Enhanced conformational sampling using enveloping distribution sampling.

Area of Science:

• Computational Biochemistry
• Molecular Dynamics Simulations
• Protein Folding

Background:

• Insufficient conformational sampling is a major challenge in biomolecular simulations.
• Standard molecular dynamics (MD) struggles with systems having high energy barriers between states, like distinct helical folds in peptides.
• Previous attempts using soft-core interactions improved transitions but neglected relevant configurations.

Purpose of the Study:

• To address the challenge of insufficient conformational sampling in biomolecular simulations.
• To propose and demonstrate an application of Enveloping Distribution Sampling (EDS) for enhanced sampling efficiency.
• To accurately determine the conformational equilibrium and free enthalpy difference between two helical states of a hexa-β-peptide.

Main Methods:

• Utilized Enveloping Distribution Sampling (EDS) with a two-state reference Hamiltonian.
• Simulated a hexa-β-peptide exhibiting two distinct helical folds (right-handed 2.7(10/12)-helix and left-handed 3(14)-helix).
• Compared EDS simulations with standard MD simulations using the GROMOS 53A6 force field.

Main Results:

• EDS simulations significantly increased the number of transitions between the two helical states compared to standard MD.
• EDS achieved faster convergence of the relative free enthalpy between the helices.
• The EDS approach ensured sampling of physically relevant conformations while enhancing inter-helical transitions.

Conclusions:

• The proposed EDS application effectively enhances conformational sampling efficiency in biomolecular simulations.
• EDS provides a powerful technique for studying systems with high energy barriers, like complex peptide folding.
• Combined with potential energy surface smoothing, EDS offers a robust method for accurate free enthalpy calculations.