Timing Correlations in Proteins Predict Functional Modules and Dynamic Allostery.

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• The relationship between protein structure and function is complex and not fully elucidated.
• Existing methods often fail to capture long-range intraprotein communication that occurs without significant conformational changes.

Purpose of the Study:

• To investigate how functional information is encoded in protein dynamics.
• To introduce a novel method for quantifying timing correlations in protein motions.

Main Methods:

• Development and application of the conditional activity function.
• Analysis of microseconds-long atomistic simulations for three proteins.
• Computation of conditional activities between side-chain dihedral angles.

Main Results:

• Identified that functional information is encoded in the timing of protein motions, not motion itself.
• Demonstrated long-range dynamical correlations (up to 7 nm) between sparse side-chain pairs using the conditional activity function.
• Observed short-range (<1 nm) structural correlations, contrasting with the long-range dynamical correlations.

Conclusions:

• The conditional activity function effectively quantifies timing correlations in protein dynamics.
• Dynamical correlations reveal functional modules and allosteric connections within proteins.
• This approach offers new insights into the structure-function paradigm by focusing on motion timing.