• Integrated the self-organized polymer model with protein side-chains and a three-interaction site model for DNA.
• Incorporated a sequence-specific DNA-protein interaction statistical potential (SP) derived from crystal structures.
• Validated the model by comparing simulated crystallographic B-factors, scattering profiles, and NMR chemical shifts with experimental data.

Main Results:

• COFFEE quantitatively reproduces crystallographic B-factors for DNA-protein complexes of varying sizes and topologies.
• Simulated scattering profiles align with small-angle X-ray scattering experiments, and chemical shifts are consistent with NMR data.
• The model accurately describes nucleosome unraveling and explains mutation effects on stability, including ARG to LYS substitutions.

Conclusions:

• COFFEE is a robust and transferable framework for simulating DNA-protein complexes at the molecular length scale.
• The model's ability to predict experimental data without force-field recalibration highlights its efficiency and accuracy.
• COFFEE provides a promising tool for investigating diverse DNA-protein interactions in biophysical processes.