Simulation of fluorescence resonance energy transfer experiments: effect of the dyes on protein folding.

Fluorescence resonance energy transfer is a powerful technique which is often used to probe the properties of proteins and complex macromolecules. The technique relies on relatively large fluorescent dyes which are engineered into the molecule of interest. In the case of small proteins, these dyes may affect the stability of the protein, and modify the folding kinetics and the folding mechanisms which are being probed. Here we use atomistic simulation to investigate the effect that commonly used fluorescent dyes have on the folding of a four-helix bundle protein. We show that, depending on where the dyes are attached, their effect on the kinetic and thermodynamic properties of the protein may be significant. We find that, while the overall folding mechanism is not affected by the dyes, they can destabilize, or even stabilize, intermediate states.

Orientational averaging of dye molecules attached to proteins in Förster resonance energy transfer measurements: insights from a simulation study.

Förster resonance energy transfer is an increasingly popular method for studying protein folding at single molecule resolution. By attaching dye molecules to particular residues in a protein molecule and measuring the energy transfer to the acceptor dye on excitation of the donor dye, information about the separation of the dyes can be obtained. Here we use an atomistic coarse-grained molecular model of the protein and dyes to look at the assumption that the dyes rotate freely during the donor decay time. We find that although complete orientational averaging does not always occur, the consequences of this are not extreme. Even in the native state, the errors in efficiency, which result from incorrectly assuming kappa2=2/3, are smaller than the typical experimental error of an efficiency measurement. The orientational freedom of the dyes originates both from the dynamics of the linker and dye molecules and also from the movements of the protein chain itself. In the unfolded state, the movements of the protein chain are sufficient to provide complete, or almost complete, orientational averaging within the donor lifetime. Increasing the rigidity of the dyes therefore has only a very small effect on the measured efficiencies in the unfolded state. In the native state the contribution of the linker and dye dynamics to orientational averaging is larger; nevertheless increasing the rigidity still has only a small effect on the measured efficiency.

Analysis of the free-energy surface of proteins from reversible folding simulations.

Computer generated trajectories can, in principle, reveal the folding pathways of a protein at atomic resolution and possibly suggest general and simple rules for predicting the folded structure of a given sequence. While such reversible folding trajectories can only be determined ab initio using all-atom transferable force-fields for a few small proteins, they can be determined for a large number of proteins using coarse-grained and structure-based force-fields, in which a known folded structure is by construction the absolute energy and free-energy minimum. Here we use a model of the fast folding helical lambda-repressor protein to generate trajectories in which native and non-native states are in equilibrium and transitions are accurately sampled. Yet, representation of the free-energy surface, which underlies the thermodynamic and dynamic properties of the protein model, from such a trajectory remains a challenge. Projections over one or a small number of arbitrarily chosen progress variables often hide the most important features of such surfaces. The results unequivocally show that an unprojected representation of the free-energy surface provides important and unbiased information and allows a simple and meaningful description of many-dimensional, heterogeneous trajectories, providing new insight into the possible mechanisms of fast-folding proteins.

Probing the free energy landscape of the FBP28WW domain using multiple techniques.

The free-energy landscape of a small protein, the FBP 28 WW domain, has been explored using molecular dynamics (MD) simulations with alternative descriptions of the molecule. The molecular models used range from coarse-grained to all-atom with either an implicit or explicit treatment of the solvent. Sampling of conformation space was performed using both conventional and temperature-replica exchange MD simulations. Experimental chemical shifts and NOEs were used to validate the simulations, and experimental phi values both for validation and as restraints. This combination of different approaches has provided insight into the free energy landscape and barriers encountered by the protein during folding and enabled the characterization of native, denatured and transition states which are compatible with the available experimental data. All the molecular models used stabilize well defined native and denatured basins; however, the degree of agreement with the available experimental data varies. While the most detailed, explicit solvent model predicts the data reasonably accurately, it does not fold despite a simulation time 10 times that of the experimental folding time. The less detailed models performed poorly relative to the explicit solvent model: an implicit solvent model stabilizes a ground state which differs from the experimental native state, and a structure-based model underestimates the size of the barrier between the two states. The use of experimental phi values both as restraints, and to extract structures from unfolding simulations, result in conformations which, although not necessarily true transition states, appear to share the geometrical characteristics of transition state structures. In addition to characterizing the native, transition and denatured states of this particular system in this work, the advantages and limitations of using varying levels of representation are discussed.

The effect of increasing the stability of non-native interactions on the folding landscape of the bacterial immunity protein Im9.

How stabilising non-native interactions influence protein folding energy landscapes is currently not well understood: such interactions could speed folding by reducing the conformational search to the native state, or could slow folding by increasing ruggedness. Here, we examine the influence of non-native interactions in the folding process of the bacterial immunity protein Im9, by exploiting our ability to manipulate the stability of the intermediate and rate-limiting transition state (TS) in the folding of this protein by minor alteration of its sequence or changes in solvent conditions. By analysing the properties of these species using Phi-value analysis, and exploration of the structural properties of the TS ensemble using molecular dynamics simulations, we demonstrate the importance of non-native interactions in immunity protein folding and demonstrate that the rate-limiting step involves partial reorganisation of these interactions as the TS ensemble is traversed. Moreover, we show that increasing the contribution to stability made by non-native interactions results in an increase in Phi-values of the TS ensemble without altering its structural properties or solvent-accessible surface area. The data suggest that the immunity proteins fold on multiple, but closely related, micropathways, resulting in a heterogeneous TS ensemble that responds subtly to mutation or changes in the solvent conditions. Thus, altering the relative strength of native and non-native interactions influences the search to the native state by restricting the pathways through the folding energy landscape.

Controlling crystallization and its absence: proteins, colloids and patchy models.

The ability to control the crystallization behaviour (including its absence) of particles, be they biomolecules such as globular proteins, inorganic colloids, nanoparticles, or metal atoms in an alloy, is of both fundamental and technological importance. Much can be learnt from the exquisite control that biological systems exert over the behaviour of proteins, where protein crystallization and aggregation are generally suppressed, but where in particular instances complex crystalline assemblies can be formed that have a functional purpose. We also explore the insights that can be obtained from computational modelling, focussing on the subtle interplay between the interparticle interactions, the preferred local order and the resulting crystallization kinetics. In particular, we highlight the role played by "frustration", where there is an incompatibility between the preferred local order and the global crystalline order, using examples from atomic glass formers and model anisotropic particles.