Cooperativity in two-state protein folding kinetics

Can 2,2,2-trifluoroethanol be an efficient protein denaturant than methanol and ethanol under thermal stress?

We report the heterogeneous unfolding phenomenon of a small protein Chymotrypsin Inhibitor 2 in various concentrations of methanol, ethanol and TFE solutions by performing atomistic molecular dynamics simulation studies. Our study reveals that the unfolding phenomenon of CI2 under thermal stress majorly depends on the concentration and the nature of the alcohol.

Long-Lived Intermediates in a Cooperative Two-State Folding Transition

Biomolecular folding often occurs through a cooperative two-state reactant ↔ product transition; the term cooperative does not convey that intermediate structures are nonexistent but rather that these states are not observable by existing experimental techniques. Because of this, few intermediates have been studied and characterized. Recently, ion mobility spectrometry (IMS) measurements revealed that the oligomer polyproline-13 (Pro13, which in propanol (PrOH) favors the right-handed helical PPI structure having adjacent pyrrolidine rings in a cis configuration) folds through six sequential long-lived intermediates as it converts to the all-trans-configured PPII structure that is favored in aqueous solutions. Here, we examine the PPI_PrOH → PPII_aq folding transition for a HisPro13 sequence, i.e., Pro13 having a single histidine residue added to the N-terminus. Remarkably, the IMS measurements show that, upon addition of histidine, all of the IMS peaks associated with intermediate structures disappear. Instead, HisPro13 folds via a cooperative two-state transition, delayed by a significant induction period. The induction period is temperature dependent-shifting the transition to longer times at lower temperatures. Equilibrium studies show that the HisPro13 PPI_PrOH → PPII_aq transition is endothermic but favored entropically. From these clues, we propose a sequential folding mechanism and develop a model that suggests that ∼13-17 long-lived intermediates are likely responsible for the induction period. In this model, intermediates are separated by average individual activation barriers of ∼90 kJ·mol^-1, and are entropically favorable.

Inferring Microscopic Kinetic Rates from Stationary State Distributions

We present a principled approach for estimating the matrix of microscopic transition probabilities among states of a Markov process, given only its stationary state population distribution and a single average global kinetic observable. We adapt Maximum Caliber, a variational principle in which the path entropy is maximized over the distribution of all possible trajectories, subject to basic kinetic constraints and some average dynamical observables. We illustrate the method by computing the solvation dynamics of water molecules from molecular dynamics trajectories.

Molecular crowders and cosolutes promote folding cooperativity of RNA under physiological ionic conditions

Folding mechanisms of functional RNAs under idealized in vitro conditions of dilute solution and high ionic strength have been well studied. Comparatively little is known, however, about mechanisms for folding of RNA in vivo where Mg(2+) ion concentrations are low, K(+) concentrations are modest, and concentrations of macromolecular crowders and low-molecular-weight cosolutes are high. Herein, we apply a combination of biophysical and structure mapping techniques to tRNA to elucidate thermodynamic and functional principles that govern RNA folding under in vivo-like conditions. We show by thermal denaturation and SHAPE studies that tRNA folding cooperativity increases in physiologically low concentrations of Mg(2+) (0.5-2 mM) and K(+) (140 mM) if the solution is supplemented with physiological amounts (∼ 20%) of a water-soluble neutral macromolecular crowding agent such as PEG or dextran. Low-molecular-weight cosolutes show varying effects on tRNA folding cooperativity, increasing or decreasing it based on the identity of the cosolute. For those additives that increase folding cooperativity, the gain is manifested in sharpened two-state-like folding transitions for full-length tRNA over its secondary structural elements. Temperature-dependent SHAPE experiments in the absence and presence of crowders and cosolutes reveal extent of cooperative folding of tRNA on a nucleotide basis and are consistent with the melting studies. Mechanistically, crowding agents appear to promote cooperativity by stabilizing tertiary structure, while those low molecular cosolutes that promote cooperativity stabilize tertiary structure and/or destabilize secondary structure. Cooperative folding of functional RNA under physiological-like conditions parallels the behavior of many proteins and has implications for cellular RNA folding kinetics and evolution.

Computational and theoretical methods for protein folding

A computational approach is essential whenever the complexity of the process under study is such that direct theoretical or experimental approaches are not viable. This is the case for protein folding, for which a significant amount of data are being collected. This paper reports on the essential role of in silico methods and the unprecedented interplay of computational and theoretical approaches, which is a defining point of the interdisciplinary investigations of the protein folding process. Besides giving an overview of the available computational methods and tools, we argue that computation plays not merely an ancillary role but has a more constructive function in that computational work may precede theory and experiments. More precisely, computation can provide the primary conceptual clues to inspire subsequent theoretical and experimental work even in a case where no preexisting evidence or theoretical frameworks are available. This is cogently manifested in the application of machine learning methods to come to grips with the folding dynamics. These close relationships suggested complementing the review of computational methods within the appropriate theoretical context to provide a self-contained outlook of the basic concepts that have converged into a unified description of folding and have grown in a synergic relationship with their computational counterpart. Finally, the advantages and limitations of current computational methodologies are discussed to show how the smart analysis of large amounts of data and the development of more effective algorithms can improve our understanding of protein folding.

Energy landscape and dynamics of proteins: an exact analysis of a simplified lattice model

We present the results of exact numerical studies of the energy landscape and the dynamics of a 12-monomer chain with contact interactions encoding the ground state on a square lattice. In spite of its simplicity, the model is shown to exhibit behavior at odds with the standard picture of proteins.

How long does it take to equilibrate the unfolded state of a protein?

How long does it take to equilibrate the unfolded state of a protein? The answer to this question has important implications for our understanding of why many small proteins fold with two state kinetics. When the equilibration within the unfolded state U is much faster than the folding, the folding kinetics will be two state even if there are many folding pathways with different barriers. Yet the mean first passage times (MFPTs) between different regions of the unfolded state can be much longer than the folding time. This seems to imply that the equilibration within U is much slower than the folding. In this communication we resolve this paradox. We present a formula for estimating the time to equilibrate the unfolded state of a protein. We also present a formula for the MFPT to any state within U, which is proportional to the average lifetime of that state divided by the state population. This relation is valid when the equilibration within U is very fast as compared with folding as it often is for small proteins. To illustrate the concepts, we apply the formulas to estimate the time to equilibrate the unfolded state of Trp-cage and MFPTs within the unfolded state based on a Markov State Model using an ultra-long 208 microsecond trajectory of the miniprotein to parameterize the model. The time to equilibrate the unfolded state of Trp-cage is ∼100 ns while the typical MFPTs within U are tens of microseconds or longer.

Exact partition function zeros of the Wako-Saitô-Muñoz-Eaton β hairpin model

I compute exact partition function zeros of β hairpins, using both analytic and numerical methods, extending previous work [J. Lee, Phys. Rev. Lett. 110, 248101 (2013)] where only a restricted class of hairpins was considered. The zeros of β hairpins with an odd number of peptide bonds are computed and the difference of the distribution of zeros from those for an even number of peptide bonds is explained in terms of additional entropy of liberating the extra bond at the turn region. Upon the introduction of a hydrophobic core in the central region of the hairpin, the zeros are distributed uniformly on two concentric circles corresponding to the hydrophobic collapse and the transition to the fully folded conformation. One of the circles dissolves as the core moves toward the turn or the tip region, which is explained in terms of the similarity of the intermediate state with the folded or unfolded states. The exact partition function zeros for a hairpin with a more complex structure of native contacts, the 16 C-terminal residues of streptococcal protein G B1, are numerically computed and their loci are closely approximated by concentric circles.

Exact partition function zeros of the Wako-Saitô-Muñoz-Eaton protein model

I compute exact partition function zeros of the Wako-Saitô-Muñoz-Eaton model for various secondary structural elements and for two proteins, 1BBL and 1I6C, by using both analytic and numerical methods. Two-state and barrierless downhill folding transitions can be distinguished by a gap in the distribution of zeros at the positive real axis.

Structural effects of linkage disequilibrium on the transcriptome

A majority of SNPs (single nucleotide polymorphisms) map to noncoding and intergenic regions of the genome. Noncoding SNPs are often identified in genome-wide association studies (GWAS) as strongly associated with human disease. Two such disease-associated SNPs in the 5' UTR of the human FTL (Ferritin Light Chain) gene are predicted to alter the ensemble of structures adopted by the mRNA. High-accuracy single nucleotide resolution chemical mapping reveals that these SNPs result in substantial changes in the structural ensemble in agreement with the computational prediction. Furthermore six rescue mutations are correctly predicted to restore the mRNA to its wild-type ensemble. Our data confirm that the FTL 5' UTR is a "RiboSNitch," an RNA that changes structure if a particular disease-associated SNP is present. The structural change observed is analogous to that of a bacterial Riboswitch in that it likely regulates translation. These data further suggest that specific pairs of SNPs in high linkage disequilibrium (LD) will form RNA structure-stabilizing haplotypes (SSHs). We identified 484 SNP pairs that form SSHs in UTRs of the human genome, and in eight of the 10 SSH-containing transcripts, SNP pairs stabilize RNA protein binding sites. The ubiquitous nature of SSHs in the transcriptome suggests that certain haplotypes are conserved to avoid RiboSNitch formation.

Toward a digital gene response: RNA G-quadruplexes with fewer quartets fold with higher cooperativity

Changes in RNA conformation can alter gene expression. The guanine quadruplex sequence (GQS) is an RNA motif that folds in the presence of K(+) ions. Changes in the conformation of this motif could be especially important in regulating gene expression in plants because intracellular K(+) concentrations often increase during drought stress. Little is known about the folding thermodynamics of RNA GQS. We show here that RNA GQS with tracts containing three G's [e.g., (GGGxx)(4)] have a modest dependence on the K(+) concentration, folding with no or even negative cooperativity (Hill coefficients ≤1), and are associated with populated folding intermediates. In contrast, GQS with tracts containing just two G's [e.g., (GGxx)(4)] have a steep dependence on the K(+) concentration and fold with positive cooperativity (Hill coefficients of 1.7-2.7) without significantly populating intermediate states. We postulate that in plants, the more stable G3 sequences are largely folded even under unstressed conditions, while the less stable G2 sequences fold only at the higher K(+) concentrations associated with cellular stress, wherein they respond sharply to changing K(+) concentrations. Given the binary nature of their folding, G2 sequences may find application in computation with DNA and in engineering of genetic circuits.

Structured pathway across the transition state for peptide folding revealed by molecular dynamics simulations

Small globular proteins and peptides commonly exhibit two-state folding kinetics in which the rate limiting step of folding is the surmounting of a single free energy barrier at the transition state (TS) separating the folded and the unfolded states. An intriguing question is whether the polypeptide chain reaches, and leaves, the TS by completely random fluctuations, or whether there is a directed, stepwise process. Here, the folding TS of a 15-residue β-hairpin peptide, Peptide 1, is characterized using independent 2.5 μs-long unbiased atomistic molecular dynamics (MD) simulations (a total of 15 μs). The trajectories were started from fully unfolded structures. Multiple (spontaneous) folding events to the NMR-derived conformation are observed, allowing both structural and dynamical characterization of the folding TS. A common loop-like topology is observed in all the TS structures with native end-to-end and turn contacts, while the central segments of the strands are not in contact. Non-native sidechain contacts are present in the TS between the only tryptophan (W11) and the turn region (P7-G9). Prior to the TS the turn is found to be already locked by the W11 sidechain, while the ends are apart. Once the ends have also come into contact, the TS is reached. Finally, along the reactive folding paths the cooperative loss of the W11 non-native contacts and the formation of the central inter-strand native contacts lead to the peptide rapidly proceeding from the TS to the native state. The present results indicate a directed stepwise process to folding the peptide.

The folding dynamics of many small protein/peptides investigated recently are in terms of simple two-state model in which only two populations exist (folded and unfolded), separated by a single free energy barrier with only one kinetically important transition state (TS). However, dynamical characterization of the folding TS is challenging. We have used independent unbiased atomistic molecular dynamics simulations with clear folding-unfolding transitions to characterize structural and dynamical features of transition state ensemble of Peptide 1. A common loop-like topology is observed in all TS structures extracted from multiple simulations. The trajectories were used to examine the mechanism by which the TS is reached and subsequent events in folding pathways. The folding TS is reached and crossed in a directed stagewise process rather than through random fluctuations. Specific structures are formed before, during, and after the transition state, indicating a clear structured folding pathway.

Are Peptides Good Two-State Folders?

The folding kinetics of proteins is frequently single-exponential, as basins of folded and unfolded conformations are well separated by a high barrier. However, for relatively short peptides, a two-state character of folding is rather the exception than the rule. In this work, we use a Zwanzig-type model of protein conformational dynamics to study the dependence of folding kinetics on the protein chain length, M. The analysis is focused on the gap in the eigenvalue spectrum of the rate matrix that describes the protein's conformational dynamics. When there is a large gap between the two smallest in magnitude nonzero eigenvalues, the corresponding relaxation times have qualitatively different physical interpretations. The longest of these two times characterizes the interbasin equilibration (i.e., folding), whereas the second time characterizes the intrabasin relaxation. We derive approximate analytical solutions for the two eigenvalues that show how they depend on M. From these solutions, we infer that there is a large gap between the two, and thus, the kinetics is essentially single-exponential when M is large enough such that 2(M+1) is much larger than M(2).

Cooperativity, local-nonlocal coupling, and nonnative interactions: principles of protein folding from coarse-grained models

Coarse-grained, self-contained polymer models are powerful tools in the study of protein folding. They are also essential to assess predictions from less rigorous theoretical approaches that lack an explicit-chain representation. Here we review advances in coarse-grained modeling of cooperative protein folding, noting in particular that the Levinthal paradox was raised in response to the experimental discovery of two-state-like folding in the late 1960s, rather than to the problem of conformational search per se. Comparisons between theory and experiment indicate a prominent role of desolvation barriers in cooperative folding, which likely emerges generally from a coupling between local conformational preferences and nonlocal packing interactions. Many of these principles have been elucidated by native-centric models, wherein nonnative interactions may be treated perturbatively. We discuss these developments as well as recent applications of coarse-grained chain modeling to knotted proteins and to intrinsically disordered proteins.

Nonadditivity in conformational entropy upon molecular rigidification reveals a universal mechanism affecting folding cooperativity

Previously, we employed a Maxwell counting distance constraint model (McDCM) to describe α-helix formation in polypeptides. Unlike classical helix-coil transition theories, the folding mechanism derives from nonadditivity in conformational entropy caused by rigidification of molecular structure as intramolecular cross-linking interactions form along the backbone. For example, when a hydrogen bond forms within a flexible region, both energy and conformational entropy decrease. However, no conformational entropy is lost when the region is already rigid because atomic motions are not constrained further. Unlike classical zipper models, the same mechanism also describes a coil-to-β-hairpin transition. Special topological features of the helix and hairpin structures allow the McDCM to be solved exactly. Taking full advantage of the fact that Maxwell constraint counting is a mean field approximation applied to the distribution of cross-linking interactions, we present an exact transfer matrix method that does not require any special topological feature. Upon application of the model to proteins, cooperativity within the folding transition is yet again appropriately described. Notwithstanding other contributing factors such as the hydrophobic effect, this simple model identifies a universal mechanism for cooperativity within polypeptide and protein-folding transitions, and it elucidates scaling laws describing hydrogen-bond patterns observed in secondary structure. In particular, the native state should have roughly twice as many constraints as there are degrees of freedom in the coil state to ensure high fidelity in two-state folding cooperativity, which is empirically observed.

Turbulent phenomena in protein folding

Protein folding and hydrodynamic turbulence are two long-standing challenges, in molecular biophysics and fluid dynamics, respectively. The theories of these phenomena have been developed independently and used different formalisms. Here we show that the protein folding flows can be surprisingly similar to turbulent fluid flows. Studying a benchmark model protein (an SH3 domain), we have found that the flows for the slow folding trajectories of the protein, in which a partly formed N- and C-terminal β sheet hinders the RT loop from attaching to the protein core, have many properties of turbulent flows of a fluid. The flows are analyzed in a three-dimensional (3D) space of collective variables, which are the numbers of native contacts between the terminal β strands, between the RT loop and the protein core, and the rest of the native contacts. We have found that the flows have fractal nature and are filled with 3D eddies; the latter contain strange attractors, at which the tracer flow paths behave as saddle trajectories. Two regions of the space increment have been observed, in which the flux variations are self-similar with the scaling exponent h=1/3, in surprising agreement with the Kolmogorov inertial range theory of turbulence. In one region, the cascade of protein rearrangements is directed from larger to smaller scales (net folding), and in the other, it is oppositely directed (net unfolding). Folding flows for the fast trajectories are essentially "laminar" and do not have the property of self-similarity. Based on the results of our study, we infer, and support this inference by simulations, that the origin of the similarity between the protein folding and turbulent motion of a fluid is in a cascade mechanism of structural transformations in the systems that underlies these phenomena.

Full reconstruction of a vectorial protein folding pathway by atomic force microscopy and molecular dynamics simulations

During co-translational folding, the nascent polypeptide chain is extruded sequentially from the ribosome exit tunnel and is [corrected] under severe conformational constraints [corrected] dictated by the one-dimensional geometry of the tunnel. [corrected] How do such vectorial constraints impact the folding pathway? Here, we combine single-molecule atomic force spectroscopy and steered molecular dynamics simulations to examine protein folding in the presence of one-dimensional constraints that are similar to those imposed on the nascent polypeptide chain. The simulations exquisitely reproduced the experimental unfolding and refolding force extension relationships and led to the full reconstruction of the vectorial folding pathway of a large polypeptide, the 253-residue consensus ankyrin repeat protein, NI6C. We show that fully stretched and then relaxed NI6C starts folding by the formation of local secondary structures, followed by the nucleation of three N-terminal repeats. This rate-limiting step is then followed by the vectorial and sequential folding of the remaining repeats. However, after partial unfolding, when allowed to refold, the C-terminal repeats successively regain structures without any nucleation step by using the intact N-terminal repeats as a template. These results suggest a pathway for the co-translational folding of repeat proteins and have implications for mechanotransduction.

Rate theories for biologists

Some of the rate theories that are most useful for modeling biological processes are reviewed. By delving into some of the details and subtleties in the development of the theories, the review will hopefully help the reader gain a more than superficial perspective. Examples are presented to illustrate how rate theories can be used to generate insight at the microscopic level into biomolecular behaviors. An attempt is made to clear up a number of misconceptions in the literature regarding popular rate theories, including the appearance of Planck's constant in the transition-state theory and the Smoluchowski result as an upper limit for protein-protein and protein-DNA association rate constants. Future work in combining the implementation of rate theories through computer simulations with experimental probes of rate processes, and in modeling effects of intracellular environments so that theories can be used for generating rate constants for systems biology studies is particularly exciting.

Slow formation of aggregation-resistant beta-sheet folding intermediates

Protein folding has been studied extensively for decades, yet our ability to predict how proteins reach their native state from a mechanistic perspective is still rudimentary at best, limiting our understanding of folding-related processes in vivo and our ability to manipulate proteins in vitro. Here, we investigate the in vitro refolding mechanism of a large beta-helix protein, pertactin, which has an extended, elongated shape. At 55 kDa, this single domain, all-beta-sheet protein allows detailed analysis of the formation of beta-sheet structure in larger proteins. Using a combination of fluorescence and far-UV circular dichroism spectroscopy, we show that the pertactin beta-helix refolds remarkably slowly, with multiexponential kinetics. Surprisingly, despite the slow refolding rates, large size, and beta-sheet-rich topology, pertactin refolding is reversible and not complicated by off-pathway aggregation. The slow pertactin refolding rate is not limited by proline isomerization, and 30% of secondary structure formation occurs within the rate-limiting step. Furthermore, site-specific labeling experiments indicate that the beta-helix refolds in a multistep but concerted process involving the entire protein, rather than via initial formation of the stable core substructure observed in equilibrium titrations. Hence pertactin provides a valuable system for studying the refolding properties of larger, beta-sheet-rich proteins, and raises intriguing questions regarding the prevention of aggregation during the prolonged population of partially folded, beta-sheet-rich refolding intermediates. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

What have we learned from the studies of two-state folders, and what are the unanswered questions about two-state protein folding?

Small proteins with globular structures often fold by simple all-or-none mechanisms, both in an equilibrium and a kinetic sense, despite the very large number of partly folded conformations available. This type of 'two-state' folding will be discussed in terms of experimental tests, underlying molecular mechanisms, and limits to two-state behavior. Factors that appear to be important for two-state folding include topology (sequence distance of contacts in the native structure), molecular cooperativity and local energy distribution. Because their local stability distributions and cooperativities can be dissected and analyzed separately from topological features, recent studies of the folding of symmetric proteins will be discussed as a means to better understand the origins of two-state folding.

A two-state cell damage model under hyperthermic conditions: theory and in vitro experiments

The ultimate goal of cancer treatment utilizing thermotherapy is to eradicate tumors and minimize damage to surrounding host tissues. To achieve this goal, it is important to develop an accurate cell damage model to characterize the population of cell death under various thermal conditions. The traditional Arrhenius model is often used to characterize the damaged cell population under the assumption that the rate of cell damage is proportional to exp(-EaRT), where Ea is the activation energy, R is the universal gas constant, and T is the absolute temperature. However, this model is unable to capture transition phenomena over the entire hyperthermia and ablation temperature range, particularly during the initial stage of heating. Inspired by classical statistical thermodynamic principles, we propose a general two-state model to characterize the entire cell population with two distinct and measurable subpopulations of cells, in which each cell is in one of the two microstates, viable (live) and damaged (dead), respectively. The resulting cell viability can be expressed as C(tau,T)=exp(-Phi(tau,T)kT)(1+exp(-Phi(tau,T)kT)), where k is a constant. The in vitro cell viability experiments revealed that the function Phi(tau,T) can be defined as a function that is linear in exposure time tau when the temperature T is fixed, and linear as well in terms of the reciprocal of temperature T when the variable tau is held as constant. To determine parameters in the function Phi(tau,T), we use in vitro cell viability data from the experiments conducted with human prostate cancerous (PC3) and normal (RWPE-1) cells exposed to thermotherapeutic protocols to correlate with the proposed cell damage model. Very good agreement between experimental data and the derived damage model is obtained. In addition, the new two-state model has the advantage that is less sensitive and more robust due to its well behaved model parameters.

Lattice model of equilibrium polymerization. VII. Understanding the role of "cooperativity" in self-assembly

Cooperativity is an emergent many-body phenomenon related to the degree to which elementary entities (particles, molecules, organisms) collectively interact to form larger scale structures. From the standpoint of a formal mean field description of chemical reactions, the cooperativity index m, describing the number of elements involved in this structural self-organization, is the order of the reaction. Thus, m for molecular self-assembly is the number of molecules in the final organized structure, e.g., spherical micelles. Although cooperativity is crucial for regulating the thermodynamics and dynamics of self-assembly, there is a limited understanding of this aspect of self-assembly. We analyze the cooperativity by calculating essential thermodynamic properties of the classical mth order reaction model of self-assembly (FAm model), including universal scaling functions describing the temperature and concentration dependence of the order parameter and average cluster size. The competition between self-assembly and phase separation is also described. We demonstrate that a sequential model of thermally activated equilibrium polymerization can quantitatively be related to the FAm model. Our analysis indicates that the essential requirement for "cooperative" self-assembly is the introduction of constraints (often nonlocal) acting on the individual assembly events to regulate the thermodynamic free energy landscape and, thus, the thermodynamic sharpness of the assembly transition. An effective value of m is defined for general self-assembly transitions, and we find a general tendency for self-assembly to become a true phase transition as m-->infinity. Finally, various quantitative measures of self-assembly cooperativity are discussed in order to identify experimental signatures of cooperativity in self-assembling systems and to provide a reliable metric for the degree of transition cooperativity.

A minimum-reaction-flux solution to master-equation models of protein folding

Master equations are widely used for modeling protein folding. Here an approximate solution to such master equations is presented. The approach used may be viewed as a discrete variational transition-state theory. The folding rate constant kf is approximated by the outgoing reaction flux J, when the unfolded set of macrostates assumes an equilibrium distribution. Correspondingly the unfolding rate constant ku is calculated as Jpu(1-pu), where pu is the equilibrium fraction of the unfolded state. The dividing surface between the unfolded and folded states is chosen to minimize the reaction flux J. This minimum-reaction-flux surface plays the role of the transition-state ensemble and identifies rate-limiting steps. Test against exact results of master-equation models of Zwanzig [Proc. Natl. Acad. Sci. USA 92, 9801 (1995)] and Munoz et al. [Proc. Natl. Acad. Sci. USA 95, 5872 (1998)] shows that the minimum-reaction-flux solution works well. Macrostates separated by the minimum-reaction-flux surface show a gap in p(fold) values. The approach presented here significantly simplifies the solution of master-equation models and, at the same time, directly yields insight into folding mechanisms.

Predicting protein folding rates from geometric contact and amino acid sequence

Protein folding speeds are known to vary over more than eight orders of magnitude. Plaxco, Simons, and Baker (see References) first showed a correlation of folding speed with the topology of the native protein. That and subsequent studies showed, if the native structure of a protein is known, its folding speed can be predicted reasonably well through a correlation with the "localness" of the contacts in the protein. In the present work, we develop a related measure, the geometric contact number, N (alpha), which is the number of nonlocal contacts that are well-packed, by a Voronoi criterion. We find, first, that in 80 proteins, the largest such database of proteins yet studied, N (alpha) is a consistently excellent predictor of folding speeds of both two-state fast folders and more complex multistate folders. Second, we show that folding rates can also be predicted from amino acid sequences directly, without the need to know the native topology or other structural properties.

The protein folding problem

The "protein folding problem" consists of three closely related puzzles: (a) What is the folding code? (b) What is the folding mechanism? (c) Can we predict the native structure of a protein from its amino acid sequence? Once regarded as a grand challenge, protein folding has seen great progress in recent years. Now, foldable proteins and nonbiological polymers are being designed routinely and moving toward successful applications. The structures of small proteins are now often well predicted by computer methods. And, there is now a testable explanation for how a protein can fold so quickly: A protein solves its large global optimization problem as a series of smaller local optimization problems, growing and assembling the native structure from peptide fragments, local structures first.

Loop-closure principles in protein folding

Simple theoretical concepts and models have been helpful to understand the folding rates and routes of single-domain proteins. As reviewed in this article, a physical principle that appears to underly these models is loop closure.

Transition states in protein folding kinetics: modeling phi-values of small beta-sheet proteins

Small single-domain proteins often exhibit only a single free-energy barrier, or transition state, between the denatured and the native state. The folding kinetics of these proteins is usually explored via mutational analysis. A central question is which structural information on the transition state can be derived from the mutational data. In this article, we model and structurally interpret mutational Phi-values for two small beta-sheet proteins, the PIN and the FBP WW domains. The native structure of these WW domains comprises two beta-hairpins that form a three-stranded beta-sheet. In our model, we assume that the transition state consists of two conformations in which either one of the hairpins is formed. Such a transition state has been recently observed in molecular dynamics folding-unfolding simulations of a small designed three-stranded beta-sheet protein. We obtain good agreement with the experimental data 1), by splitting up the mutation-induced free-energy changes into terms for the two hairpins and for the small hydrophobic core of the proteins; and 2), by fitting a single parameter, the relative degree to which hairpins 1 and 2 are formed in the transition state. The model helps us to understand how mutations affect the folding kinetics of WW domains, and captures also negative Phi-values that have been difficult to interpret.

Parallel folding pathways in the SH3 domain protein

The transition-state ensemble (TSE) is the set of protein conformations with an equal probability to fold or unfold. Its characterization is crucial for an understanding of the folding process. We determined the TSE of the src-SH3 domain protein by using extensive molecular dynamics simulations of the Go model and computing the folding probability of a generated set of TSE candidate conformations. We found that the TSE possesses a well-defined hydrophobic core with variable enveloping structures resulting from the superposition of three parallel folding pathways. The most preferred pathway agrees with the experimentally determined TSE, while the two least preferred pathways differ significantly. The knowledge of the different pathways allows us to design the interactions between amino acids that guide the protein to fold through the least preferred pathway. This particular design is akin to a circular permutation of the protein. The finding motivates the hypothesis that the different experimentally observed TSEs in homologous proteins and circular permutants may represent potentially available pathways to the wild-type protein.

Protein folding in confined and crowded environments

Confinement and crowding are two major factors that can potentially impact protein folding in cellular environments. Theories based on considerations of excluded volumes predict disparate effects on protein folding stability for confinement and crowding: confinement can stabilize proteins by over 10k(B)T but crowding has a very modest effect on stability. On the other hand, confinement and crowding are both predicted to favor conformations of the unfolded state which are compact, and consequently may increase the folding rate. These predictions are largely borne out by experimental studies of protein folding under confined and crowded conditions in the test tube. Protein folding in cellular environments is further complicated by interactions with surrounding surfaces and other factors. Concerted theoretical modeling and test-tube and in vivo experiments promise to elucidate the complexity of protein folding in cellular environments.

Kinetics analysis methods for approximate folding landscapes

MOTIVATION

Protein motions play an essential role in many biochemical processes. Lab studies often quantify these motions in terms of their kinetics such as the speed at which a protein folds or the population of certain interesting states like the native state. Kinetic metrics give quantifiable measurements of the folding process that can be compared across a group of proteins such as a wild-type protein and its mutants.

RESULTS

We present two new techniques, map-based master equation solution and map-based Monte Carlo simulation, to study protein kinetics through folding rates and population kinetics from approximate folding landscapes, models called maps. From these two new techniques, interesting metrics that describe the folding process, such as reaction coordinates, can also be studied. In this article we focus on two metrics, formation of helices and structure formation around tryptophan residues. These two metrics are often studied in the lab through circular dichroism (CD) spectra analysis and tryptophan fluorescence experiments, respectively. The approximated landscape models we use here are the maps of protein conformations and their associated transitions that we have presented and validated previously. In contrast to other methods such as the traditional master equation and Monte Carlo simulation, our techniques are both fast and can easily be computed for full-length detailed protein models. We validate our map-based kinetics techniques by comparing folding rates to known experimental results. We also look in depth at the population kinetics, helix formation and structure near tryptophan residues for a variety of proteins.

AVAILABILITY

We invite the community to help us enrich our publicly available database of motions and kinetics analysis by submitting to our server: http://parasol.tamu.edu/foldingserver/.

Using Stochastic Roadmap Simulation to Predict Experimental Quantities in Protein Folding Kinetics: Folding Rates and Phi-Values

This paper presents a new method for studying protein folding kinetics. It uses the recently introduced Stochastic Roadmap Simulation (SRS) method to estimate the transition state ensemble (TSE) and predict the rates and the Phi-values for protein folding. The new method was tested on 16 proteins, whose rates and Phi-values have been determined experimentally. Comparison with experimental data shows that our method estimates the TSE much more accurately than an existing method based on dynamic programming. This improvement leads to better folding-rate predictions. We also compute the mean first passage time of the unfolded states and show that the computed values correlate with experimentally determined folding rates. The results on Phi-value predictions are mixed, possibly due to the simple energy model used in the tests. This is the first time that results obtained from SRS have been compared against a substantial amount of experimental data. The results further validate the SRS method and indicate its potential as a general tool for studying protein folding kinetics.

Identification of characteristic protein folding channels in a coarse-grained hydrophobic-polar peptide model

Folding channels and free-energy landscapes of hydrophobic-polar heteropolymers are discussed on the basis of a minimalistic off-lattice coarse-grained model. We investigate how rearrangements of hydrophobic and polar monomers in a heteropolymer sequence lead to completely different folding behaviors. Studying three exemplified sequences with the same content of hydrophobic and polar residues, we can reproduce within this simple model two-state folding, folding through intermediates, as well as metastability.

Routes are trees: the parsing perspective on protein folding

An important puzzle in structural biology is the question of how proteins are able to fold so quickly into their unique native structures. There is much evidence that protein folding is hierarchic. In that case, folding routes are not linear, but have a tree structure. Trees are commonly used to represent the grammatical structure of natural language sentences, and chart parsing algorithms efficiently search the space of all possible trees for a given input string. Here we show that one such method, the CKY algorithm, can be useful both for providing novel insight into the physical protein folding process, and for computational protein structure prediction. As proof of concept, we apply this algorithm to the HP lattice model of proteins. Our algorithm identifies all direct folding route trees to the native state and allows us to construct a simple model of the folding process. Despite its simplicity, our model provides an account for the fact that folding rates depend only on the topology of the native state but not on sequence composition.

Denaturation of jack-bean urease by sodium n-dodecyl sulphate: A kinetic study below the critical micelle concentration

Kinetics of urease denaturation by anionic surfactant (sodium n-dodecyl sulphate, SDS) at concentrations below the critical micelle concentration (CMC) is investigated spectrophotometrically at neutral pH and the corresponding two-phase kinetic parameters of the process are estimated from a three-state reversible process using a binomial exponential relation based on the relaxation time method as: Using a prepared computer program, the experimental data are properly fitted into a binomial exponential relation, considering a two-phase denaturation pathway including a kinetically stable folded intermediate formed at SDS concentration of 1.1 mM. Forward and backward rate constants are estimated as: k(1)=0.2141+/-4.5 x 10(-3), k(2)=5.173 x 10(-3)+/-8.3 x 10(-5), k(-1)=0.09432+/-3.6 x 10(-4) and k(-2)=2.079 x 10(-3)+/-5.6 x 10(-5)s(-1) for the proposed mechanism. The rate-limiting step as well as the reaction coordinates in the denaturation mechanism are established. The mechanism involves formation of a kinetically stable folded native like intermediate through the electrostatic interactions. The intermediate was found to be more stable even than the native form (by about 9 kJmol(-1)) and still hexamer, because no loss of amplitude was observed. Electrophoresis experiments on the native and surfactant/urease complexes indicated a higher mobility for the kinetically folded native like intermediate.

A kinetic theory of tertiary contact formation coupled to the helix-coil transition in polypeptides

The framework model and the hydrophobic collapse model represent two canonical descriptions of the protein folding process. The first places primary reliance on the short-range interactions of secondary structure and the second assigns greater importance to the long-range interactions of tertiary structure. The availability of increasingly detailed information about the folding mechanisms of diverse proteins suggests that both are important and the folding mechanism of most proteins utilizes different combinations of such interactions. A prior report described the XHC model, an extended helix-coil theory, which treats the mutual stabilization of secondary and tertiary structure in simple alpha-helical proteins at equilibrium. In this study, a kinetic scheme describing tertiary contact formation has been developed which relaxes to the XHC equilibrium model. The relaxation is governed by the relative stabilities of the equilibrium states and an additional factor which represents an activation energy for formation of a tertiary contact. The model can be used to simulate time-dependent properties of the ensemble of conformations during the entire folding process, and the resulting predictions are applicable to a range of experimental methods. This XHC kinetic model enables investigation of the relative influence of secondary and tertiary interactions on folding mechanisms.

Diffusion-collision of foldons elucidates the kinetic effects of point mutations and suggests control strategies of the folding process of helical proteins

In this article we use mutation studies as a benchmark for a minimal model of the folding process of helical proteins. The model ascribes a pivotal role to the collisional dynamics of a few crucial residues (foldons) and predicts the folding rates by exploiting information drawn from the protein sequence. We show that our model rationalizes the effects of point mutations on the kinetics of folding. The folding times of two proteins and their mutants are predicted. Stability and location of foldons have a critical role as the determinants of protein folding. This allows us to elucidate two main mechanisms for the kinetic effects of mutations. First, it turns out that the mutations eliciting the most notable effects alter protein stability through stabilization or destabilization of the foldons. Secondly, the folding rate is affected via a modification of the foldon topology by those mutations that lead to the birth or death of foldons. The few mispredicted folding rates of some mutants hint at the limits of the current version of the folding model proposed in the present article. The performance of our folding model declines in case the mutated residues are subject to strong long-range forces. That foldons are the critical targets of mutation studies has notable implications for design strategies and is of particular interest to address the issue of the kinetic regulation of single proteins in the general context of the overall dynamics of the interactome.

Relationships between the folding rate constant and the topological parameters of small two-state proteins based on general random walk model

In this paper, we propose an analytically tractable model of protein folding based on one-dimensional general random walk. A second-order differential equation for the mean folding time of a single protein is constructed which can be used to derive the observed relationship between the folding rate constant and the number of native contacts. The parameters appearing in the model can be determined by fitting the theoretical prediction to the experimental result. In addition, taking into account the fact that the number of native contacts is almost proportional to the relative contact order, we can also explain the observed relationship between the folding rate constant and the relative contact order.

Do proteins with similar folds have similar transition state structures? A diffuse transition state of the 169 residue apoflavodoxin

Apoflavodoxin from Anabaena PCC 7119 is a 169 residue globular protein of known structure and energetics. Here, we present a comprehensive Phi-value analysis to characterize the structure of its transition state. A total of 34 non-disruptive mutations are made throughout the structure and a range of Phi-values from zero to one are observed. In addition, a small set of eight aliphatic small-to-large mutations have been introduced in the hydrophobic core of the protein and they have been analyzed to investigate the feasibility of stabilizing the unfolding transition state by creating new non-native interactions. We find that the transition state of apoflavodoxin (so far the largest protein subjected to Phi-analysis) is diffuse and that it can be stabilized by unspecific hydrophobic interactions that can speed up the folding reaction. The data gathered on the apoflavodoxin transition state are compared with results from experimental studies in other proteins to revisit the relationship between the native state topology and transition state structure.

Loop-closure events during protein folding: rationalizing the shape of Phi-value distributions

In the past years, the folding kinetics of many small single-domain proteins has been characterized by mutational Phi-value analysis. In this article, a simple, essentially parameter-free model is introduced which derives folding routes from native structures by minimizing the entropic loop-closure cost during folding. The model predicts characteristic folding sequences of structural elements such as helices and beta-strand pairings. Based on few simple rules, the kinetic impact of these structural elements is estimated from the routes and compared to average experimental Phi-values for the helices and strands of 15 small, well-characterized proteins. The comparison leads on average to a correlation coefficient of 0.62 for all proteins with polarized Phi-value distributions, and 0.74 if distributions with negative average Phi-values are excluded. The diffuse Phi-value distributions of the remaining proteins are reproduced correctly. The model shows that Phi-value distributions, averaged over secondary structural elements, can often be traced back to entropic loop-closure events, but also indicates energetic preferences in the case of a few proteins governed by parallel folding processes.

How do biomolecular systems speed up and regulate rates?

The viability of a biological system depends upon careful regulation of the rates of various processes. These rates have limits imposed by intrinsic chemical or physical steps (e.g., diffusion). These limits can be expanded by interactions and dynamics of the biomolecules. For example, (a) a chemical reaction is catalyzed when its transition state is preferentially bound to an enzyme; (b) the folding of a protein molecule is speeded up by specific interactions within the transition-state ensemble and may be assisted by molecular chaperones; (c) the rate of specific binding of a protein molecule to a cellular target can be enhanced by mechanisms such as long-range electrostatic interactions, nonspecific binding and folding upon binding; (d) directional movement of motor proteins is generated by capturing favorable Brownian motion through intermolecular binding energy; and (e) conduction and selectivity of ions through membrane channels are controlled by interactions and the dynamics of channel proteins. Simple physical models are presented here to illustrate these processes and provide a unifying framework for understanding speed attainment and regulation in biomolecular systems.

Phi values in protein-folding kinetics have energetic and structural components

Phi values are experimental measures of how the kinetics of protein folding is changed by single-site mutations. Phi values measure energetic quantities, but they are often interpreted in terms of the structures of the transition-state ensemble. Here, we describe a simple analytical model of the folding kinetics in terms of the formation of protein substructures. The model shows that Phi values have both structural and energetic components. It also provides a natural and general interpretation of "nonclassical" Phi values (i.e., < 0 or > 1). The model reproduces the Phi values for 20 single-residue mutations in the alpha-helix of the protein CI2, including several nonclassical Phi values, in good agreement with experiments.

The role of sequence and structure in protein folding kinetics; the diffusion-collision model applied to proteins L and G

The diffusion-collision model (DCM) is applied to the folding kinetics of protein L and protein G. In the DCM, the two proteins are treated as consisting of two beta-hairpins and one alpha-helix, so that they are isomorphous with the three-helix bundle DCM model. In the absence of sequence dependent factors, both proteins would fold in the same way in the DCM, with the coalescence of the N-terminal hairpin and the helix slightly favored over the C-terminal hairpin and the helix because the former are closer together than the latter. However, sequence dependent factors make the N-terminal hairpin of protein L and the C-terminal hairpin of protein G more stable in the ensemble of unfolded conformations. This difference in the stabilities gives rise to the difference in the calculated folding behavior, in agreement with experiment.