DPD Simulation of Protein Conformations: From α-Helices to β-Structures

Area of Science:

• Computational chemistry
• Biophysics
• Polymer science

Background:

• Polypeptide structure and dynamics are crucial for biological function.
• Coarse-grained molecular dynamics (CGMD) is widely used but computationally intensive.
• Dissipative Particle Dynamics (DPD) offers a faster alternative but requires accurate modeling of specific interactions.

Purpose of the Study:

• To introduce a novel coarse-grained model for Dissipative Particle Dynamics (DPD) simulations of polypeptides.
• To incorporate hydrogen bonding crucial for secondary structure stabilization (α-helices, β-structures).
• To assess the model's capability in simulating conformational transitions and pH-dependent behavior.

Main Methods:

• Developed a coarse-grained model using dissociable Morse bonds to represent peptide group hydrogen bonding.
• Simulated coil-like, globular, α-helical, and β-hairpin configurations of model peptides.
• Investigated the influence of Morse potential parameters, side chain hydrophobicity, and pH on polypeptide conformations.
• Modeled a triblock polypeptide mimicking α-synuclein sequence at different pH values.

Main Results:

• The model successfully simulates transitions between various polypeptide conformations.
• Simulated pH-dependent conformational changes of a model α-synuclein polypeptide align with experimental observations.
• Morse potential parameters and side chain hydrophobicity effectively control simulated structures.

Conclusions:

• The proposed DPD model accurately captures hydrogen bonding essential for polypeptide secondary structures.
• This approach enhances the DPD method's applicability for modeling protein and polypeptide equilibrium and dynamic properties.
• DPD simulations offer a competitive alternative to CGMD, particularly for studying polypeptide transport in confined environments.