Synergy between simulation and experiment in describing the energy landscape of protein folding

Targeting the protein folding transition state by mutation: Large scale (un)folding rate accelerations without altering native stability

Proteins are constantly undergoing folding and unfolding transitions, with rates that determine their homeostasis in vivo and modulate their biological function. The ability to optimize these rates without affecting overall native stability is hence highly desirable for protein engineering and design. The great challenge is, however, that mutations generally affect folding and unfolding rates with inversely complementary fractions of the net free energy change they inflict on the native state. Here we address this challenge by targeting the folding transition state (FTS) of chymotrypsin inhibitor 2 (CI2), a very slow and stable two-state folding protein with an FTS known to be refractory to change by mutation. We first discovered that the CI2's FTS is energetically taxed by the desolvation of several, highly conserved, charges that form a buried salt bridge network in the native structure. Based on these findings, we designed a CI2 variant that bears just four mutations and aims to selectively stabilize the FTS. This variant has >250-fold faster rates in both directions and hence identical native stability, demonstrating the success of our FTS-centric design strategy. With an optimized FTS, CI2 also becomes 250-fold more sensitive to proteolytic degradation by its natural substrate chymotrypsin, and completely loses its activity as inhibitor. These results indicate that CI2 has been selected through evolution to have a very unstable FTS in order to attain the kinetic stability needed to effectively function as protease inhibitor. Moreover, the CI2 case showcases that protein (un)folding rates can critically pivot around a few key residues-interactions, which can strongly modify the general effects of known structural factors such as domain size and fold topology. From a practical standpoint, our results suggest that future efforts should perhaps focus on identifying such critical residues-interactions in proteins as best strategy to significantly improve our ability to predict and engineer protein (un)folding rates.

From covalent transition states in chemistry to noncovalent in biology: from β- to Φ-value analysis of protein folding

Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted's landmark paper that introduced the β-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding - 'part (b) of the protein folding problem'. This review describes the development of Φ-value analysis of transition states and compares and contrasts the interpretation of β- and Φ-values and their limitations. Φ-analysis afforded the first description of transition states in protein folding at the level of individual residues. It revealed the nucleation-condensation folding mechanism of protein domains with the transition state as an expanded, distorted native structure, containing little fully formed secondary structure but many weak tertiary interactions. A spectrum of transition states with various degrees of structural polarisation was then uncovered that spanned from nucleation-condensation to the framework mechanism of fully formed secondary structure. Φ-analysis revealed how movement of the expanded transition state on an energy landscape accommodates the transition from framework to nucleation-condensation mechanisms with a malleability of structure as a unifying feature of folding mechanisms. Such movement follows the rubric of analysis of classical covalent chemical mechanisms that began with Brønsted. Φ-values are used to benchmark computer simulation, and Φ and simulation combine to describe folding pathways at atomic resolution.

High Energy Channeling and Malleable Transition States: Molecular Dynamics Simulations and Free Energy Landscapes for the Thermal Unfolding of Protein U1A and 13 Mutants

The spliceosome protein U1A is a prototype case of the RNA recognition motif (RRM) ubiquitous in biological systems. The in vitro kinetics of the chemical denaturation of U1A indicate that the unfolding of U1A is a two-state process but takes place via high energy channeling and a malleable transition state, an interesting variation of typical two-state behavior. Molecular dynamics (MD) simulations have been applied extensively to the study of two-state unfolding and folding of proteins and provide an opportunity to obtain a theoretical account of the experimental results and a molecular model for the transition state ensemble. We describe herein all-atom MD studies including explicit solvent of up to 100 ns on the thermal unfolding (UF) of U1A and 13 mutants. Multiple MD UF trajectories are carried out to ensure accuracy and reproducibility. A vector representation of the MD unfolding process in RMSD space is obtained and used to calculate a free energy landscape for U1A unfolding. A corresponding MD simulation and free energy landscape for the protein CI2, well known to follow a simple two state folding/unfolding model, is provided as a control. The results indicate that the unfolding pathway on the MD calculated free energy landscape of U1A shows a markedly extended transition state compared with that of CI2. The MD results support the interpretation of the observed chevron plots for U1A in terms of a high energy, channel-like transition state. Analysis of the MDUF structures shows that the transition state ensemble involves microstates with most of the RRM secondary structure intact but expanded by ~14% with respect to the radius of gyration. Comparison with results on a prototype system indicates that the transition state involves an ensemble of molten globule structures and extends over the region of ~1-35 ns in the trajectories. Additional MDUF simulations were carried out for 13 U1A mutants, and the calculated φ-values show close accord with observed results and serve to validate our methodology.

Double Mutant of Chymotrypsin Inhibitor 2 Stabilized through Increased Conformational Entropy

The conformational heterogeneity of a folded protein can affect not only its function but also stability and folding. We recently discovered and characterized a stabilized double mutant (L49I/I57V) of the protein CI2 and showed that state-of-the-art prediction methods could not predict the increased stability relative to the wild-type protein. Here, we have examined whether changed native-state dynamics, and resulting entropy changes, can explain the stability changes in the double mutant protein, as well as the two single mutant forms. We have combined NMR relaxation measurements of the ps-ns dynamics of amide groups in the backbone and the methyl groups in the side chains with molecular dynamics simulations to quantify the native-state dynamics. The NMR experiments reveal that the mutations have different effects on the conformational flexibility of CI2: a reduction in conformational dynamics (and entropy estimated from this) of the native state of the L49I variant correlates with its decreased stability, while increased dynamics of the I57V and L49I/I57V variants correlates with their increased stability. These findings suggest that explicitly accounting for changes in native-state entropy might be needed to improve the predictions of the effect of mutations on protein stability.

Rational Design of Chymotrypsin Inhibitor 2 by Optimizing Non-Native Interactions

Rational design of proteins via mutagenesis is crucial for several biotechnological applications. A significant challenge of the computational strategies used to predict optimized mutations is to understand the influence of each amino acid during the folding process. In the present work, chymotrypsin inhibitor 2 (CI2) and several of its designed mutants have been simulated using a non-native hydrophobic and electrostatic potential as a structure-based Cα model. Through these simulations, we could identify the most critical folding stage to accelerate CI2 and also the charged residues responsible for providing its thermostability. The replacement of ionizable residues for hydrophobic ones tended to promote the formation of the CI2 secondary structure in the early transition state, which speeds up folding. However, this same replacement destabilized the native structure, and there was a decrease in the protein thermostability. Such a simple method proved to be capable of providing valuable information about thermodynamics and kinetics of CI2 and its mutations, thus being a fast alternative to the study of rational protein design.

A component analysis of the free energies of folding of 35 proteins: A consensus view on the thermodynamics of folding at the molecular level

What factors favor protein folding? This is a textbook question. Parsing the experimental free energies of folding/unfolding into diverse enthalpic and entropic components of solute and solvent favoring or disfavoring folding is not an easy task. In this study, we present a computational protocol for estimating the free energy contributors to protein folding semi-quantitatively using ensembles of unfolded and native states generated via molecular dynamics simulations. We tested the methodology on 35 proteins with diverse structural motifs and sizes and found that the calculated free energies correlate well with experiment (correlation coefficient ∼ 0.85), enabling us to develop a consensus view of the energetics of folding. As a more sensitive test of the methodology, we also investigated the free energies of folding of an additional 33 single point mutants and obtained a correlation coefficient of 0.8. A notable observation is that the folding free energy components appear to carry signatures of the fold (SCOP classification) of the protein. © 2017 Wiley Periodicals, Inc.

Interplay between Protein Thermal Flexibility and Kinetic Stability

Kinetic stability is a key parameter to comprehend protein behavior and it plays a central role to understand how evolution has reached the balance between function and stability in cell-relevant timescales. Using an approach that includes simulations, protein engineering, and calorimetry, we show that there is a clear correlation between kinetic stability determined by differential scanning calorimetry and protein thermal flexibility obtained from a novel method based on temperature-induced unfolding molecular dynamics simulations. Thermal flexibility quantitatively measures the increment of the conformational space available to the protein when energy in provided. The (β/α)₈ barrel fold of two closely related by evolution triosephosphate isomerases from two trypanosomes are used as model systems. The kinetic stability-thermal flexibility correlation has predictive power for the studied proteins, suggesting that the strategy and methodology discussed here might be applied to other proteins in biotechnological developments, evolutionary studies, and the design of protein based therapeutics.

Insights from molecular dynamics simulations for computational protein design

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.

Statistical Mechanical Model for pH-Induced Protein Folding: Application to Apomyoglobin

Despite the major role of pH in protein folding and stability, a quantitative understanding of the pH-induced protein folding mechanism remains elusive. Two conventional models, the Monod-Wyman-Changeux and Linderstrøm-Lang smeared charge models, respectively, have been used to analyze the formation/disruption of specific native structures and fluctuating non-native states. However, there are only a few models that can represent the overall kinetic events of folding/unfolding independent of the properties of relevant molecular species, which has hampered the efforts to systematically analyze pH-induced folding. Here, we constructed a statistical mechanical model that incorporates the protonation mechanism of conventional models along with a combined manual search and least-squares fitting procedure, which was used to investigate the folding of horse apomyoglobin over a wide pH range (2.2-6.7), with a time window ranging from ∼40 μs to ∼100 s, using continuous-/stopped-flow fluorescence at 8 °C. Quantitative analysis assuming a five-state sequential scheme indicated that (1) pH-induced folding/unfolding is represented by both specific binding and Coulombic interactions; (2) kinetic folding/unfolding intermediates share kinetic mechanisms with the equilibrium intermediate, indicating their equivalence; and (3) native-like properties are acquired successively during folding by intermediates and in transition states. This model could also be applied to a variety of association/dissociation processes.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

Using the folding landscapes of proteins to understand protein function

Proteins fold on a biologically-relevant timescale because of a funnel-shaped energy landscape. This landscape is sculpted through evolution by selecting amino-acid sequences that stabilize native interactions while suppressing stable non-native interactions that occur during folding. However, there is strong evolutionary selection for functional residues and these cannot be chosen to optimize folding. Their presence impacts the folding energy landscape in a variety of ways. Here, we survey the effects of functional residues on folding by providing several examples. We then review how such effects can be detected computationally and be used as assays for protein function. Overall, an understanding of how functional residues modulate folding should provide insights into the design of natural proteins and their homeostasis.

The folding of a family of three-helix bundle proteins: spectrin R15 has a robust folding nucleus, unlike its homologous neighbours

Three homologous spectrin domains have remarkably different folding characteristics. We have previously shown that the slow-folding R16 and R17 spectrin domains can be altered to resemble the fast folding R15, in terms of speed of folding (and unfolding), landscape roughness and folding mechanism, simply by substituting five residues in the core. Here we show that, by contrast, R15 cannot be engineered to resemble R16 and R17. It is possible to engineer a slow-folding version of R15, but our analysis shows that this protein neither has a rougher energy landscape nor does change its folding mechanism. Quite remarkably, R15 appears to be a rare example of a protein with a folding nucleus that does not change in position or in size when its folding nucleus is disrupted. Thus, while two members of this protein family are remarkably plastic, the third has apparently a restricted folding landscape.

Probing the protein-folding mechanism using denaturant and temperature effects on rate constants

Protein folding has been extensively studied, but many questions remain regarding the mechanism. Characterizing early unstable intermediates and the high-free-energy transition state (TS) will help answer some of these. Here, we use effects of denaturants (urea, guanidinium chloride) and temperature on folding and unfolding rate constants and the overall equilibrium constant as probes of surface area changes in protein folding. We interpret denaturant kinetic m-values and activation heat capacity changes for 13 proteins to determine amounts of hydrocarbon and amide surface buried in folding to and from TS, and for complete folding. Predicted accessible surface area changes for complete folding agree in most cases with structurally determined values. We find that TS is advanced (50-90% of overall surface burial) and that the surface buried is disproportionately amide, demonstrating extensive formation of secondary structure in early intermediates. Models of possible pre-TS intermediates with all elements of the native secondary structure, created for several of these proteins, bury less amide and hydrocarbon surface than predicted for TS. Therefore, we propose that TS generally has both the native secondary structure and sufficient organization of other regions of the backbone to nucleate subsequent (post-TS) formation of tertiary interactions. The approach developed here provides proof of concept for the use of denaturants and other solutes as probes of amount and composition of the surface buried in coupled folding and other large conformational changes in TS and intermediates in protein processes.

Biomolecular simulation: a computational microscope for molecular biology

Molecular dynamics simulations capture the behavior of biological macromolecules in full atomic detail, but their computational demands, combined with the challenge of appropriately modeling the relevant physics, have historically restricted their length and accuracy. Dramatic recent improvements in achievable simulation speed and the underlying physical models have enabled atomic-level simulations on timescales as long as milliseconds that capture key biochemical processes such as protein folding, drug binding, membrane transport, and the conformational changes critical to protein function. Such simulation may serve as a computational microscope, revealing biomolecular mechanisms at spatial and temporal scales that are difficult to observe experimentally. We describe the rapidly evolving state of the art for atomic-level biomolecular simulation, illustrate the types of biological discoveries that can now be made through simulation, and discuss challenges motivating continued innovation in this field.

Microsecond folding experiments and simulations: a match is made

For the past two decades, protein folding experiments have been speeding up from the second or millisecond time scale to the microsecond time scale, and full-atom simulations have been extended from the nanosecond to the microsecond and even millisecond time scale. Where the two meet, it is now possible to compare results directly, allowing force fields to be validated and refined, and allowing experimental data to be interpreted in atomistic detail. In this perspective we compare recent experiments and simulations on the microsecond time scale, pointing out the progress that has been made in determining native structures from physics-based simulations, refining experiments and simulations to provide more quantitative underlying mechanisms, and tackling the problems of multiple reaction coordinates, downhill folding, and complex underlying structure of unfolded or misfolded states.

A comparison of experimental and computational methods for mapping the interactions present in the transition state for folding of FKBP12

The folding pathway of FKBP12, a 107 residue α/β protein, has been characterised in detail using a combination of experimental and computational techniques. FKBP12 follows a two-state model of folding in which only the denatured and native states are significantly populated; no intermediate states are detected. The refolding rate constant in water is 4 s(-1) at 25 °C. Two different experimental strategies were employed for studying the transition state for folding. In the first case, a non-mutagenic approach was used and the unfolding and refolding of the wild-type protein measured as a function of experimental conditions such as temperature, denaturant, ligand and trifluoroethanol (TFE) concentration. These data suggest a compact transition state relative to the unfolded state with some 70% of the surface area buried. The ligand-binding site, whichis mainly formed by two long loops, is largely unstructured in the transition state. TFE experiments suggest that the α-helix may be formed in the transition state. The second experimental approach involved using protein engineering techniques with φ-value analysis. Residue-specific information on the structure and energetics of the transition state can be obtained by this method. 34 mutations were made at sites throughout the protein to probe the extent of secondary and tertiary structure in the transition state. In contrast to some other proteins of this size, no element of structure is fully formed in the transition state, instead, the transition state is similar to that found for smaller, single-domain proteins, such as chymotrypsin inhibitor 2 and the SH3 domainfrom α-spectrin. For FKBP12, the central three strands of the β-sheet (2, 4 and 5), comprise the most structured region of the transition state. In particular Val 101, which is one of the most highly buried residues and located in the middle of the central β-strand,makes approximately 60% of its native interactions. The outer β-strands, and the ends of the central β-strands are formed to a lesser degree. The short α-helix is largely unstructured in the transition state as are the loops. The data are consistent with a nucleation-condensation model of folding, the nucleus of which is formed by side chains within β-strands 2, 4 and 5 and the C-terminus of the α-helix. These residues are distant in the primary sequence, demonstrating the importance of tertiary interactions in the transition state. High-temperature molecular dynamic simulations on the unfoldingpathway of FKBP12 are in good agreement with the experimental results.

Separating the effects of internal friction and transition state energy to explain the slow, frustrated folding of spectrin domains

The elongated three-helix bundle domains spectrin R16 and R17 fold some two to three orders of magnitude more slowly than their homologue R15. We have shown that this slow folding is due, at least in part, to roughness in the free-energy landscape of R16 and R17. We have proposed that this roughness is due to a frustrated search for the correct docking of partly preformed helices. However, this accounts for only a small part of the slowing of folding and unfolding. Five residues on the A helix of R15, when inserted together into R16 or R17, increase the folding rate constants, reduce landscape roughness, and alter the folding mechanism to one resembling R15. The effect of each of these mutations individually is investigated here. No one mutation causes the behavior seen for the five in combination. However, two mutations, E18F and K25V, significantly increase the folding and unfolding rates of both R16 and R17 but without a concomitant loss in landscape roughness. E18F has the greatest effect on the kinetics, and a Φ-value analysis of the C helix reveals that the folding mechanism is unchanged. For both E18F and K25V the removal of the charge and resultant transition state stabilization is the main origin of the faster folding. Consequently, the major cause of the unusually slow folding of R16 and R17 is the non-native burial of the two charged residues in the transition state. The slowing due to landscape roughness is only about fivefold.

Protein folds and protein folding

The classification of protein folds is necessarily based on the structural elements that distinguish domains. Classification of protein domains consists of two problems: the partition of structures into domains and the classification of domains into sets of similar structures (or folds). Although similar topologies may arise by convergent evolution, the similarity of their respective folding pathways is unknown. The discovery and the characterization of the majority of protein folds will be followed by a similar enumeration of available protein folding pathways. Consequently, understanding the intricacies of structural domains is necessary to understanding their collective folding pathways. We review the current state of the art in the field of protein domain classification and discuss methods for the systematic and comprehensive study of protein folding across protein fold space via atomistic molecular dynamics simulation. Finally, we discuss our large-scale Dynameomics project, which includes simulations of representatives of all autonomous protein folds.

Dynameomics: protein dynamics and unfolding across fold space

All currently known structures of proteins together define ‘protein fold space’. To increase the general understanding of protein dynamics and protein folding, we selected a set of 807 proteins and protein domains that represent 95% of the currently known autonomous folded domains present in globular proteins. Native state and unfolding simulations of these representatives are now complete and accessible via a novel database containing over 11 000 simulations. Because protein folding is a microscopically reversible process, these simulations effectively sample protein folding across all of protein fold space. Here, we give an overview of how the representative proteins were selected and how the simulations were performed and validated. We then provide examples of different types of analyses that can be performed across our large set of simulations, made possible by the database approach. We further show how the unfolding simulations can be used to compare unfolding of structural elements in isolation and in different structural contexts, using as an example a short, triple stranded β-sheet that forms the WW domain and is present in several larger unrelated proteins.

Investigation of an anomalously accelerating substitution in the folding of a prototypical two-state protein

The folding rates of two-state single-domain proteins are generally resistant to small-scale changes in amino acid sequence. For example, having surveyed here over 700 single-residue substitutions in 24 well-characterized two-state proteins, we find that the majority (55%) of these substitutions affect folding rates by less than a factor of 2, and that only 9% affect folding rates by more than a factor of 8. Among those substitutions that significantly affect folding rates, we find that accelerating substitutions are an order of magnitude less common than those that decelerate the process. One of the most extreme outliers in this data set, an arginine-to-phenylalanine substitution at position 48 (R48F) of chymotrypsin inhibitor 2 (CI2), accelerates the protein's folding rate by a factor of 36 relative to that of the wild-type protein and is the most accelerating substitution reported to date in a two-state protein. In order to better understand the origins of this anomalous behavior, we have characterized the kinetics of multiple additional substitutions at this position. We find that substitutions at position 48 in CI2 fall into two distinct classes. The first, comprising residues that ablate the charge of the wild-type arginine but retain the hydrophobicity of its alkane chain, accelerate folding by at least 10-fold. The second class, comprising all other residues, produces folding rates within a factor of two of the wild-type rate. A significant positive correlation between hydrophobicity and folding rate across all of the residues we have characterized at this position suggests that the hydrophobic methylene units of the wild-type arginine play a significant role in stabilizing the folding transition state. Likewise, studies of the pH dependence of the histidine substitution indicate a strong correlation between folding rate and charge state. Thus, mutations that ablate the arginine's positive charge while retaining the hydrophobic contacts of its methylene units tend to dramatically accelerate folding. Previous studies have suggested that arginine 48 plays an important functional role in CI2, which may explain why it is highly conserved despite the anomalously large deceleration it produces in the folding of this protein.

Dynameomics: a comprehensive database of protein dynamics

The dynamic behavior of proteins is important for an understanding of their function and folding. We have performed molecular dynamics simulations of the native state and unfolding pathways of over 2000 protein/peptide systems (approximately 11,000 independent simulations) representing the majority of folds in globular proteins. These data are stored and organized using an innovative database approach, which can be mined to obtain both general and specific information about the dynamics and folding/unfolding of proteins, relevant subsets thereof, and individual proteins. Here we describe the project in general terms and the type of information contained in the database. Then we provide examples of mining the database for information relevant to protein folding, structure building, the effect of single-nucleotide polymorphisms, and drug design. The native state simulation data and corresponding analyses for the 100 most populated metafolds, together with related resources, are publicly accessible through http://www.dynameomics.org.

Unfolding simulations reveal the mechanism of extreme unfolding cooperativity in the kinetically stable alpha-lytic protease

Kinetically stable proteins, those whose stability is derived from their slow unfolding kinetics and not thermodynamics, are examples of evolution's best attempts at suppressing unfolding. Especially in highly proteolytic environments, both partially and fully unfolded proteins face potential inactivation through degradation and/or aggregation, hence, slowing unfolding can greatly extend a protein's functional lifetime. The prokaryotic serine protease α-lytic protease (αLP) has done just that, as its unfolding is both very slow (t_1/2 ∼1 year) and so cooperative that partial unfolding is negligible, providing a functional advantage over its thermodynamically stable homologs, such as trypsin. Previous studies have identified regions of the domain interface as critical to αLP unfolding, though a complete description of the unfolding pathway is missing. In order to identify the αLP unfolding pathway and the mechanism for its extreme cooperativity, we performed high temperature molecular dynamics unfolding simulations of both αLP and trypsin. The simulated αLP unfolding pathway produces a robust transition state ensemble consistent with prior biochemical experiments and clearly shows that unfolding proceeds through a preferential disruption of the domain interface. Through a novel method of calculating unfolding cooperativity, we show that αLP unfolds extremely cooperatively while trypsin unfolds gradually. Finally, by examining the behavior of both domain interfaces, we propose a model for the differential unfolding cooperativity of αLP and trypsin involving three key regions that differ between the kinetically stable and thermodynamically stable classes of serine proteases.

Proteins, synthesized as linear polymers of amino acids, fold up into compact native states, burying their hydrophobic amino acids into their interiors. Protein folding minimizes the non-specific interactions that unfolded protein chains can make, which include aggregation with other proteins and degradation by proteases. Unfortunately, even in the native state, proteins can partially unfold, opening up regions of their structure and making these adverse events possible. Some proteins, particularly those in harsh environments full of proteases, have evolved to virtually eliminate partial unfolding, significantly reducing their rate of degradation. This elimination of partial unfolding is termed “cooperative,” because unfolding is an all-or-none process. One class of proteins has diverged into two families, one bacterial and highly cooperative and the other animal and non-cooperative. We have used detailed simulations of unfolding for members of each family, α-lytic protease (bacterial) and trypsin (animal) to understand the unfolding pathways of each and the mechanism for the differential unfolding cooperativity. Our results explain prior biochemical experiments, reproduce the large difference in unfolding cooperativity between the families, and point to the interface between α-lytic protease's two domains as essential to establishing unfolding cooperativity. As seen in an unrelated protein family, generation of a cooperative domain interface may be a common evolutionary response for ensuring the highest protein stability.

Dynameomics: a consensus view of the protein unfolding/folding transition state ensemble across a diverse set of protein folds

The Dynameomics project aims to simulate a representative sample of all globular protein metafolds under both native and unfolding conditions. We have identified protein unfolding transition state (TS) ensembles from multiple molecular dynamics simulations of high-temperature unfolding in 183 structurally distinct proteins. These data can be used to study individual proteins and individual protein metafolds and to mine for TS structural features common across all proteins. Separating the TS structures into four different fold classes (all proteins, all-alpha, all-beta, and mixed alpha/beta and alpha +beta) resulted in no significant difference in the overall protein properties. The residues with the most contacts in the native state lost the most contacts in the TS ensemble. On average, residues beginning in an alpha-helix maintained more structure in the TS ensemble than did residues starting in beta-strands or any other conformation. The metafolds studied here represent 67% of all known protein structures, and this is, to our knowledge, the largest, most comprehensive study of the protein folding/unfolding TS ensemble to date. One might have expected broad distributions in the average global properties of the TS relative to the native state, indicating variability in the amount of structure present in the TS. Instead, the average global properties converged with low standard deviations across metafolds, suggesting that there are general rules governing the structure and properties of the TS.

Molecular dynamics simulation of phosphorylated KID post-translational modification

Background

Kinase-inducible domain (KID) as transcriptional activator can stimulate target gene expression in signal transduction by associating with KID interacting domain (KIX). NMR spectra suggest that apo-KID is an unstructured protein. After post-translational modification by phosphorylation, KID undergoes a transition from disordered to well folded protein upon binding to KIX. However, the mechanism of folding coupled to binding is poorly understood.

Methodology

To get an insight into the mechanism, we have performed ten trajectories of explicit-solvent molecular dynamics (MD) for both bound and apo phosphorylated KID (pKID). Ten MD simulations are sufficient to capture the average properties in the protein folding and unfolding.

Conclusions

Room-temperature MD simulations suggest that pKID becomes more rigid and stable upon the KIX-binding. Kinetic analysis of high-temperature MD simulations shows that bound pKID and apo-pKID unfold via a three-state and a two-state process, respectively. Both kinetics and free energy landscape analyses indicate that bound pKID folds in the order of KIX access, initiation of pKID tertiary folding, folding of helix α_B, folding of helix α_A, completion of pKID tertiary folding, and finalization of pKID-KIX binding. Our data show that the folding pathways of apo-pKID are different from the bound state: the foldings of helices α_A and α_B are swapped. Here we also show that Asn139, Asp140 and Leu141 with large Φ-values are key residues in the folding of bound pKID. Our results are in good agreement with NMR experimental observations and provide significant insight into the general mechanisms of binding induced protein folding and other conformational adjustment in post-translational modification.

All-atom computer simulations of amyloid fibrils disaggregation

Amyloidlike fibrils are found in many fatal diseases, including Alzheimer's disease, type II diabetes mellitus, transmissible spongiform encephalopathies, and prion diseases. These diseases are linked to proteins that have partially unfolded, misfolded, and aggregated into amyloidlike fibrils. The kinetics of amyloidlike fibrils aggregation is still hotly debated and remains an important open question. We have utilized the GNNQQNY crystal structure and high-temperature molecular dynamics simulation in explicit solvent to study the disaggregation mechanism of the GNNQQNY fibrils and to infer its likely aggregation pathways. A hexamer model and a 12-mer model both with two parallel beta-sheets separated by a dry side-chain interface were adopted in our computational analysis. A cumulative time of 1 micros was simulated for the hexamer model at five different temperatures (298 K, 348 K, 398 K, 448 K, and 498 K), and a cumulative time of 2.1 micros was simulated for the 12-mer model at four temperatures (298 K, 398 K, 448 K, and 498 K). Our disaggregation landscape and kinetics analyses indicate that tetramers probably act as the transition state in both the hexamer and the 12-mer simulations. In addition, the 12-mer simulations show that the initial aggregation nucleus is with eight peptides. Furthermore, the landscape is rather flat from 8-mers to 12-mers, indicating the absence of major barriers once the initial aggregation nucleus forms. Thus, the likely aggregation pathway is from monomers to the initial nucleus of 8-mers with tetramers as the transition state. Transition state structure analysis shows that the two dominant transition state conformations are tetramers in the 3-1 and 2-2 arrangements. The predominant nucleus conformations are in peptide arrangements maximizing dry side-chain contacts. Landscape and kinetics analyses also indicate that the parallel beta-sheets form earlier than the dry side-chain contacts during aggregation. These results provide further insights in understanding the early fibrils aggregation.

Conformational behavior of polypeptides derived through simultaneous global conservative site-directed mutagenesis of chymotrypsin inhibitor 2

The natural occurrence of conservative residue substitutions in proteins suggests that side-chain packing schemes in protein interiors can accommodate mutational replacements of residues by others of similar nature. To explore the extent to which such substitutions are tolerated, especially when introduced simultaneously and globally over the entire length of a polypeptide chain, we examined the conformational behavior of a model 65 residues-long protein, wild-type chymotrypsin inhibitor 2 (WTCI2), and two globally-mutated (GM) variants named GMCI2-1 and GMCI2-2, each incorporating 55 conservative residue substitutions. GMCI2-1, was soluble over a wide range of pH, and folded into a compact, spherical, monomer marked by (i) complete absence of surface hydrophobicity, (ii) a WTCI2-like betaII-type CD spectrum, (iii) high WTCI2-like thermal stability, and (d) 1D and 2D NMR spectra characteristic of folded protein structure. GMCI2-2 was insoluble over a wide range of pH, and could be solubilized only at pH 4.0, showing non-WTCI2-like far-UV CD spectra characterized by high helical content. These results tentatively indicate that polypeptides incorporating residues of identical nature at equivalent chain locations can show the potential to fold with similar characteristics. However, further detailed investigations would be required to determine whether indeed the structural fold of GMCI2-1 resembles that of WTCI2, and to evaluate the extent to which it does so.

A one-dimensional reaction coordinate for identification of transition states from explicit solvent P(fold)-like calculations

A properly identified transition state ensemble (TSE) in a molecular dynamics (MD) simulation can reveal a tremendous amount about how a protein folds and offer a point of comparison to experimentally derived Phi(F) values, which reflect the degree of structure in these transient states. In one such method of TSE identification, dubbed P(fold), MD simulations of individual protein structures taken from an unfolding trajectory are used to directly assess an input structure's probability of folding before unfolding, and P(fold) is, by definition, 0.5 for the TSE. Other, less computationally intensive methods, such as multidimensional scaling (MDS) of the pairwise root mean-squared deviation (RMSD) matrix of the conformations sampled in a thermal unfolding trajectory, have also been used to identify the TSE. Identification of the TSE is made from the original MD simulation without the need to run further simulations. Here we present a P(fold)-like study and describe methods for identification of the TSE through the derivation of a high fidelity, bounded, one-dimensional reaction coordinate for protein folding. These methods are applied to the engrailed homeodomain. The TSE identified by this approach is essentially identical to the TSE identified previously by MDS of the pairwise RMSD matrix. However, the cost of performing P(fold), or even our reduced P(fold)-like calculations, is at least 36,000 times greater than the MDS method.

Binding induced folding in p53-MDM2 complex

The MDM2 N-terminal domain can bind to the transactivation domain of p53 and downregulate its ability to activate transcription. It was found that binding with p53 stabilizes the MDM2 N-terminal domain. Thus the coupling between binding and folding is essential in the normal functional interactions between p53 and MDM2. We have performed explicit-solvent molecular dynamics simulations (MD) for both bound MDM2(N) and apo-MDM2 to study the interdependence of binding and folding in the p53-MDM2 complex. Kinetic analysis of high-temperature MD simulations shows that both bound MDM2(N) and apo-MDM2 unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound MDM2 unfolds in the order of p53 unbinding, tertiary unfolding, and finally secondary structure unfolding. Our data show that the unfolding pathways are different between bound MDM2(N) and apo-MDM2: the unfolding order of unstable helices and tertiary contacts is reversed. Transition state analysis shows that the transition state of bound MDM2 is more nativelike and more heterogeneous than that of apo-MDM2. The predicted Phi-values suggest that the stable helices are more nativelike than other regions in both bound MDM2(N) and apo-MDM2. Within the stable helices, helix II in bound MDM2 is more nativelike than that in apo-MDM2. However, helix I and IV in bound MDM2 are less nativelike than those in apo-MDM2.

Mutations in alpha-helical solvent-exposed sites of eglin c have long-range effects: evidence from molecular dynamics simulations

Eglin c is a small protease inhibitor whose structural and thermodynamic properties have been well studied. Previous thermodynamic measurements on mutants at solvent-accessible positions in the protein's helix have shown the unexpected result that the data could be best fit by the inclusion of residue- and position-specific parameters to the model. To explore the origins of this surprising result, long molecular dynamics simulations in explicit solvent have been performed. These simulations indicate specific long-range interactions between the solvent-exposed residues in the eglin c alpha-helix and binding loop, an unexpected observation for such a small protein. The residues involved in the interaction are on opposite sides of the protein, about 25 A apart. Simulations of alanine substitutions at the solvent-exposed helix positions, arginine 22, glutamic acid 23, threonine 26, and leucine 27, show both small and large perturbations of eglin c dynamics. Two mutations exhibit large impacts on the long-range helix-loop interactions. Previous stability measurements (Yi et al., Biochemistry 2003;42:7594-7603) had indicated that an alanine substitution at position 27 was less stabilizing than at other solvent-exposed positions in the helix. The L27A mutation effects observed in these simulations suggest that the position-dependent loss of stability measured in wet bench experiments is derived from changes in dynamics that involve long-range interactions; thus, these simulations support the hypothesis that solvent-exposed positions in helices are not always equivalent.

Direct observation of microscopic reversibility in single-molecule protein folding

Both folded and unfolded conformations should be observed for a protein at its melting temperature (T(m)), where DeltaG between these states is zero. In an all-atom molecular dynamics simulation of chymotrypsin inhibitor 2 (CI2) at its experimental T(m), the protein rapidly loses its low-temperature native structure; it then unfolds before refolding to a stable, native-like conformation. The initial unfolding follows the unfolding pathway described previously for higher-temperature simulations: the hydrophobic core is disrupted, the beta-sheet pulls apart and the alpha-helix unravels. The unfolded state reached under these conditions maintains a kernel of structure in the form of a non-native hydrophobic cluster. Refolding simply reverses this path, the side-chain interactions shift, the helix refolds, and the native packing and hydrogen bonds are recovered. The end result of this refolding is not the initial crystal structure; it contains the proper topology and the majority of the native contacts, but the structure is expanded and the contacts are long. We believe this to be the native state at elevated temperature, and the change in volume and contact lengths is consistent with experimental studies of other native proteins at elevated temperature and the chemical denaturant equivalent of T(m).

Direct correlation between proteins' folding rates and their amino acid compositions: An ab initio folding rate prediction

Discovering the mechanism of protein folding, in molecular biology, is a great challenge. A key step to this end is to find factors that correlate with protein folding rates. Over the past few years, many empirical parameters, such as contact order, long-range order, total contact distance, secondary structure contents, have been developed to reflect the correlation between folding rates and protein tertiary or secondary structures. However, the correlation between proteins' folding rates and their amino acid compositions has not been explored. In the present work, we examined systematically the correlation between proteins' folding rates and their amino acid compositions for two-state and multistate folders and found that different amino acids contributed differently to the folding progress. The relation between the amino acids' molecular weight and degeneracy and the folding rates was examined, and the role of hydrophobicity in the protein folding process was also inspected. As a consequence, a new indicator called composition index was derived, which takes no structure factors into account and is merely determined by the amino acid composition of a protein. Such an indicator is found to be highly correlated with the protein's folding rate (r > 0.7). From the results of this work, three points of concluding remarks are evident. (1) Two-state folders and multistate folders have different rate-determining amino acids. (2) The main determining information of a protein's folding rate is largely reflected in its amino acid composition. (3) Composition index may be the best predictor for an ab initio protein folding rate prediction directly from protein sequence from the standpoint of practical application.

Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: deciphering the effect of intermolecular interactions on computational structure prediction of the p27Kip1 protein bound to the cyclin A-cyclin-dependent kinase 2 complex

The relationship between folding mechanism coupled to binding and structure prediction of the tertiary complexes is studied for the p27(Kip) (1) protein which has an intrinsically disordered unbound form and undergoes a functional folding transition during complex formation with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) binary complex. Hierarchy of p27(Kip1) structural loss determined in our earlier studies from temperature-induced Monte Carlo simulations and subsequent characterization of the transition state ensemble (TSE) for the folding reaction have shown that simultaneous ordering of the p27(Kip1) native intermolecular interface for the beta-hairpin and beta-strand secondary structure elements is critical for nucleating a rapid kinetic transition to the native tertiary complex. In the present study, we investigate the effect of forming specific intermolecular interactions on structure prediction of the p27(Kip1) tertiary complex. By constraining different secondary structure elements of p27(Kip1) in their native bound conformations and conducting multiple simulated annealing simulations, we analyze differences in the success rate of predicting the native structure of p27(Kip1) in the tertiary complex. In accordance with the nucleation-condensation mechanism, we have found that further stabilization of the native intermolecular interface for the beta-hairpin and beta-strand elements of p27(Kip1), that become ordered in the TSE, but are hardly populated in the unbound state, results in a consistent acquisition of the native bound structure. Conversely, the excessive stablization of the local secondary structure elements, which are rarely detected in the TSE, has a detrimental effect on convergence to the native bound structure.

Site-specific labeling of proteins for single-molecule FRET by combining chemical and enzymatic modification

An often limiting factor for studying protein folding by single-molecule fluorescence resonance energy transfer (FRET) is the ability to site-specifically introduce a photostable organic FRET donor (D) and a complementary acceptor (A) into a polypeptide chain. Using alternating-laser excitation and chymotrypsin inhibitor 2 as a model, we show that chemical labeling of a unique cysteine, followed by enzymatic modification of a reactive glutamine in an N-terminally appended substrate sequence recognition tag for transglutaminase (TGase) affords stoichiometrically D-/A-labeled protein suitable for single-molecule FRET experiments. Thermodynamic data indicate that neither the presence of the TGase tag nor D/A labeling perturbs protein stability. As the N terminus in proteins is typically solvent accessible, a TGase tag can (in principle) be appended to any protein of interest by genetic engineering. Two-step chemical/enzymatic labeling may thus represent a simple, low-cost, and widely available strategy for D/A labeling of proteins for FRET-based single-molecule protein folding studies, even for non-protein-experts laboratories.

Atomically Detailed Description of the Unfolding of α-Lactalbumin by the Combined Use of Experiments and Simulations

The recombinant form of goat alpha-lactalbumin has a significantly faster unfolding rate compared to the authentic form, although the two molecules differ only in an extra methionine at the N terminus of the recombinant. The mechanism of the destabilization caused by this residue was investigated through the combined use of kinetic experiments and molecular dynamics simulations. Unfolding simulations for the authentic and recombinant forms at 398 K (ten trajectories of 5 ns for each form, 100 ns total) precisely reproduced the experimentally observed differences in unfolding behavior. In addition, experiments reproduced the destabilization of a mutant protein, T38A, faithfully as predicted by the simulations. This bidirectional verification between experiments and simulations enabled the atomically detailed description of the role of the extra methionine residue in the unfolding process.

Ensemble versus single-molecule protein unfolding

Molecular dynamics (MD) simulations are the classic single-molecule "experiments," providing atomic-resolution structural and dynamic information. However, the single-molecule nature of the technique has also been its shortcoming, with frequent criticisms of sampling inadequacies and questions regarding the ensemble behavior of large numbers of molecules. Given the increase in computer power, we now address this issue by performing a large number of simulations and comparing individual and ensemble properties. One hundred independent MD simulations of the protein chymotrypsin inhibitor 2 were carried out for 20 ns each at 498 K in water to more fully describe the potentially diverse routes of protein unfolding and investigate how representative a single trajectory can be. Rapid unfolding was observed in all cases with the trajectories distributed about an average "ensemble" path in which secondary and tertiary structure was lost concomitantly, with tertiary structure loss occurring slightly faster. Individual trajectories did, however, sample conformations far from the average path with very heterogeneous time-dependent properties. Nevertheless, all of the simulations but one followed the average ensemble pathway, such that a small number of simulations (5-10) are sufficient to capture the average properties of these states and the unfolding pathway.

How well can simulation predict protein folding kinetics and thermodynamics?

Simulation of protein folding has come a long way in five years. Notably, new quantitative comparisons with experiments for small, rapidly folding proteins have become possible. As the only way to validate simulation methodology, this achievement marks a significant advance. Here, we detail these recent achievements and ask whether simulations have indeed rendered quantitative predictions in several areas, including protein folding kinetics, thermodynamics, and physics-based methods for structure prediction. We conclude by looking to the future of such comparisons between simulations and experiments.

Sensitivity of the folding/unfolding transition state ensemble of chymotrypsin inhibitor 2 to changes in temperature and solvent

To better characterize the transition state for folding/unfolding and its sensitivity to environmental changes, we have run multiple molecular dynamics simulations of chymotrypsin inhibitor 2 (CI2) under varying solvent conditions and temperature. The transition state structures agree well with experiment, and are similar under all of the conditions investigated here. Increasing the temperature leads to some movement in the position of the transition state along several reaction coordinates, as measured by changes in properties of the transition state structures. These structural changes are in the direction of a more native-like transition state as denaturation conditions become more severe, as expected for a Hammond effect. These structural changes are not, however, reflected in the global structure as measured by the total number of contacts or the average S-values. These results suggest that the small changes in average Phi-values with temperature seen by experiment may be due to an increase in the sensitivity of the transition state to mutation rather than a change in the average structure of the transition state. A simple analysis of the rates of unfolding indicates that the free energy barrier to unfolding decreases with increasing temperature, but even in our very high temperature simulations there is a small free energy barrier.

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.