Temperature-Shuffled Structural Dissimilarity Sampling Based on a Root-Mean-Square Deviation.

Area of Science:

• Computational Chemistry
• Biophysics
• Molecular Dynamics

Background:

• Conformational sampling is crucial for understanding protein dynamics and function.
• Existing methods like structural dissimilarity sampling (SDS) have limitations in exploring complex transitions.

Purpose of the Study:

• To introduce and validate a novel enhanced conformational sampling method, temperature-shuffled SDS (TSF-SDS).
• To assess the efficiency of TSF-SDS in promoting and characterizing protein conformational transitions.

Main Methods:

• Developed TSF-SDS by incorporating temperature shuffling into the SDS cycle.
• Defined structural dissimilarity using root-mean-square deviation (RMSD) among snapshots.
• Applied TSF-SDS to T4 lysozyme (T4L) for open-closed transition studies in explicit water.

Main Results:

• TSF-SDS successfully reproduced T4L's domain motion within nanosecond timescales.
• Conventional SDS without temperature shuffling failed to promote the T4L transition.
• TSF-SDS efficiently identified the native state of trp-cage and ubiquitin dimer dissociation.

Conclusions:

• TSF-SDS significantly improves conformational sampling efficiency compared to conventional SDS.
• The method is effective for exploring essential conformational transitions in proteins.
• TSF-SDS demonstrates broad applicability in molecular simulations.