Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures

Abstract

Proteins have been found to inhabit a diverse set of threedimensional structures. The dynamics that govern protein interconversion between structures happen over a wide range of time scalespicoseconds to seconds. Our understanding of protein functions and dynamics is largely reliant upon our ability to elucidate physically populated structures. From an experimental structural characterization perspective, we are often limited to measuring the ensemble-averaged structure both in the steady-state and time-resolved regimes. Generating kinetic models and understanding protein structure−function relationships require atomistic knowledge of the populated states in the ensemble. In this Perspective, we present ensemble refinement methodologies that integrate time-resolved experimental signals with molecular dynamics models. We first discuss integration of experimental structural restraints to molecular models in disordered protein systems that adhere to the principle of maximum entropy for creating a complete set of ensemble structures. We then propose strategies to find kinetic pathways between the refined structures, using time-resolved inputs to guide molecular dynamics trajectories and the use of inference to generate tailored stimuli to prepare a desired ensemble of protein states.

Pathfinder: Protein folding pathway prediction based on conformational sampling

“…Convolutional neural networks learn continuous conformational representations generated from protein folding simulations to predict biologically relevant transition paths [ 41 ]. Integrating biological experimental structural constraints into MD models significantly explored protein dynamics trajectories [ 42 ]. The current mainstream method is combining biological experiments and MD to explore protein folding mechanism.…”

The Role of Transient Intermediate Structures in the Unfolding of the Trp-Cage Fast-Folding Protein: Generating Ensembles from Time-Resolved X-ray Solution Scattering with Genetic Algorithms

“…1 Few experimental methods can track protein folding dynamics on time scales shorter than milliseconds and offer relatively low structural resolution. 17 For instance, T-jump time-resolved vibrational spectroscopy methods observe the transient conformations of specific amines and carbonyls, yet concrete global information is lacking. 18,19 An emerging technique, time-resolved X-ray solution scattering (TRXSS), has been shown to capture protein folding dynamics on nanosecond to milliseconds time scales while avoiding spectroscopic probes or biochemical modifications.…”

“…Validation of the simulation results remains as an ongoing challenge, not only for the TC5b Trp-cage unfolding mechanisms, but also for other protein folding problems . Few experimental methods can track protein folding dynamics on time scales shorter than milliseconds and offer relatively low structural resolution . For instance, T-jump time-resolved vibrational spectroscopy methods observe the transient conformations of specific amines and carbonyls, yet concrete global information is lacking. , An emerging technique, time-resolved X-ray solution scattering (TRXSS), has been shown to capture protein folding dynamics on nanosecond to milliseconds time scales while avoiding spectroscopic probes or biochemical modifications. − In this work, we implement T-jump TRXSS to capture the transient conformational states of Trp-cage.…”