Complex Pathways in Folding of Protein G Explored by Simulation and Experiment

Abstract

The B1 domain of protein G has been a classic model system of folding for decades, the subject of numerous experimental and computational studies. Most of the experimental work has focused on whether the protein folds via an intermediate, but the evidence is mostly limited to relatively slow kinetic observations with a few structural probes. In this work we observe folding on the submillisecond timescale with microfluidic mixers using a variety of probes including tryptophan fluorescence, circular dichroism, and photochemical oxidation. We find that each probe yields different kinetics and compare these observations with a Markov State Model constructed from large-scale molecular dynamics simulations and find a complex network of states that yield different kinetics for different observables. We conclude that there are many folding pathways before the final folding step and that these paths do not have large free energy barriers.

Optimized parameter selection reveals trends in Markov state models for protein folding

“…Optionally, a trajectory may be transformed (featurized) from its Cartesian coordinates into a system of internal coordinates. Many recent studies have constructed MSMs by initially featurizing Cartesian coordinates into a backbone-based 21,35,38,45,46 or contactbased 45,[47][48][49] internal coordinate system such as φ and ψ dihedral angles or inter-residue contact distances, respectively. Internal coordinate systems may also include combinations of different types of features.…”

“…35,54,55 In contrast to PCA, tICA describes the slowest degrees of freedom in a dataset by finding linear combinations of features that maximize autocorrelation time. Both PCA 39,47,[56][57][58][59][60][61][62] and tICA 21,35,38,39,46,49,55,63,64 have been used in the analysis of protein folding and conformational change. PCA or tICA FIG. 1.…”

“…3,4 Due to a multitude of computational and algorithmic advances, 5-8 millisecond time scale MD simulations are now feasible, enabling the investigation of protein folding in silico. [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] The analysis of the enormous quantities of data generated by these simulations is currently a major challenge.…”

“…[12][13][14]16,[19][20][21][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38] Building a MSM involves decomposing the phase space sampled by one or more MD trajectories into a set of discrete states and estimating the (conditional) transition probabilities between each pair of states. However, there are many ways to perform the state decomposition, and the choice of MSM building protocol can introduce subjectivity into the analysis.…”

A network of molecular switches controls the activation of the two-component response regulator NtrC

“…MSMs have been used extensively to study large-scale conformational changes involved in protein folding as well as more subtle changes involved in receptor activation and ligand binding [29][30][31][32][33][34][35][36] . This study further supports the utility of MSMs as a natural framework for understanding and quantifying changes in hydrogen bond networks or residue side chain rotations associated with many protein conformational changes in signalling networks.…”