Inside the chaperonin toolbox: theoretical and computational models for chaperonin mechanism

Nanomanufacturing: A Perspective

Nanomanufacturing, the commercially scalable and economically sustainable mass production of nanoscale materials and devices, represents the tangible outcome of the nanotechnology revolution. In contrast to those used in nanofabrication for research purposes, nanomanufacturing processes must satisfy the additional constraints of cost, throughput, and time to market. Taking silicon integrated circuit manufacturing as a baseline, we consider the factors involved in matching processes with products, examining the characteristics and potential of top-down and bottom-up processes, and their combination. We also discuss how a careful assessment of the way in which function can be made to follow form can enable high-volume manufacturing of nanoscale structures with the desired useful, and exciting, properties.

The dynamic conformational cycle of the group I chaperonin C-termini revealed via molecular dynamics simulation

Chaperonins are large ring shaped oligomers that facilitate protein folding by encapsulation within a central cavity. All chaperonins possess flexible C-termini which protrude from the equatorial domain of each subunit into the central cavity. Biochemical evidence suggests that the termini play an important role in the allosteric regulation of the ATPase cycle, in substrate folding and in complex assembly and stability. Despite the tremendous wealth of structural data available for numerous orthologous chaperonins, little structural information is available regarding the residues within the C-terminus. Herein, molecular dynamics simulations are presented which localize the termini throughout the nucleotide cycle of the group I chaperonin, GroE, from Escherichia coli. The simulation results predict that the termini undergo a heretofore unappreciated conformational cycle which is coupled to the nucleotide state of the enzyme. As such, these results have profound implications for the mechanism by which GroE utilizes nucleotide and folds client proteins.

Effects of confinement on the structure and dynamics of an intrinsically disordered peptide: a molecular-dynamics study

In vivo, proteins and peptides are exposed to radically different environments than those in bulk. Because of the abundance of other cellular components, proteins perform their function in crowded and confined spaces. Confinement has been shown to alter the structure, dynamics, and folding of proteins that possess a native fold. Little is known, however, of the effects of confinement on biologically important intrinsically disordered proteins or peptides (IDP). Here, we use extensive molecular dynamics simulations to investigate the effects of confinement in an IDP, the Aβ21-30, a central folding nucleus of the full length amyloid β-protein. In this study, we report results derived from 107 μs of molecular dynamics simulations that subjected the Aβ21-30 to two types of confinement: hydrophilic and hydrophobic pores. Results show that turn structures are enhanced as a function of decreasing pore size (increasing confinement) over other structures, including coils, β-hairpins, and bridges. However, the percentage occurrence of the dominant hydrogen bond between amino acids Asp23 and Ser26 shown to stabilize the turn in bulk simulations does not increase as a function of confinement signifying a disconnect between structure and internal hydrogen bonding. Differences in structure and dynamics of the decapeptide due to hydrophilic and hydrophobic confinement are more apparent at the extreme confinement conditions, where a reduction of the available phase space in hydrophilic confinement is explained in terms of interactions between the decapeptide and a layer of water at the interface between the decapeptide and the surface of the pore, and a smaller size of the decapeptide in the hydrophobic pores is rationalized in terms of peptide-surface interactions.

Using simulations to provide the framework for experimental protein folding studies

Molecular dynamics simulations are a powerful theoretical tool to model the protein folding process in atomistic details under realistic conditions. Combined with a number of experimental techniques, simulations provide a detailed picture of how a protein folds or unfolds in the presence of explicit solvent and other molecular species, such as cosolvents, osmolytes, cofactors, active binding partners or inert crowding agents. The denaturing effects of temperature, pressure and external mechanical forces can also be probed. Qualitative and quantitative agreement with experiment contributes to a comprehensive molecular picture of protein states along the folding/unfolding pathway. The variety of systems examined reveals key features of the protein folding process.

Simulation of chaperonin effect on protein folding: a shift from nucleation-condensation to framework mechanism

The iterative annealing mechanism (IAM) of chaperonin-assisted protein folding is explored in a framework of a well-established coarse-grained protein modeling tool, which enables the study of protein dynamics in a time-scale well beyond classical all-atom molecular mechanics. The chaperonin mechanism of action is simulated for two paradigm systems of protein folding, B domain of protein A (BdpA) and B1 domain of protein G (GB1), and compared to chaperonin-free simulations presented here for BdpA and recently published for GB1. The prediction of the BdpA transition state ensemble (TSE) is in perfect agreement with experimental findings. It is shown that periodic distortion of the polypeptide chains by hydrophobic chaperonin interactions can promote rapid folding and leads to a decrease in folding temperature. It is also demonstrated how chaperonin action prevents kinetically trapped conformations and modulates the observed folding mechanisms from nucleation-condensation to a more framework-like.

Protein functional landscapes, dynamics, allostery: a tortuous path towards a universal theoretical framework

Energy landscape theories have provided a common ground for understanding the protein folding problem, which once seemed to be overwhelmingly complicated. At the same time, the native state was found to be an ensemble of interconverting states with frustration playing a more important role compared to the folding problem. The landscape of the folded protein – the native landscape – is glassier than the folding landscape; hence, a general description analogous to the folding theories is difficult to achieve. On the other hand, the native basin phase volume is much smaller, allowing a protein to fully sample its native energy landscape on the biological timescales. Current computational resources may also be used to perform this sampling for smaller proteins, to build a ‘topographical map’ of the native landscape that can be used for subsequent analysis. Several major approaches to representing this topographical map are highlighted in this review, including the construction of kinetic networks, hierarchical trees and free energy surfaces with subsequent structural and kinetic analyses. In this review, we extensively discuss the important question of choosing proper collective coordinates characterizing functional motions. In many cases, the substates on the native energy landscape, which represent different functional states, can be used to obtain variables that are well suited for building free energy surfaces and analyzing the protein's functional dynamics. Normal mode analysis can provide such variables in cases where functional motions are dictated by the molecule's architecture. Principal component analysis is a more expensive way of inferring the essential variables from the protein's motions, one that requires a long molecular dynamics simulation. Finally, the two popular models for the allosteric switching mechanism, ‘preexisting equilibrium’ and ‘induced fit’, are interpreted within the energy landscape paradigm as extreme points of a continuum of transition mechanisms. Some experimental evidence illustrating each of these two models, as well as intermediate mechanisms, is presented and discussed.