Abstract
ABSTRACTOne of the major challenges in atomistic simulations of proteins is efficient sampling of pathways associated with rare conformational transitions. Recent developments in statistical methods for computation of direct evolutionary couplings between amino acids within and across polypeptide chains have allowed for inference of native residue contacts, informing accurate prediction of protein folds and multimeric structures. In this study, we assess the use of distances between evolutionarily coupled residues as natural choices for reaction coordinates which can be incorporated into Markov state model-based adaptive sampling schemes and potentially used to predict not only functional conformations but also pathways of conformational change, protein folding, and protein-protein association. We demonstrate the utility of evolutionary couplings in sampling and predicting activation pathways of the β2-adrenergic receptor (β2-AR), folding of the FiP35 WW domain, and dimerization of the E. coli molybdopterin synthase subunits. We find that the time required for β2-AR activation and folding of the WW domain are greatly diminished using evolutionary couplings-guided adaptive sampling. Additionally, we were able to identify putative molybdopterin synthase association pathways and near-crystal structure complexes from protein-protein association simulations.
Highlights
Molecular dynamics (MD) simulation has rapidly advanced into an invaluable tool for understanding the structure-function relationship in biological molecules and providing specific, testable predictions in molecular biology[1,2,3,4,5,6]
As with β2-adrenergic receptor (β2-AR) activation, we found that the time to the folded state from an arbitrarily chosen unfolded state was greatly reduced by using either random or evolutionary couplings-guided adaptive sampling over long serial trajectories with equivalent amounts of simulation time (Fig. 4)
We have demonstrated the utility of using distances between evolutionarily coupled residues as reaction coordinates for adaptive sampling in molecular simulation, extending the use of evolutionary couplings from generation of static structures to accelerating sampling of folding, activation, and association pathways
Summary
Molecular dynamics (MD) simulation has rapidly advanced into an invaluable tool for understanding the structure-function relationship in biological molecules and providing specific, testable predictions in molecular biology[1,2,3,4,5,6]. A key limitation of MD simulation is the difficulty of efficiently sampling conformational ensembles where dynamics take place over computationally vast time-scales[7,8] Countless innovations such as steered MD9, accelerated MD10, and replica exchange MD11 improve the efficiency of sampling but either require subjective choices of reaction coordinates or sacrifice kinetic information for accurate thermodynamics. Regardless of their limitations, these methods and others have achieved great success and have allowed for analysis of protein structure and dynamics in unprecedented detail[12]. In order to move beyond using biomolecular simulation to explain experiments post hoc and better capture the predictive power of molecular simulation, methods allowing biologically relevant conformational states to be identified by computational means must be developed
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