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

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

Identifying folding nucleus based on residue contact networks of proteins

In the native structure of a protein, all the residues are tightly parked together in a specific order following its folding and every residue contacts with some spatially neighbor residues. A residue contact network can be constructed by defining the residues as nodes and the native contacts as edges. During the folding of small single-domain proteins, there is a set of contacts (or bonds), defined as the folding nucleus (FN), which is formed around the transition state, i.e., a rate-limiting barrier located at about the middle between the unfolded states and the native state on the free energy landscape. Such a FN plays an essential role in the folding dynamics and the residues, which form the related contacts called as folding nucleus residues (FNRs). In this work, the FNRs in proteins are identified by using quantities which characterize the topology of residue contact networks of proteins. By comparing the specificities of residues with the network quantities K(R), L(R), and D(R), up to 90% FNRs of six typical proteins found experimentally are identified. It is found that the FNRs behave the full-closeness centrals rather than degree or closeness centers in the residue contact network, implying that they are important to the folding cooperativity of proteins. Our study shows that the FNRs can be identified solely from the native structures of proteins based on the analysis of residue contact network without any knowledge of the transition state ensemble.     

Unfolding the fold of cyclic cysteine-rich peptides

We propose a method to extensively characterize the native state ensemble of cyclic cysteine-rich peptides. The method uses minimal information, namely, amino acid sequence and cyclization, as a topological feature that characterizes the native state. The method does not assume a specific disulfide bond pairing for cysteines and allows the possibility of unpaired cysteines. A detailed view of the conformational space relevant for the native state is obtained through a hierarchic multi-resolution exploration. A crucial feature of the exploration is a geometric approach that efficiently generates a large number of distinct cyclic conformations independently of one another. A spatial and energetic analysis of the generated conformations associates a free-energy landscape to the explored conformational space. Application to three long cyclic peptides of different folds shows that the conformational ensembles and cysteine arrangements associated with free energy minima are fully consistent with available experimental data. The results provide a detailed analysis of the native state features of cyclic peptides that can be further tested in experiment.     

Reconstruction of the src-SH3 protein domain transition state ensemble using multiscale molecular dynamics simulations

We use an integrated computational approach to reconstruct accurately the transition state ensemble (TSE) for folding of the src-SH3 protein domain. We first identify putative TSE conformations from free energy surfaces generated by importance sampling molecular dynamics for a fully atomic, solvated model of the src-SH3 protein domain. These putative TSE conformations are then subjected to a folding analysis using a coarse-grained representation of the protein and rapid discrete molecular dynamics simulations. Those conformations that fold to the native conformation with a probability (P(fold)) of approximately 0.5, constitute the true transition state. Approximately 20% of the putative TSE structures were found to have a P(fold) near 0.5, indicating that, although correct TSE conformations are populated at the free energy barrier, there is a critical need to refine this ensemble. Our simulations indicate that the true TSE conformations are compact, with a well-defined central beta sheet, in good agreement with previous experimental and theoretical studies. A structured central beta sheet was found to be present in a number of pre-TSE conformations, however, indicating that this element, although required in the transition state, does not define it uniquely. An additional tight cluster of contacts between highly conserved residues belonging to the diverging turn and second beta-sheet of the protein emerged as being critical elements of the folding nucleus. A number of commonly used order parameters to identify the transition state for folding were investigated, with the number of native Cbeta contacts displaying the most satisfactory correlation with P(fold) values.     

Folding pathway dependence on energetic frustration and interaction heterogeneity for a three-dimensional hydrophobic protein model

Monte Carlo simulations of a hydrophobic protein model of 40 monomers in the cubic lattice are used to explore the effect of energetic frustration and interaction heterogeneity on its folding pathway. The folding pathway is described by the dependence of relevant conformational averages on an appropriate reaction coordinate, pfold, defined as the probability for a given conformation to reach the native structure before unfolding. We compare the energetically frustrated and heterogeneous hydrophobic potential, according to which individual monomers have a higher or lower tendency to form contacts unspecifically depending on their hydrophobicities, to an unfrustrated homogeneous Go-type potential with uniformly attractive native interactions and neutral non-native interactions (called Go1 in this study), and to an unfrustrated heterogeneous potential with neutral non-native interactions and native interactions having the same energy as the hydrophobic potential (called Go2 in this study). Folding kinetics are slowed down dramatically when energetic frustration increases, as expected and previously observed in a two-dimensional model. Contrary to our previous results in two dimensions, however, it appears that the folding pathway and transition state ensemble can be significantly dependent on the energy function used to stabilize the native structure. The sequence of events along the reaction coordinate, or the order along this coordinate in which different regions of the native conformation become structured, turns out to be similar for the hydrophobic and Go2 potentials, but with analogous events tending to occur at lower pfold values in the first case. In particular, the transition state obtained from the ensemble around pfold = 0.5 is more structured for the hydrophobic potential. For Go1, not only the transition state ensemble but the order of events itself is modified, suggesting that interaction heterogeneity, in addition to energetic frustration, can have significant effects on the folding mechanism, most likely by modifying the probability of different contacts in the unfolded state, the starting point for the folding reaction. Although based on a simple model, these results provide interesting insight into how sequence-dependent switching between folding pathways might occur in real proteins.     

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.     

Network and graph analyses of folding free energy surfaces

Protein folding is governed by a complex free energy surface whose entropic contributions are relevant because of the large number of degrees of freedom involved. Such complexity, in particular the conformational heterogeneity of the denatured state, is hidden in projections onto one or two order parameters (e.g. fraction of native contacts and/or radius of gyration), which usually results in relatively smooth surfaces. Recent approaches borrowed from network and graph theory have yielded quantitative unprojected representations of the free energy surfaces of a beta-hairpin and a three-stranded beta-sheet peptide using equilibrium folding-unfolding molecular dynamics simulations. Interestingly, the network and graph analyses of these structured peptides have revealed a very heterogeneous denatured state ensemble. It includes high-enthalpy, high-entropy conformations with fluctuating non-native secondary structure, as well as low-enthalpy, low-entropy traps.     

Kinetic analysis of molecular dynamics simulations reveals changes in the denatured state and switch of folding pathways upon single-point mutation of a beta-sheet miniprotein

The effects of a single-point mutation on folding thermodynamics and kinetics are usually interpreted by focusing on the native structure and the transition state. Here, the entire conformational spaces of a 20-residue three-stranded antiparallel beta-sheet peptide (double hairpin) and of its single-point mutant W10V are sampled close to the melting temperature by equilibrium folding-unfolding molecular dynamics simulations for a total of 40 micros. The folded state as well as the most populated free energy basins in the denatured state are isolated by grouping conformations according to fast relaxation at equilibrium. Such kinetic analysis provides more detailed and useful information than a simple projection of the free energy. The W10V mutant has the same native structure as the wild type peptide, and similar folding rate and stability. In the denatured state, the N-terminal hairpin is about 20% more structured in W10V than the wild type mainly because of van der Waals interactions. Notably, the W10V mutation influences also the van der Waals energy at the transition state ensemble causing a shift in the ratio of fluxes between two different transition state regions on parallel folding pathways corresponding to nucleation at either of the two beta-hairpins. Previous experimental studies have focused on the effects of denaturant-dependent or temperature-dependent changes in the structure of the denatured state. The atomistic simulations show that a single-point mutation in the central strand of a beta-sheet peptide results in remarkable changes in the topography of the denatured state ensemble. These changes modulate the relative accessibility of parallel folding pathways because of kinetic partitioning of the denatured state. Therefore, the observed dependence of the folding process on the starting ensemble raises questions on the biological significance of in vitro folding studies under strongly denaturing conditions.     

Determination of the transition state ensemble for the folding of ubiquitin from a combination of Phi and Psi analyses

Protein engineering techniques have emerged as powerful tools for characterizing transition states (TSs) for protein folding. Recently, the Ψ analysis, in which double-histidine mutations create the possibility of reversible crosslinking in the native state, has been proposed as an additional approach to the well-established Φ analysis. We present here a combination of these two procedures for defining the structure of the TS of ubiquitin, a small α/β protein that has been used extensively as a model system for both experimental and computational studies of the protein-folding process. We performed a series of molecular dynamics simulations in which Φ and Ψ values were used as ensemble-averaged structural restraints to determine an ensemble of structures representing the TS of ubiquitin. Although the available Ψ values for ubiquitin did not, by themselves, generate well-defined TS ensembles, the inclusion of the restricted set of zero or unity values, but not fractional ones, provided useful complementary information to the Φ analysis. Our results show that the TS of ubiquitin is formed by a relatively narrow ensemble of structures exhibiting an overall native-like topology in which the N-terminal and C-terminal regions are in close proximity.     

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-α, all-β, and mixed α/β and α + β) 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 α-helix maintained more structure in the TS ensemble than did residues starting in β-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.     

Enhanced specificity against misfolding in a thermostable mutant of the Tetrahymena ribozyme

Structured RNAs encode native conformations that are more stable than the vast ensembles of alternative conformations, but how this specificity is evolved is incompletely understood. Here we show that a variant of the Tetrahymena group I intron ribozyme that was generated previously by in vitro selection for enhanced thermostability also displays modestly enhanced specificity against a stable misfolded structure that is globally similar to the native state, despite the absence of selective pressure to increase the energy gap between these structures. The enhanced specificity for native folding arises from mutations in two nucleotides that are close together in space in the native structure, and additional experiments show that these two mutations do not affect the stability of the misfolded conformation relative to the largely unstructured transition state ensemble for interconversion between the native and misfolded conformers. Thus, they selectively stabilize the native state, presumably by strengthening a local tertiary contact network that cannot form in the misfolded conformation. The stabilization is larger in the presence of the peripheral element P5abc, suggesting that cooperative tertiary structure formation plays a key role in the enhanced stability. The increased specificity in the absence of explicit selection suggests that the large energy gap in the wild-type RNA may have arisen analogously, a consequence of selective pressure for stability of the functional structure. More generally, the structural rigidity and intricate networks of contacts in structured RNAs may allow them to evolve substantial structural specificity without explicit negative selection, even against closely related alternative structures.     

Toward Correct Protein Folding Potentials

Empirical protein folding potentialfunctions should have a global minimum nearthe native conformationof globular proteins that fold stably, andthey should give the correct free energy offolding. We demonstrate that otherwise verysuccessful potentials fail to have even alocal minimumanywhere near the native conformation, anda seemingly well validated method ofestimatingthe thermodynamic stability of the nativestate is extremely sensitive to smallperturbations inatomic coordinates. These are bothindicative of fitting a great deal ofirrelevant detail. Here weshow how to devise a robust potentialfunction that succeeds very well at bothtasks, at least for alimited set of proteins, and this involvesdeveloping a novel representation of thedenatured state.Predicted free energies of unfolding for 25mutants of barnase are in close agreementwith theexperimental values, while for 17 mutantsthere are substantial discrepancies.     

Ab initio computational modeling of loops in G-protein-coupled receptors: lessons from the crystal structure of rhodopsin

With the help of the crystal structure of rhodopsin an ab initio method has been developed to calculate the three-dimensional structure of the loops that connect the transmembrane helices (TMHs). The goal of this procedure is to calculate the loop structures in other G-protein coupled receptors (GPCRs) for which only model coordinates of the TMHs are available. To mimic this situation a construct of rhodopsin was used that only includes the experimental coordinates of the TMHs while the rest of the structure, including the terminal domains, has been removed. To calculate the structure of the loops a method was designed based on Monte Carlo (MC) simulations which use a temperature annealing protocol, and a scaled collective variables (SCV) technique with proper structural constraints. Because only part of the protein is used in the calculations the usual approach of modeling loops, which consists of finding a single, lowest energy conformation of the system, is abandoned because such a single structure may not be a representative member of the native ensemble. Instead, the method was designed to generate structural ensembles from which the single lowest free energy ensemble is identified as representative of the native folding of the loop. To find the native ensemble a successive series of SCV-MC simulations are carried out to allow the loops to undergo structural changes in a controlled manner. To increase the chances of finding the native funnel for the loop, some of the SCV-MC simulations are carried out at elevated temperatures. The native ensemble can be identified by an MC search starting from any conformation already in the native funnel. The hypothesis is that native structures are trapped in the conformational space because of the high-energy barriers that surround the native funnel. The existence of such ensembles is demonstrated by generating multiple copies of the loops from their crystal structures in rhodopsin and carrying out an extended SCV-MC search. For the extracellular loops e1 and e3, and the intracellular loop i1 that were used in this work, the procedure resulted in dense clusters of structures with Calpha-RMSD approximately 0.5 angstroms. To test the predictive power of the method the crystal structure of each loop was replaced by its extended conformations. For e1 and i1 the procedure identifies native clusters with Calpha-RMSD approximately 0.5 angstroms and good structural overlap of the side chains; for e3, two clusters were found with Calpha-RMSD approximately 1.1 angstroms each, but with poor overlap of the side chains. Further searching led to a single cluster with lower Calpha-RMSD but higher energy than the two previous clusters. This discrepancy was found to be due to the missing elements in the constructs available from experiment for use in the calculations. Because this problem will likely appear whenever parts of the structural information are missing, possible solutions are discussed.     

Protein-inhibitor flexible docking by a multicanonical sampling: native complex structure with the lowest free energy and a free-energy barrier distinguishing the native complex from the others

Flexible docking between a protein (lysozyme) and an inhibitor (tri-N-acetyl-D-glucosamine, tri-NAG) was carried out by an enhanced conformational sampling method, multicanonical molecular dynamics simulation. We used a flexible all-atom model to express lysozyme, tri-NAG, and water molecules surrounding the two bio-molecules. The advantages of this sampling method are as follows: the conformation of system is widely sampled without trapping at energy minima, a thermally equilibrated conformational ensemble at an arbitrary temperature can be reconstructed from the simulation trajectory, and the thermodynamic weight can be assigned to each sampled conformation. During the simulation, exchanges between the binding and free (i.e., unbinding) states of the protein and the inhibitor were repeatedly observed. The conformational ensemble reconstructed at 300 K involved various conformational clusters. The main outcome of the current study is that the most populated conformational cluster (i.e., the cluster of the lowest free energy) was assigned to the native complex structure (i.e., the X-ray complex structure). The simulation also produced non-native complex structures, where the protein and the inhibitor bound with different modes from that of the native complex structure, as well as the unbinding structures. A free-energy barrier (i.e., activation free energy) was clearly detected between the native complex structures and the other structures. The thermal fluctuations of tri-NAG in the lowest free-energy complex correlated well with the X-ray B-factors of tri-NAG in the X-ray complex structure. The existence of the free-energy barrier ensures that the lowest free-energy structure can be discriminated naturally from the other structures. In other words, the multicanonical molecular dynamics simulation can predict the native complex structure without any empirical objective function. The current study also manifested that the flexible all-atom model and the physico-chemically defined atomic-level force field can reproduce the native complex structure. A drawback of the current method is that it requires a time consuming computation due to the exhaustive conformational sampling. We discussed a possibility for combining the current method with conventional docking methods.     

Abstracts: Albany 2007, The 15th Conversation

Abstract

Forty nine molecular dynamics simulations of unfolding trajectories of the segment B1 of streptococcal protein G (GB1) provide a direct demonstration of the diversity of unfolding pathway and give a statistically utmost unfolding pathway under the physical property space. Twelve physical properties of the protein were chosen to construct a 12-dimensional property space. Then the 12-dimentional property space was reduced to a 3-dimentional principle component property space. Under the property space, the multiple unfolding trajectories look like “trees”, which have some common characters. The “root of the tree” corresponds to the native state, the “bole” homologizes the partially unfolded conformations, and the “crown” is in correspondence to the unfolded state. These unfolding trajectories can be divided into three types. The first one has the characters of straight “bole” and “crown” corresponding to a fast two-state unfolding pathway of GB1. The second one has the character of “the standstill in the middle tree bole”, which may correspond to a three-state unfolding pathway. The third one has the character of “the circuitous bole” corresponding to a slow two-state unfolding pathway. The fast two-state unfolding pathway is a statistically utmost unfolding pathway or preferred pathway of GB1, which occupies 53% of 49 unfolding trajectories. In the property space all the unfolding trajectories construct a thermal unfolding pathway ensemble of GB1. The unfolding pathway ensemble resembles a funnel that is gradually emanative from the native state ensemble to the unfolded state ensemble. In the property space, the thermal unfolded state distribution looks like electronic cloud in quantum mechanics. The unfolded states of the independent unfolding simulation trajectories have substantial overlaps, indicating that the thermal unfolded states are confined by the physical property values, and the number of protein unfolded state are much less than that was believed before.     

Molecular simulation uncovers the conformational space of the λ Cro dimer in solution

The significant variation among solved structures of the λ Cro dimer suggests its flexibility. However, contacts in the crystal lattice could have stabilized a conformation which is unrepresentative of its dominant solution form. Here we report on the conformational space of the Cro dimer in solution using replica exchange molecular dynamics in explicit solvent. The simulated ensemble shows remarkable correlation with available x-ray structures. Network analysis and a free energy surface reveal the predominance of closed and semi-open dimers, with a modest barrier separating these two states. The fully open conformation lies higher in free energy, indicating that it requires stabilization by DNA or crystal contacts. Most NMR models are found to be unstable conformations in solution. Intersubunit salt bridging between Arg⁴ and Glu⁵³ during simulation stabilizes closed conformations. Because a semi-open state is among the low-energy conformations sampled in simulation, we propose that Cro-DNA binding may not entail a large conformational change relative to the dominant dimer forms in solution.     

Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion.

Classic molecular motion simulation techniques, such as Monte Carlo (MC) simulation, generate motion pathways one at a time and spend most of their time in the local minima of the energy landscape defined over a molecular conformation space. Their high computational cost prevents them from being used to compute ensemble properties (properties requiring the analysis of many pathways). This paper introduces stochastic roadmap simulation (SRS) as a new computational approach for exploring the kinetics of molecular motion by simultaneously examining multiple pathways. These pathways are compactly encoded in a graph, which is constructed by sampling a molecular conformation space at random. This computation, which does not trace any particular pathway explicitly, circumvents the local-minima problem. Each edge in the graph represents a potential transition of the molecule and is associated with a probability indicating the likelihood of this transition. By viewing the graph as a Markov chain, ensemble properties can be efficiently computed over the entire molecular energy landscape. Furthermore, SRS converges to the same distribution as MC simulation. SRS is applied to two biological problems: computing the probability of folding, an important order parameter that measures the "kinetic distance" of a protein's conformation from its native state; and estimating the expected time to escape from a ligand-protein binding site. Comparison with MC simulations on protein folding shows that SRS produces arguably more accurate results, while reducing computation time by several orders of magnitude. Computational studies on ligand-protein binding also demonstrate SRS as a promising approach to study ligand-protein interactions.     

NMR investigations on residue level unfolding thermodynamics in DLC8 dimer by temperature dependent native state hydrogen exchange

Understanding protein stability at residue level detail in the native state ensemble of a protein is crucial to understanding its biological function. At the same time, deriving thermodynamic parameters using conventional spectroscopic and calorimetric techniques remains a major challenge for some proteins due to protein aggregation and irreversibility of denaturation at higher temperature values. In this regard, we describe here the NMR investigations on the conformational stabilities and related thermodynamic parameters such as local unfolding enthalpies, heat capacities and transition midpoints in DLC8 dimer, by using temperature dependent native state hydrogen exchange; this protein aggregates at high (>65°C) temperatures. The stability (free energy) of the native state was found to vary substantially with temperature at every residue. Significant differences were found in the thermodynamic parameters at individual residue sites indicating that the local environments in the protein structure would respond differently to external perturbations; this reflects on plasticity differences in different regions of the protein. Further, comparison of this data with similar data obtained from GdnHCl dependent native state hydrogen exchange indicated many similarities at residue level, suggesting that local unfolding transitions may be similar in both the cases. This has implications for the folding/unfolding mechanisms of the protein. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.