Accelerating atomistic simulations of proteins using multiscale enhanced sampling with independent tempering.

Area of Science:

• Computational biology
• Molecular dynamics
• Biophysics

Background:

• Efficient conformational sampling is crucial for accurate protein simulations.
• Multiscale enhanced sampling (MSES) couples atomistic and coarse-grained (CG) simulations to accelerate sampling.
• Hamiltonian replica exchange removes bias from MSES, combining atomistic accuracy with CG speed.

Purpose of the Study:

• To extend MSES for independent control of atomistic and CG simulation temperatures.
• To introduce a new algorithm, MSES with independent tempering (MSES-IT), for enhanced sampling efficiency.
• To improve Hamiltonian and temperature replica exchange protocols.

Main Methods:

• Directly scaling atomistic and CG Hamiltonians to control effective temperatures.
• Implementing MSES-IT with advanced replica exchange protocols.
• Utilizing a beta-hairpin model to test the algorithm's performance.

Main Results:

• Setting the CG model's effective temperature to its melting temperature maximized CG transition rates.
• MSES-IT demonstrated more efficient replica exchange and diffusion in the condition space.
• Faster reversible transitions at the atomic level and improved conformational ensemble generation were observed compared to original MSES.

Conclusions:

• MSES-IT significantly enhances protein simulation efficiency and accuracy.
• Independent tempering offers a powerful strategy for optimizing multiscale simulations.
• The method provides a superior approach for generating converged conformational ensembles.