Folding kinetics of proteins: A model study

100th Anniversary of Macromolecular Science Viewpoint: Modeling and Simulation of Macromolecules with Hydrogen Bonds: Challenges, Successes, and Opportunities

Macromolecular materials with directional interactions such as hydrogen bonds exhibit numerous attractive features in terms of structure, thermodynamics, and dynamics. Besides enabling precise tuning of desirable geometries in the assembled state (e.g., programmable coordination numbers depending on the valency of the directional interaction), mixing in a blend/composite through stabilization via hydrogen bonds between the various components, hydrogen bonds can also impart responsiveness to external stimuli (e.g., temperature, pH). In biomacromolecules (e.g., proteins, DNA, polysaccharides), hydrogen bonds play a key role in stabilizing secondary and tertiary structures, which in turn define the function of these macromolecules. In this Viewpoint, I present the challenges, successes, and opportunities for molecular modeling and simulations to conduct fundamental and application-focused research on macromolecular materials with hydrogen bonding interactions. The past successes and limitations of atomistic simulations are discussed first, followed by highlights from recent developments in coarse-grained modeling and their use in studies of (synthetic and biologically relevant) macromolecular materials. Model development focused on polynucleotides (e.g., DNA, RNA, etc.), polypeptides, polysaccharides, and synthetic polymers at experimentally relevant conditions are highlighted. This viewpoint ends with potential future directions for macromolecular modeling and simulations with other types of directional interactions beyond hydrogen bonding.

Force-dependent switch in protein unfolding pathways and transition-state movements

Although it is known that single-domain proteins fold and unfold by parallel pathways, demonstration of this expectation has been difficult to establish in experiments. Unfolding rate, [Formula: see text], as a function of force f, obtained in single-molecule pulling experiments on src SH3 domain, exhibits upward curvature on a [Formula: see text] plot. Similar observations were reported for other proteins for the unfolding rate [Formula: see text]. These findings imply unfolding in these single-domain proteins involves a switch in the pathway as f or [Formula: see text] is increased from a low to a high value. We provide a unified theory demonstrating that if [Formula: see text] as a function of a perturbation (f or [Formula: see text]) exhibits upward curvature then the underlying energy landscape must be strongly multidimensional. Using molecular simulations we provide a structural basis for the switch in the pathways and dramatic shifts in the transition-state ensemble (TSE) in src SH3 domain as f is increased. We show that a single-point mutation shifts the upward curvature in [Formula: see text] to a lower force, thus establishing the malleability of the underlying folding landscape. Our theory, applicable to any perturbation that affects the free energy of the protein linearly, readily explains movement in the TSE in a β-sandwich (I27) protein and single-chain monellin as the denaturant concentration is varied. We predict that in the force range accessible in laser optical tweezer experiments there should be a switch in the unfolding pathways in I27 or its mutants.

Generalized iterative annealing model for the action of RNA chaperones

As a consequence of the rugged landscape of RNA molecules their folding is described by the kinetic partitioning mechanism according to which only a small fraction (φF) reaches the folded state while the remaining fraction of molecules is kinetically trapped in misfolded intermediates. The transition from the misfolded states to the native state can far exceed biologically relevant time. Thus, RNA folding in vivo is often aided by protein cofactors, called RNA chaperones, that can rescue RNAs from a multitude of misfolded structures. We consider two models, based on chemical kinetics and chemical master equation, for describing assisted folding. In the passive model, applicable for class I substrates, transient interactions of misfolded structures with RNA chaperones alone are sufficient to destabilize the misfolded structures, thus entropically lowering the barrier to folding. For this mechanism to be efficient the intermediate ribonucleoprotein complex between collapsed RNA and protein cofactor should have optimal stability. We also introduce an active model (suitable for stringent substrates with small φF), which accounts for the recent experimental findings on the action of CYT-19 on the group I intron ribozyme, showing that RNA chaperones do not discriminate between the misfolded and the native states. In the active model, the RNA chaperone system utilizes chemical energy of adenosine triphosphate hydrolysis to repeatedly bind and release misfolded and folded RNAs, resulting in substantial increase of yield of the native state. The theory outlined here shows, in accord with experiments, that in the steady state the native state does not form with unit probability.

Sequence-dependent folding landscapes of adenine riboswitch aptamers

Expression of a large fraction of genes in bacteria is controlled by riboswitches, which are found in the untranslated region of mRNA. Structurally riboswitches have a conserved aptamer domain to which a metabolite binds, resulting in a conformational change in the downstream expression platform. Prediction of the functions of riboswitches requires a quantitative description of the folding landscape so that the barriers and time scales for the conformational change in the switching region in the aptamer can be estimated. Using a combination of all atom molecular dynamics (MD) and coarse-grained model simulations we studied the response of adenine (A) binding add and pbuE A-riboswitches to mechanical force. The two riboswitches contain a structurally similar three-way junction formed by three paired helices, P1, P2, and P3, but carry out different functions. Using pulling simulations, with structures generated in MD simulations, we show that after P1 rips the dominant unfolding pathway in the add A-riboswitch is the rupture of P2 followed by unraveling of P3. In the pbuE A-riboswitch, after P1 unfolds P3 ruptures ahead of P2. The order of unfolding of the helices, which is in accord with single molecule pulling experiments, is determined by the relative stabilities of the individual helices. Our results show that the stability of isolated helices determines the order of assembly and response to force in these non-coding regions. We use the simulated free energy profile for the pbuE A-riboswitch to estimate the time scale for allosteric switching, which shows that this riboswitch is under kinetic control lending additional support to the conclusion based on single molecule pulling experiments. A consequence of the stability hypothesis is that a single point mutation (U28C) in the P2 helix of the add A-riboswitch, which increases the stability of P2, would make the folding landscapes of the two riboswitches similar. This prediction can be tested in single molecule pulling experiments.

A coarse-grained protein model in a water-like solvent

Simulations employing an explicit atom description of proteins in solvent can be computationally expensive. On the other hand, coarse-grained protein models in implicit solvent miss essential features of the hydrophobic effect, especially its temperature dependence, and have limited ability to capture the kinetics of protein folding. We propose a free space two-letter protein (“H-P”) model in a simple, but qualitatively accurate description for water, the Jagla model, which coarse-grains water into an isotropically interacting sphere. Using Monte Carlo simulations, we design protein-like sequences that can undergo a collapse, exposing the “Jagla-philic” monomers to the solvent, while maintaining a “hydrophobic” core. This protein-like model manifests heat and cold denaturation in a manner that is reminiscent of proteins. While this protein-like model lacks the details that would introduce secondary structure formation, we believe that these ideas represent a first step in developing a useful, but computationally expedient, means of modeling proteins.

Entropic stabilization of the folded states of RNA due to macromolecular crowding

We review the effects of macromolecular crowding on the folding of RNA by considering the simplest scenario when excluded volume interactions between crowding particles and RNA dominate. Using human telomerase enzyme as an example, we discuss how crowding can alter the equilibrium between pseudoknot and hairpin states of the same RNA molecule-a key aspect of crowder-RNA interactions. We summarize data showing that the crowding effect is significant only if the size of the spherical crowding particle is smaller than the radius of gyration of the RNA in the absence of crowding particles. The implication for function of the wild type and mutants of human telomerase is outlined by using a relationship between enzyme activity and its conformational equilibrium. In addition, we discuss the interplay between macromolecular crowding and ionic strength of the RNA buffer. Finally, we briefly review recent experiments which illustrate the connection between excluded volume due to macromolecular crowding and the thermodynamics of RNA folding.

RNA under tension: Folding Landscapes, Kinetic partitioning Mechanism, and Molecular Tensegrity

Non-coding RNA sequences play a great role in controlling a number of cellular functions, thus raising the need to understand their complex conformational dynamics in quantitative detail. In this perspective, we first show that single molecule pulling when combined with with theory and simulations can be used to quantitatively explore the folding landscape of nucleic acid hairpins, and riboswitches with tertiary interactions. Applications to riboswitches, which are non-coding RNA elements that control gene expression by undergoing dynamical conformational changes in response to binding of metabolites, lead to an organization principle that assembly of RNA is determined by the stability of isolated helices. We also point out the limitations of single molecule pulling experiments, with molecular extension as the only accessible parameter, in extracting key parameters of the folding landscapes of RNA molecules.

Replica exchange statistical temperature molecular dynamics algorithm

The replica exchange statistical temperature molecular dynamics (RESTMD) algorithm is presented, designed to alleviate an extensive increase of the number of replicas required as system size increases in the conventional temperature replica exchange method (tREM), and to obtain improved sampling in individual replicas. RESTMD optimally integrates multiple STMD (Phys. Rev. Lett. 2006, 97, 050601) runs with replica exchanges, giving rise to a flat energy sampling in each replica with a self-adjusting weight determination. The expanded flat energy dynamic sampling range allows the use of significantly fewer STMD replicas while maintaining the desired acceptance probability for replica exchanges. The computational advantages of RESTMD over conventional REM and single-replica STMD are explicitly demonstrated with an application to a coarse-grained protein model. The effect of two different kinetic temperature control schemes on the sampling efficiency is explored for diverse simulation conditions.

Denaturant-dependent folding of GFP

We use molecular simulations using a coarse-grained model to map the folding landscape of Green Fluorescent Protein (GFP), which is extensively used as a marker in cell biology and biotechnology. Thermal and Guanidinium chloride (GdmCl) induced unfolding of a variant of GFP, without the chromophore, occurs in an apparent two-state manner. The calculated midpoint of the equilibrium folding in GdmCl, taken into account using the Molecular Transfer Model (MTM), is in excellent agreement with the experiments. The melting temperatures decrease linearly as the concentrations of GdmCl and urea are increased. The structural features of rarely populated equilibrium intermediates, visible only in free energy profiles projected along a few order parameters, are remarkably similar to those identified in a number of ensemble experiments in GFP with the chromophore. The excellent agreement between simulations and experiments show that the equilibrium intermediates are stabilized by the chromophore. Folding kinetics, upon temperature quench, show that GFP first collapses and populates an ensemble of compact structures. Despite the seeming simplicity of the equilibrium folding, flux to the native state flows through multiple channels and can be described by the kinetic partitioning mechanism. Detailed analysis of the folding trajectories show that both equilibrium and several kinetic intermediates, including misfolded structures, are sampled during folding. Interestingly, the intermediates characterized in the simulations coincide with those identified in single molecule pulling experiments. Our predictions, amenable to experimental tests, show that MTM is a practical way to simulate the effect of denaturants on the folding of large proteins.

Application of nonlinear dimensionality reduction to characterize the conformational landscape of small peptides

The automatic classification of the wealth of molecular configurations gathered in simulation in the form of a few coordinates that help to explain the main states and transitions of the system is a recurring problem in computational molecular biophysics. We use the recently proposed ScIMAP algorithm to automatically extract motion parameters from simulation data. The procedure uses only molecular shape similarity and topology information inferred directly from the simulated conformations, and is not biased by a priori known information. The automatically recovered coordinates prove as excellent reaction coordinates for the molecules studied and can be used to identify stable states and transitions, and as a basis to build free-energy surfaces. The coordinates provide a better description of the free energy landscape when compared with coordinates computed using principal components analysis, the most popular linear dimensionality reduction technique. The method is first validated on the analysis of the dynamics of an all-atom model of alanine dipeptide, where it successfully recover all previously known metastable states. When applied to characterize the simulated folding of a coarse-grained model of beta-hairpin, in addition to the folded and unfolded states, two symmetric misfolding crossings of the hairpin strands are observed, together with the most likely transitions from one to the other.

Chasing funnels on protein-protein energy landscapes at different resolutions

Studies of intermolecular energy landscapes are important for understanding protein association and adequate modeling of protein interactions. Landscape representation at different resolutions can be used for the refinement of docking predictions and detection of macro characteristics, like the binding funnel. A representative set of protein-protein complexes was used to systematically map the intermolecular landscape by grid-based docking. The change of the resolution was achieved by varying the range of the potential, according to the variable resolution GRAMM methodology. A formalism was developed to consistently parameterize the potential and describe essential characteristics of the landscape. The results of gradual landscape smoothing, from high to low resolution, indicate that i), the number of energy basins, the landscape ruggedness, and the slope decrease accordingly; ii), the number of near-native matches, defined as those inside the funnel, increases until the trend breaks down at critical resolution; the rate of the increase and the critical resolution are specific to the type of a complex (enzyme inhibitor, antigen-antibody, and other), reflect known underlying recognition factors, and correlate with earlier determined estimates of the funnel size; iii), the native/nonnative energy gap, a major characteristic of the energy minima hierarchy, remains constant; and iv), the putative funnel (defined as the deepest basin) has the largest average depth-related ruggedness and slope, at all resolutions. The results facilitate better understanding of the binding landscapes and suggest directions for implementation in practical docking protocols.

A coarse-grained alpha-carbon protein model with anisotropic hydrogen-bonding

We develop a sequence based alpha-carbon model to incorporate a mean field estimate of the orientation dependence of the polypeptide chain that gives rise to specific hydrogen bond pairing to stabilize alpha-helices and beta-sheets. We illustrate the success of the new protein model in capturing thermodynamic measures and folding mechanism of proteins L and G. Compared to our previous coarse-grained model, the new model shows greater folding cooperativity and improvements in designability of protein sequences, as well as predicting correct trends for kinetic rates and mechanism for proteins L and G. We believe the model is broadly applicable to other protein folding and protein-protein co-assembly processes, and does not require experimental input beyond the topology description of the native state. Even without tertiary topology information, it can also serve as a mid-resolution protein model for more exhaustive conformational search strategies that can bridge back down to atomic descriptions of the polypeptide chain.

An analytical study of the interplay between geometrical and energetic effects in protein folding

Analytical studies have several advantages for an understanding of the mechanisms of protein folding such as the interplay between geometrical and energetic effects. In this paper, we introduce a Gaussian filament with a C(alpha) structure-based (Go) potential as a new theoretical scheme based on a Hamiltonian approach. This model takes into account geometrical information in a realistic fashion without the need of phenomenological descriptions. In order to make this model more appropriate for comparison with protein folding simulations and experiments, we introduce a many-body interaction into the potential term to enhance cooperativity. We apply our new analytical model to a beta-hairpin-type peptide and compare our results with a molecular dynamics simulation of a structure-based model.

Self-assembly of β-sheet forming peptides into chiral fibrillar aggregates

The authors introduce a novel mid-resolution off-lattice coarse-grained model to investigate the self-assembly of beta-sheet forming peptides. The model retains most of the peptide backbone degrees of freedom as well as one interaction center describing the side chains. The peptide consists of a core of alternating hydrophobic and hydrophilic residues, capped by two oppositely charged residues. Nonbonded interactions are described by Lennard-Jones and Coulombic terms. The influence of different levels of "hydrophobic" and "steric" forces between the side chains of the peptides on the thermodynamics and kinetics of aggregation was investigated using Langevin dynamics. The model is simple enough to allow the simulation of systems consisting of hundreds of peptides, while remaining realistic enough to successfully lead to the formation of chiral, ordered beta tapes, ribbons, as well as higher order fibrillar aggregates.

A ternary nucleation model for the nucleation pathway of protein folding

Recently [Y. S. Djikaev and E. Ruckenstein, J. Phys. Chem. B 111, 886 (2007)], the authors proposed a kinetic model for the nucleation mechanism of protein folding where a protein was modeled as a heteropolymer consisting of hydrophobic and hydrophilic beads and the composition of the growing cluster of protein residues was assumed to be constant and equal to the overall protein composition. Here, they further develop the model by considering a protein as a three-component heteropolymer and by allowing the composition of the growing cluster of protein residues to vary independently of the overall one. All the bonds in the heteropolymer (now consisting of hydrophobic, hydrophilic, and neutral beads) have the same constant length, and all the bond angles are equal and fixed. As a crucial idea of the model, an overall potential around the cluster wherein a residue performs a chaotic motion is considered to be a combination of the average dihedral and average pairwise potentials assigned to the bead. The overall potential as a function of the distance from the cluster center has a double well shape which allows one to determine its emission and absorption rates by using a first passage time analysis. Knowing these rates as functions of three independent variables of a ternary cluster, one can develop a self-consistent kinetic theory for the nucleation mechanism of folding of a protein using a ternary nucleation formalism and evaluate the size and composition of the nucleus and the protein folding time. As an illustration, the model is applied to the folding of bovine pancreatic ribonuclease consisting of 124 amino acids whereof 40 are hydrophobic, 81 hydrophilic, and 3 neutral. With a reasonable choice of diffusion coefficients of the residues in the native state and potential parameters, the model predicts folding times in the range of 1-100 s.

Statistical temperature molecular dynamics: Application to coarse-grained β-barrel-forming protein models

Recently the authors proposed a novel sampling algorithm, "statistical temperature molecular dynamics" (STMD) [J. Kim et al., Phys. Rev. Lett. 97, 050601 (2006)], which combines ingredients of multicanonical molecular dynamics and Wang-Landau sampling. Exploiting the relation between the statistical temperature and the density of states, STMD generates a flat energy distribution and efficient sampling with a dynamic update of the statistical temperature, transforming an initial constant estimate to the true statistical temperature T(U), with U being the potential energy. Here, the performance of STMD is examined in the Lennard-Jones fluid with diverse simulation conditions, and in the coarse-grained, off-lattice BLN 46-mer and 69-mer protein models, exhibiting rugged potential energy landscapes with a high degree of frustration. STMD simulations combined with inherent structure (IS) analysis allow an accurate determination of protein thermodynamics down to very low temperatures, overcoming quasiergodicity, and illuminate the transitions occurring in folding in terms of the energy landscape. It is found that a thermodynamic signature of folding is significantly suppressed by accurate sampling, due to an incoherent contribution from low-lying non-native IS in multifunneled landscapes. It is also shown that preferred accessibility to such IS during the collapse transition is intimately related to misfolding or poor foldability.

Energy barrier scalings in driven systems

Energy landscape mappings are performed for two different molecular systems under mechanical loads. Barrier heights are observed to scale as Delta U approximately delta(3/2), where delta is a residual load. Catastrophe theory predicts that this scaling should arise for vanishing delta; however, this region is irrelevant in physical processes at finite temperature because thermal fluctuations cause the system to cross over the barrier before reaching the small-delta regime. Surprisingly, we find that the Delta U approximately delta(3/2), scaling is valid far beyond the vanishing delta regime described by catastrophe theory. We discuss how this scaling will therefore be relevant at finite temperatures and gives corrections to Eyring's theory for transition rates.

Structural transitions of confined model proteins: molecular dynamics simulation and experimental validation

Proteins fold in a confined space not only in vivo, i.e., folding assisted by molecular chaperons and chaperonins in a crowded cellular medium, but also in vitro as in production of recombinant proteins. Despite extensive work on protein folding in bulk, little is known about how and to what extent the thermodynamics and kinetics of protein folding are altered by confinement. In this work, we use a Gō-like off-lattice model to investigate the folding and stability of an all beta-sheet protein in spherical cages of different sizes and surface hydrophobicity. We find whereas extreme confinement inhibits correct folding, a hydrophilic cage stabilizes the protein due to restriction of the unfolded configurations. In a hydrophobic cage, however, strong attraction from the cage surface destabilizes the confined protein because of competition between self-aggregation and adsorption of hydrophobic residues. We show that the kinetics of protein collapse and folding is strongly correlated with both the cage size and the surface hydrophobicity. It is demonstrated that a cage of moderate size and hydrophobicity optimizes both the folding yield and kinetics of structural transitions. To support the simulation results, we have also investigated the refolding of hen-egg lysozyme in the presence of cetyltrimethylammoniumbromide (CTAB) surfactants that provide an effective confinement of the proteins by micellization. The influence of the surfactant hydrophobicity on the structural and biological activity of the protein is determined with circular dichroism spectrum, fluorescence emission spectrum, and biological activity assay. It is shown that, as predicted by coarse-grained simulations, CTAB micelles facilitate the collapse of denatured lysozyme, whereas the addition of beta-cyclodextrin-grafted-PNIPAAm, a weakly hydrophobic stripper, dissociates CTAB micelles and promotes the conformational rearrangement and thereby gives an improved recovery of lysozyme activity.

Local-structural diversity and protein folding: Application to all-β off-lattice protein models

Global measures of structural diversity within a distribution of biopolymers, such as the radius of gyration and percent native contacts, have proven useful in the analysis of simulation data for protein folding. In this paper we describe a statistical-based methodology to quantify the local structural variability of a distribution of biopolymers, applied to 46- and 69-"residue" off-lattice, three-color model proteins. Each folds into beta-barrel structures. First we perform a principal component analysis of all interbead distance variables for a large number of independent, converged Boltzmann-distributed samples of conformations collected at each of a wide range of temperatures. Next, the principal component vectors are subjected to orthogonal (varimax) rotation. The results are displayed on so-called "squared-loading" plots. These provide a quantitative measure of the contribution to the sample variance of the position of each residue relative to the others. Dominant structural elements, those having the largest structural diversity within the sampled distribution, are responsible for peaks and shoulders observed in the specific heat versus temperature curves, generated using the weighted histogram analysis method. The loading plots indicate that the local-structural diversity of these systems changes gradually with temperature through the folding transition but radically changes near the collapse transition temperature. The analysis of the structural overlap order statistic suggests that the 46-mer thermodynamic folding transition involves the native state and at least three other nearly native intermediates. In the case of the 46-mer protein model, data are generated at sufficiently low temperatures that squared-loading plots, coupled with cluster analysis, provide a local and energetic description of its glassy state.

Topological frustration and the folding of interleukin-1 beta

The cytokine, interleukin-1beta (IL-1beta), adopts a beta-trefoil fold. It is known to be much slower folding than similarly sized proteins, despite having a low contact order. Proteins are sufficiently well designed that their folding is not dominated by local energetic traps. Therefore, protein models that encode only the folded structure and are energetically unfrustrated (Gō-type), can capture the essentials of the folding routes. We investigate the folding thermodynamics of IL-1beta using such a model and molecular dynamics (MD) simulations. We develop an enhanced sampling technique (a modified multicanonical method) to overcome the sampling problem caused by the slow folding. We find that IL-1beta has a broad and high free energy barrier. In addition, the protein fold causes intermediate unfolding and refolding of some native contacts within the protein along the folding trajectory. This "backtracking" occurs around the barrier region. Complex folds like the beta-trefoil fold and functional loops like the beta-bulge of IL-1beta can make some of the configuration space unavailable to the protein and cause topological frustration.

Effects of frustration, confinement, and surface interactions on the dimerization of an off-lattice β-barrel protein

We study the effects of confinement, sequence frustration, and surface interactions on the thermodynamics of dimerization of an off-lattice minimalist beta-barrel protein using replica exchange molecular dynamics. We vary the degree of frustration of the protein by tuning the specificity of the hydrophobic interactions and investigate dimerization in confining spheres of different radii. We also investigate surface effects by tethering the first residue of one of the proteins to a uniformly repulsive surface. We find that increasing the confinement and frustration stabilize the dimer, while adding a repulsive surface decreases its stability. Different ensembles of structures, including properly dimerized and various partially dimerized states, are observed at the association transition temperature T(a), depending on the amount of frustration and whether a surface is present. The presence of a surface is predicted to alter the morphology of larger aggregates formed from partially unfolded dimeric conformations.

Modeling the Interplay between Geometrical and Energetic Effects in Protein Folding

A theoretical framework is constructed with the aid of a free-energy functional method that is capable of describing the interplay between geometrical and energetic effects on protein folding. In this paper, we generalize a free-energy functional model based on polymer theory to make it more appropriate for comparison with protein folding simulations and experiments. This generalization is made by introducing cooperativity into the configurational entropy and the internal energy. Modifications to configurational entropy enable the model to account for the loop-loop interactions, a contribution neglected in the original model. Modifications to the internal energy introduce many-body corrections, which are needed to establish quantitative contact to simulations as well as experimental observations. To demonstrate the efficiency of the modified analytical model, we compare our results with C(alpha) structure-based (Go) model simulations of chymotrypsin inhibitor II and the SH3 domain of src.

The competition between protein folding and aggregation: off-lattice minimalist model studies

Protein aggregation has been associated with a number of human diseases, and is a serious problem in the manufacture of recombinant proteins. Of particular interest to the biotechnology industry is deleterious aggregation that occurs during the refolding of proteins from inclusion bodies. As a complement to experimental efforts, computer simulations of multi-chain systems have emerged as a powerful tool to investigate the competition between folding and aggregation. Here we report results from Langevin dynamics simulations of minimalist model proteins. Order parameters are developed to follow both folding and aggregation. By mapping natural units to real units, the simulations are shown to be carried out under experimentally relevant conditions. Data pertaining to the contacts formed during the association process show that multiple mechanisms for aggregation exist, but certain pathways are statistically preferred. Kinetic data show that there are multiple time scales for aggregation, although most association events take place at times much shorter than those required for folding. Last, we discuss results presented here as a basis for future work aimed at rational design of mutations to reduce aggregation propensity, as well as for development of small-molecular weight refolding enhancers.

Energy landscape distortions and the mechanical unfolding of proteins

Molecular simulations and an energy landscape analysis are used to examine the stretching of a model protein. A mapping of the energy landscape shows that stretching the protein causes energy minima and energy barriers to flatten out and disappear, and new energy minima to be created. The implications of these landscape distortions depend on the timescale regime under which the protein is stretched. When the timescale for thermally activated processes is longer than the timescale of stretching, the disappearances of energy barriers provide the mechanism for protein unfolding. When the timescale for thermally activated processes is shorter than the timescale of stretching, the landscape distortions influence the stretching process by changing the number and types of energy minima in which the system can exist.

Protein folding rates correlate with heterogeneity of folding mechanism

By observing trends in the folding kinetics of experimental 2-state proteins at their transition midpoints, and by observing trends in the barrier heights of numerous simulations of coarse-grained, C(alpha) model Go proteins, we show that folding rates correlate with the degree of heterogeneity in the formation of native contacts. Statistically significant correlations are observed between folding rates and measures of heterogeneity inherent in the native topology, as well as between rates and the variance in the distribution of either experimentally measured or simulated phi values.

Theory of protein folding

Protein folding should be complex. Proteins organize themselves into specific three-dimensional structures, through a myriad of conformational changes. The classical view of protein folding describes this process as a nearly sequential series of discrete intermediates. In contrast, the energy landscape theory of folding considers folding as the progressive organization of an ensemble of partially folded structures through which the protein passes on its way to the natively folded structure. As a result of evolution, proteins have a rugged funnel-like landscape biased toward the native structure. Connecting theory and simulations of minimalist models with experiments has completely revolutionized our understanding of the underlying mechanisms that control protein folding.

Self-assembly of peptides into a β-barrel motif

We report the results of a study of the self-assembly of four minimalist peptide strands with a native beta-barrel structure. Using a soft-well potential to mimic cellular crowding, molecular dynamics simulations were performed in confining spheres of varying radii. By utilizing a previously introduced scaling factor lambda for the non-native hydrophobic interactions (0<lambda<1), we were able to study models with varying degrees of frustration. Both the thermodynamics and kinetics of a Go-like model (lambda=0) and a highly frustrated model (lambda=0.9) were studied. Additionally, we used an extrapolation technique to investigate the thermodynamics of assembly at intermediate values of lambda. As in our earlier work [J. Chem. Phys. 118, 8106 (2003)] on a connected Go-like model beta-barrel protein, we find that the stability of the assembled protein increases with decreasing sphere size, and that larger confining spheres result in increased assembly times. Additionally, the lambda=0 model seems to undergo distinct phase transitions during the assembly process. In contrast, the more frustrated model (lambda=0.9) appears to undergo a glasslike transition at temperatures comparable to the assembly temperature of the Go model, and that this transition is relatively nonspecific. Our results suggest the assembly process is dependent on both sequence and environment, with implications for the formation of misassembled aggregates.

Global minimization of an off-lattice potential energy function using a chaperone-based refolding method

A global energy minimization method based on what is known about the mechanisms of the GroEL/GroES chaperonin system is applied to two 22-mers of an off-lattice protein model whose native states are beta-hairpins and which have structural similarity to short peptides known to interact strongly with the GroEL substrate binding domain. These model substrates have been used by other workers to test the effectiveness of a number of global minimization techniques, and are regarded as providing a significant challenge. The minimization method developed here is progressively elaborated from an initial simple form that targets exposed hydrophobic regions for unfolding to include a refolding phase that encourages the later recompactification of partly unfolded substrate; this refolding phase is seen to be crucial in the successful application of the method. The optimal handling of hydrophilic monomers within the model is also systematically explored, and it is seen that the best interpretation of their role is one that allows the chaperonin model to operate in "proofreading" mode whereby misfolded substrates are recognized by their surface exposure of a large proportion of hydrophobic monomers. The final version of the model allows native-like structures to be found quickly, on average for the two 22-mer substrates after 6 or 7 chaperone contacts. These results compare very favorably with those that have been obtained elsewhere using generic global minimization methods such as those based on thermal annealing. The paper concludes with a discussion of the place of the technique within the general category of hypersurface deformation methods for global minimization, and with suggestions as to how the chaperone-based method developed here could be elaborated so as to be effective on longer substrate chains that give rise to more complex tertiary structures in their native states.