Constrained Unfolding of a Helical Peptide: Implicit versus Explicit Solvents

Area of Science:

• Computational Chemistry
• Biophysics
• Molecular Dynamics

Background:

• Steered Molecular Dynamics (SMD) is effective for calculating potential of mean force (PMF) during peptide unfolding but is computationally expensive, especially in explicit solvents.
• Adaptive steered molecular dynamics (ASMD) improves computational efficiency by staging trajectory calculations.

Purpose of the Study:

• To evaluate the computational advantage of ASMD, specifically naive ASMD and full-relaxation ASMD (FR-ASMD), for peptide unfolding simulations.
• To compare the energetics and hydrogen-bonding pathways of peptide unfolding in explicit and implicit solvents using ASMD methods.

Main Methods:

• Employed naive ASMD and FR-ASMD to simulate the unfolding of a benchmark peptide initially in an α-helical structure.
• Calculated potential of mean force (PMF) and analyzed hydrogen-bonding patterns along the unfolding pathways.
• Compared results obtained in explicit water environments with those from implicit solvent models.

Main Results:

• ASMD significantly reduces the computational cost compared to conventional SMD.
• Peptide unfolding energetics differ substantially between vacuum and solvent environments but show similarity between implicit and explicit solvents.
• Hydrogen-bonding pathways during helix opening are comparable in implicit and explicit solvents, despite the known importance of solvent interactions.

Conclusions:

• FR-ASMD and naive ASMD provide efficient alternatives to conventional SMD for studying peptide unfolding energetics and mechanisms.
• Implicit solvent models can effectively capture the essential energetics and hydrogen-bonding dynamics of peptide unfolding observed in explicit solvents.
• The findings suggest that ASMD methods are valuable tools for investigating biomolecular processes with reduced computational overhead.