Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures.

Area of Science:

• Structural biology
• Computational biophysics
• Biochemistry

Background:

• Proteins exist in diverse 3D structures with dynamics occurring over picoseconds to seconds.
• Understanding protein function requires knowledge of physically populated structures.
• Experimental methods often provide ensemble-averaged structures, limiting atomistic insights.

Purpose of the Study:

• To present ensemble refinement methodologies integrating time-resolved experimental signals with molecular dynamics models.
• To enable the elucidation of atomistic details of populated protein states.
• To facilitate the generation of kinetic models and understanding of protein structure-function relationships.

Main Methods:

• Integrating experimental structural restraints with molecular models using maximum entropy principles for disordered proteins.
• Utilizing time-resolved experimental inputs to guide molecular dynamics trajectories.
• Employing inference to generate tailored stimuli for preparing specific protein state ensembles.

Main Results:

• Development of ensemble refinement methodologies for comprehensive protein structure elucidation.
• Strategies proposed for identifying kinetic pathways between protein structures.
• Integration of experimental data with computational models to capture protein dynamics.

Conclusions:

• The presented methodologies enhance the understanding of protein dynamics and structure-function relationships.
• Combining experimental data with molecular dynamics provides atomistic insights into protein ensembles.
• This approach advances the study of disordered proteins and their functional mechanisms.