Prediction of Sub-Monomer A2 Domain Dynamics of the von Willebrand Factor by Machine Learning Algorithm and Coarse-Grained Molecular Dynamics Simulation.

We develop a machine learning tool useful for predicting the instantaneous dynamical state of sub-monomer features within long linear polymer chains, as well as extracting the dominant macromolecular motions associated with sub-monomer behaviors of interest. We employ the tool to better understand and predict sub-monomer A2 domain unfolding dynamics occurring amidst the dominant large-scale macromolecular motions of the biopolymer von Willebrand Factor (vWF) immersed in flow. Results of coarse-grained Molecular Dynamics (MD) simulations of non-grafted vWF multimers subject to a shearing flow were used as input variables to a Random Forest Algorithm (RFA). Twenty unique features characterizing macromolecular conformation information of vWF multimers were used for training the RFA. The corresponding responses classify instantaneous A2 domain state as either folded or unfolded, and were directly taken from coarse-grained MD simulations. Three separate RFAs were trained using feature/response data of varying resolution, which provided deep insights into the highly correlated macromolecular dynamics occurring in concert with A2 domain unfolding events. The algorithm is used to analyze results of simulation, but has been developed for use with experimental data as well.

Internal Tensile Force and A2 Domain Unfolding of von Willebrand Factor Multimers in Shear Flow.

Using Brownian molecular dynamics simulations, we examine the internal dynamics and biomechanical response of von Willebrand factor (vWF) multimers subject to shear flow. The coarse grain multimer description employed here is based on a monomer model in which the A2 domain of vWF is explicitly represented by a nonlinear elastic spring whose mechanical response was fit to experimental force/extension data from vWF monomers. This permits examination of the dynamic behavior of hydrodynamic forces acting on A2 domains as a function of shear rate and multimer length, as well as position of an A2 domain along the multimer contour. Force/position data reveal that collapsed multimers exhibit a force distribution with two peaks, one near each end of the chain; unraveled multimers, however, show a single peak in A2 domain force near the center of multimers. Guided further by experimental data, significant excursions of force acting on a domain are associated with an increasing probability for A2 domain unfolding. Our results suggest that the threshold shear rate required to induce A2 domain unfolding is inversely proportional to multimer length. By examining data for the duration and location of significant force excursions, convincing evidence is advanced that unfolding of A2 domains, and therefore scission of vWF multimers by the size-regulating blood enzyme ADAMTS13, happen preferentially near the center of unraveled multimers.

Lipid-dependent conformational dynamics underlie the functional versatility of T-cell receptor.

T-cell receptor-CD3 complex (TCR) is a versatile signaling machine that can initiate antigen-specific immune responses based on various biochemical changes of CD3 cytoplasmic domains, but the underlying structural basis remains elusive. Here we developed biophysical approaches to study the conformational dynamics of CD3ε cytoplasmic domain (CD3εCD). At the single-molecule level, we found that CD3εCD could have multiple conformational states with different openness of three functional motifs, i.e., ITAM, BRS and PRS. These conformations were generated because different regions of CD3εCD had heterogeneous lipid-binding properties and therefore had heterogeneous dynamics. Live-cell imaging experiments demonstrated that different antigen stimulations could stabilize CD3εCD at different conformations. Lipid-dependent conformational dynamics thus provide structural basis for the versatile signaling property of TCR.