Docking-based long timescale simulation of cell-size protein systems at atomic resolution

Abstract

Computational methodologies are increasingly addressing modeling of the whole cell at the molecular level. Proteins and their interactions are the key component of cellular processes. Techniques for modeling protein interactions, so far, have included protein docking and molecular simulation. The latter approaches account for the dynamics of the interactions, but are relatively slow, if carried out at all-atom resolution, or are significantly coarse-grained. Protein docking algorithms are far more efficient in sampling spatial coordinates. However, they do not account for the kinetics of the association (i.e., they do not involve the time coordinate). Our proof-of-concept study bridges the two modeling approaches, developing an approach that can reach unprecedented simulation timescales at all-atom resolution. The global intermolecular energy landscape of a large system of proteins was mapped by the pairwise Fast Fourier Transform docking and sampled in space and time by Monte Carlo simulations. The simulation protocol was parametrized on existing data and validated on a number of observations from experiments and molecular dynamics simulations. The simulation protocol performed consistently across very different systems of proteins at different protein concentrations. It recapitulated data on the previously observed protein diffusion rates and aggregation. The speed of calculation allows reaching second-long trajectories of protein systems that approach the size of the cells, at atomic resolution.

Modeling reveals the strength of weak interactions in stacked ring assembly

“…While some work has been done using molecular dynamics to study the assembly of molecular machines like the ribosome (46)(47)(48)(49)(50), there has been comparatively little work investigating the assembly of rings and stacked rings like the proteasome. One difficulty is time scale; under standard in vitro assembly conditions, the proteasome CP self-assembly reaction takes about 3 hours to reach completion (31,51), which is well beyond the reach of currently-available biophysical simulation techniques (52,53). It is thus critical to develop computational and mathematical models of assembly that allow us to systematically explore assembly dynamics on realistic timescales.…”

Prediction of protein interactions is essential for studying biomolecular mechanisms

“…An important activity in the protein docking/scoring field are the community-wide critical assessment efforts [8], which provide platforms for the objective blind assessment of the predictive approaches. The progress in structural modeling of macromolecular complexes is propelling growing interest in larger systems, up to the level of a whole cell [9][10][11]. Such modeling addresses protein interactions in vivo, in a crowded cellular environment.…”