Inferring protein dynamics through experiment and simulation: collective modes from atomic trajectories

Proteins are evolved molecular machines that carry out the essential chemical reactions necessary for life. Like machines designed by humans, proteins execute their functions through an orderly set of motions and fluctuations - their “reaction coordinate”. However, proteins are also marginally stable, with the expectation that functional dynamics are embedded in small subspace of a high dimensional pattern of overall motions. Here, we aim to discover the embedded functional dynamics using experiment and simulation.

One approach to studying intramolecular fluctuations is computational simulation of atomic trajectories. Recent advances in experimental protein dynamics open up the ability to test, validate, and possibly improve the process of molecular simulation through direct comparisons between prediction and data. We describe two such comparative analyses using data from X-ray diffraction studies reporting electric field-stimulated excited state motions and evolutionarily conserved room-temperature conformational fluctuations. The goal is then to use both simulation and experiment to infer the effective variables describing functional, collective motions in proteins. This work initiates a path towards understanding the physics of protein function and evolution.