The MARTINI Coarse-Grained Force Field: Extension to Proteins

Area of Science:

• Computational Biology
• Biophysics
• Molecular Modeling

Background:

• Atomistic simulations are limited to short timescales, hindering the study of large biological phenomena like protein dynamics and self-assembly.
• Coarse-grained (CG) molecular modeling extends simulation capabilities to larger length and time scales, bridging atomistic and mesoscopic regimes.

Purpose of the Study:

• To develop and validate a new coarse-grained (CG) protein model as an extension of the MARTINI force field.
• To assess the model's accuracy in simulating peptide-bilayer systems, including amino acid and peptide partitioning and membrane pore formation.

Main Methods:

• Calculated potential of mean force for amino acids in a dioleoylphosphatidylcholine (DOPC) lipid bilayer.
• Compared amino acid association constants, pentapeptide partitioning, WALP23 partitioning/orientation in DOPC, and KALP peptide partitioning in dimyristoylphosphatidylcholine (DMPC) and dipalmitoylphosphatidylcholine (DPPC) bilayers.
• Simulated magainin-induced transmembrane pore formation and systematically investigated polyalanine-leucine peptide partitioning in DPPC bilayers.

Main Results:

• The CG model demonstrated good agreement with atomistic simulations for various peptide-bilayer interactions.
• The model successfully reproduced the expected trends in peptide partitioning based on length and leucine content.
• Simulations of magainin showed the formation of disordered toroidal pores, consistent with previous atomistic studies.

Conclusions:

• The developed CG protein model is computationally efficient.
• The model accurately reproduces peptide-lipid interactions and the partitioning behavior of amino acids and peptides in lipid bilayers.
• This CG model serves as a valuable tool for studying biological phenomena on larger scales.