Anomalous Rotational Dynamics of Proteins on Surfaces
April 11, 2022
(A-C) Schematic of angular states (top-panel of A-C) and HS-AFM snapshots (bottom panel of A-C) of protein nanorods in their energetically preferred orientations, corresponding to specific directions of the mineral lattice. (D) Orientational free energy landscape and heat map of relative populations at each angle determined from deep learning analysis of HS-AFM data.
Quantified the rotational dynamics of proteins at a solid-liquid interface, revealing the coexistence of Brownian motion and non-classical jumps between minima in the orientational energy landscape.
Significance and Impact
These new insights on the dynamic processes of biomolecular assembly at solid-liquid interfaces will enable better control over synthesis of bioinspired composites and understanding of their behavior.
Protein motion on a mineral surface was tracked by high-speed atomic force microscopy (HS-AFM)
Deep learning enabled automated analysis of energy landscapes and inter-minima transitions
Comparison with kinetic Monte Carlo simulations revealed two modes of rotation: Brownian motion between adjacent states and activated processes that enable large jumps between non-adjacent states.