Overcoming the Rare Event Sampling Problem in Biological Systems with Infinite Swapping

Area of Science:

• Computational biology
• Biophysics
• Molecular dynamics

Background:

• Rare event sampling is crucial for understanding molecular processes.
• Parallel tempering (PT) is a common method but can be limited.
• Infinite swapping (INS) is a novel approach to enhance sampling efficiency.

Purpose of the Study:

• To evaluate the efficiency of Infinite Swapping (INS) compared to Parallel Tempering (PT).
• To assess INS performance across diverse biological systems with varying sampling challenges.
• To investigate the impact of symmetrized distributions and enhanced replica exchange in INS.

Main Methods:

• Implementation of Infinite Swapping (INS) using an expanded computational ensemble.
• Application of INS to three distinct biological systems: blocked alanine dipeptide, Villin headpiece, and neuroglobin.
• Quantitative comparison of sampling efficiency between INS and PT.

Main Results:

• Infinite Swapping (INS) demonstrated substantially higher sampling efficiency across all tested biological systems.
• Symmetrization of configurations in temperature space enhanced information exchange between replicas.
• INS proved effective for small molecule dynamics, protein folding, and substate sampling in folded proteins.

Conclusions:

• Infinite Swapping (INS) is a more efficient method for rare event sampling in computational biology.
• The enhanced information exchange in INS significantly accelerates the exploration of conformational landscapes.
• INS offers a powerful alternative to PT for complex biological simulations.