Folding and stretching in a Go-like model of titin

Generalization of the elastic network model for the study of large conformational changes in biomolecules

The elastic network (EN) is a prime model that describes the long-time dynamics of biomolecules. However, the use of harmonic potentials renders this model insufficient for studying large conformational changes of proteins (e.g. stretching of proteins, folding and thermal unfolding). Here, we extend the capabilities of the EN model by using a harmonic approximation described by Lennard-Jones (LJ) interactions for far contacts and native contacts obtained from the standard overlap criterion as in the case of Gō-like models. While our model is validated against the EN model by reproducing the equilibrium properties for a number of proteins, we also show that the model is suitable for the study of large conformation changes by providing various examples. In particular, this is illustrated on the basis of pulling simulations that predict with high accuracy the experimental data on the rupture force of the studied proteins. Furthermore, in the case of DDFLN4 protein, our pulling simulations highlight the advantages of our model with respect to Gō-like approaches, where the latter fail to reproduce previous results obtained by all-atom simulations that predict an additional characteristic peak for this protein. In addition, folding simulations of small peptides yield different folding times for α-helix and β-hairpin, in agreement with experiment, in this way providing further opportunities for the application of our model in studying large conformational changes of proteins. In contrast to the EN model, our model is suitable for both normal mode analysis and molecular dynamics simulation. We anticipate that the proposed model will find applications in a broad range of problems in biology, including, among others, protein folding and thermal unfolding.

Combining the MARTINI and Structure-Based Coarse-Grained Approaches for the Molecular Dynamics Studies of Conformational Transitions in Proteins

The application of coarse-grained (CG) models in biology is essential to access large length and time scales required for the description of many biological processes. The ELNEDIN protein model is based on the well-known MARTINI CG force-field and incorporates additionally harmonic bonds of a certain spring constant within a defined cutoff distance between pairs of residues, in order to preserve the native structure of the protein. In this case, the use of unbreakable harmonic bonds hinders the study of unfolding and folding processes. To overcome this barrier we have replaced the harmonic bonds with Lennard-Jones interactions based on the contact map of the native protein structure as is done in Go̅-like models. This model exhibits very good agreement with all-atom simulations and the ELNEDIN. Moreover, it can capture the structural motion linked to particular catalytic activity in the Man5B protein, in agreement with all-atom simulations. In addition, our model is based on the van der Waals radii, instead of a cutoff distance, which results in a smaller contact map. In conclusion, we anticipate that our model will provide further possibilities for studying biological systems based on the MARTINI CG force-field by using advanced-sampling methods, such as parallel tempering and metadynamics.

Determination of contact maps in proteins: A combination of structural and chemical approaches

Contact map selection is a crucial step in structure-based molecular dynamics modelling of proteins. The map can be determined in many different ways. We focus on the methods in which residues are represented as clusters of effective spheres. One contact map, denoted as overlap (OV), is based on the overlap of such spheres. Another contact map, named Contacts of Structural Units (CSU), involves the geometry in a different way and, in addition, brings chemical considerations into account. We develop a variant of the CSU approach in which we also incorporate Coulombic effects such as formation of the ionic bridges and destabilization of possible links through repulsion. In this way, the most essential and well defined contacts are identified. The resulting residue-residue contact map, dubbed repulsive CSU (rCSU), is more sound in its physico-chemical justification than CSU. It also provides a clear prescription for validity of an inter-residual contact: the number of attractive atomic contacts should be larger than the number of repulsive ones - a feature that is not present in CSU. However, both of these maps do not correlate well with the experimental data on protein stretching. Thus, we propose to use rCSU together with the OV map. We find that the combined map, denoted as OV+rCSU, performs better than OV. In most situations, OV and OV+rCSU yield comparable folding properties but for some proteins rCSU provides contacts which improve folding in a substantial way. We discuss the likely residue-specificity of the rCSU contacts. Finally, we make comparisons to the recently proposed shadow contact map, which is derived from different principles.

Connecting thermal and mechanical protein (un)folding landscapes

Molecular dynamics simulations supplement single-molecule pulling experiments by providing the possibility of examining the full free energy landscape using many coordinates. Here, we use an all-atom structure-based model to study the force and temperature dependence of the unfolding of the protein filamin by applying force at both termini. The unfolding time-force relation τ(F) indicates that the force-induced unfolding behavior of filamin can be characterized into three regimes: barrier-limited low- and intermediate-force regimes, and a barrierless high-force regime. Slope changes of τ(F) separate the three regimes. We show that the behavior of τ(F) can be understood from a two-dimensional free energy landscape projected onto the extension X and the fraction of native contacts Q. In the low-force regime, the unfolding rate is roughly force-independent due to the small (even negative) separation in X between the native ensemble and transition state ensemble (TSE). In the intermediate-force regime, force sufficiently separates the TSE from the native ensemble such that τ(F) roughly follows an exponential relation. This regime is typically explored by pulling experiments. While X may fail to resolve the TSE due to overlap with the unfolded ensemble just below the folding temperature, the overlap is minimal at lower temperatures where experiments are likely to be conducted. The TSE becomes increasingly structured with force, whereas the average order of structural events during unfolding remains roughly unchanged. The high-force regime is characterized by barrierless unfolding, and the unfolding time approaches a limit of ∼10 μs for the highest forces we studied. Finally, a combination of X and Q is shown to be a good reaction coordinate for almost the entire force range.

Statistical radii associated with amino acids to determine the contact map: fixing the structure of a type I cohesin domain in the Clostridium thermocellum cellulosome

We propose to improve and simplify protein refinement procedures through consideration of which pairs of amino acid residues should form native contacts. We first consider 11 330 proteins from the CATH database to determine statistical distributions of contacts associated with a given type of amino acid. The distributions are set across the distances between the α-C atoms that are in contact. Based on this data, we determine typical radii of effective spheres that can be placed on the α-C atoms in order to reconstruct the distribution of the contact lengths. This is done by checking for overlaps with enlarged van der Waals spheres associated with heavy atoms on other amino acids.The resulting contacts can be used to identify non-native contacts that may arise during the time evolution of structure-based models. Here, the radii are used to guide reconstruction of nine missing side chains in a type I cohesin domain with the Protein Data Bank code 1AOH. We first identify the likely missing contacts and then sculpt the corresponding side chains by standard refinement tools to achieve consistency with the expected contact map. One ambiguity in refinement is resolved by determining all-atom conformational energies.

A structure-based model fails to probe the mechanical unfolding pathways of the titin I27 domain

We discuss the use of a structure based Cα-Go model and Langevin dynamics to study in detail the mechanical properties and unfolding pathway of the titin I27 domain. We show that a simple Go-model does detect correctly the origin of the mechanical stability of this domain. The unfolding free energy landscape parameters x(u) and ΔG(‡), extracted from dependencies of unfolding forces on pulling speeds, are found to agree reasonably well with experiments. We predict that above v = 10(4) nm/s the additional force-induced intermediate state is populated at an end-to-end extension of about 75 Å. The force-induced switch in the unfolding pathway occurs at the critical pulling speed v(crit) ≈ 10(6)-10(7) nm/s. We argue that this critical pulling speed is an upper limit of the interval where Bell's theory works. However, our results suggest that the Go-model fails to reproduce the experimentally observed mechanical unfolding pathway properly, yielding an incomplete picture of the free energy landscape. Surprisingly, the experimentally observed intermediate state with the A strand detached is not populated in Go-model simulations over a wide range of pulling speeds. The discrepancy between simulation and experiment is clearly seen from the early stage of the unfolding process which shows the limitation of the Go model in reproducing unfolding pathways and deciphering the complete picture of the free energy landscape.

Nanomechanics of β-rich proteins related to neuronal disorders studied by AFM, all-atom and coarse-grained MD methods

Computer simulations of protein unfolding substantially help to interpret force-extension curves measured in single-molecule atomic force microscope (AFM) experiments. Standard all-atom (AA) molecular dynamics simulations (MD) give a good qualitative mechanical unfolding picture but predict values too large for the maximum AFM forces with the common pulling speeds adopted here. Fine tuned coarse-grain MD computations (CG MD) offer quantitative agreement with experimental forces. In this paper we address an important methodological aspect of MD modeling, namely the impact of numerical noise generated by random assignments of bead velocities on maximum forces (F_max) calculated within the CG MD approach. Distributions of CG forces from 2000 MD runs for several model proteins rich in β structures and having folds with increasing complexity are presented. It is shown that F_max have nearly Gaussian distributions and that values of F_max for each of those β-structures may vary from 93.2 ± 28.9 pN (neurexin) to 198.3 ± 25.2 pN (fibronectin). The CG unfolding spectra are compared with AA steered MD data and with results of our AFM experiments for modules present in contactin, fibronectin and neurexin. The stability of these proteins is critical for the proper functioning of neuronal synaptic clefts. Our results confirm that CG modeling of a single molecule unfolding is a good auxiliary tool in nanomechanics but large sets of data have to be collected before reliable comparisons of protein mechanical stabilities are made.

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Coarse-grain Protein Models

Coarse-graining is a powerful approach for modeling biomolecules that, over the last few decades, has been extensively applied to proteins. Coarse-grain models offer access to large systems and to slow processes without becoming computationally unmanageable. In addition, they are very versatile, enabling both the protein representation and the energy function to be adapted to the biological problem in hand. This review concentrates on modeling soluble proteins and their assemblies. It presents an overview of the coarse-grain representations, of the associated interaction potentials, and of the optimization procedures used to define them. It then shows how coarse-grain models have been used to understand processes involving proteins, from their initial folding to their functional properties, their binary interactions, and the assembly of large complexes.

Computational investigation of the effect of thermal perturbation on the mechanical unfolding of titin I27

The emergence of single-molecule force measurement experiments has facilitated a better understanding of protein folding pathways and the thermodynamics involved. Computational methods such as steered molecular dynamics (SMD) simulations are helpful in providing atomistic level information on the unfolding pathways. Recent experimental studies have showed that combinations of single-molecule experiments with traditional methods such as chemical and/or thermal denaturation yield additional insights into the folding phenomenon. In this study, we report results from extensive computations (a total of about 60 SMD simulations with a total length of about 0.4 μs) that address the effect of thermal perturbation on the mechanical stability of the I27 domain of the protein titin. A wide range of temperatures (280-340 K) were considered for the pulling, which was done at both constant velocity and constant force using SMD simulations. Good agreement with experimental data, such as for the trends in changes in average force and the maximum force with respect to the temperature, was obtained. This study identifies two competing pathways for the mechanical unfolding of I27, and illustrates the significance of combining various techniques to examine protein folding.

Stretching and twisting of the DNA duplexes in coarse-grained dynamical models

Three coarse-grained molecular dynamics models of the double-stranded DNA are proposed and compared in the context of single molecule mechanical manipulation such as twisting and various schemes of stretching-unzipping, shearing, two-strand stretching and stretching of only one strand. The models differ in the number of effective beads (between two and five) representing each nucleotide. They all show similar behaviour, but the bigger the resolution, the more details in the force patterns. The models incorporate the effective Lennard-Jones potentials in the couplings between two strands and harmonic potentials to describe the structure of a single strand. The force patterns are shown to depend on the sequence studied. In particular, both shearing and unzipping for an all-AT sequence lead to lower forces than for an all-CG sequence. The unzipping patterns and the corresponding scenario diagrams for the contact rupture events are found to reflect the sequential information if the temperature is moderate and initial transients are discarded. The derived torque-force phase diagram is found to be qualitatively consistent with experiments and all-atom simulations.

Mechanical strength of 17,134 model proteins and cysteine slipknots

A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17 134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cystein slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.

The advances in nanotechnology have allowed for manipulation of single biomolecules and determination of their elastic properties. Titin was among the first proteins studied in this way. Its unravelling by stretching requires a 204 pN force. The resistance to stretching comes mostly from a localized region known as a force clamp. In titin, the force clamp is simple as it is formed by two parallel β-strands that are sheared on pulling. Studies of a set of under a hundred proteins accomplished in the last decade have revealed a variety of the force clamps that lead to forces ranging from under 20 pN to about 500 pN. This set comprises only a tiny fraction of proteins known. Thus one needs guidance as to what proteins should be considered for specific mechanical properties. Such a guidance is provided here through simulations within simplified coarse-grained models on 17 134 proteins that are stretched at constant speed. We correlate their unravelling forces with two structure classification schemes. We identify proteins with large resistance to unravelling and characterize their force clamps. Quite a few top strength proteins owe their sturdiness to a new type of the force clamp: the cystein slipknot in which the force peak is due to dragging of a piece of the backbone through a closed ring formed by two other pieces of the backbone and two connecting disulphide bonds.

Experimental and computational characterization of biological liquid crystals: a review of single-molecule bioassays

Quantitative understanding of the mechanical behavior of biological liquid crystals such as proteins is essential for gaining insight into their biological functions, since some proteins perform notable mechanical functions. Recently, single-molecule experiments have allowed not only the quantitative characterization of the mechanical behavior of proteins such as protein unfolding mechanics, but also the exploration of the free energy landscape for protein folding. In this work, we have reviewed the current state-of-art in single-molecule bioassays that enable quantitative studies on protein unfolding mechanics and/or various molecular interactions. Specifically, single-molecule pulling experiments based on atomic force microscopy (AFM) have been overviewed. In addition, the computational simulations on single-molecule pulling experiments have been reviewed. We have also reviewed the AFM cantilever-based bioassay that provides insight into various molecular interactions. Our review highlights the AFM-based single-molecule bioassay for quantitative characterization of biological liquid crystals such as proteins.

Mechanical signaling on the single protein level studied using steered molecular dynamics

Efficient communication between the cell and its external environment is of the utmost importance to the function of multicellular organisms. While signaling events can be generally characterized as information exchange by means of controlled energy conversion, research efforts have hitherto mainly been concerned with mechanisms involving chemical and electrical energy transfer. Here, we review recent computational efforts addressing the function of mechanical force in signal transduction. Specifically, we focus on the role of steered molecular dynamics (SMD) simulations in providing details at the atomic level on a group of protein domains, which play a fundamental role in signal exchange by responding properly to mechanical strain. We start by giving a brief introduction to the SMD technique and general properties of mechanically stable protein folds, followed by specific examples illustrating three general regimes of signal transfer utilizing mechanical energy: purely mechanical, mechanical to chemical, and chemical to mechanical. Whenever possible the physiological importance of the example at hand is stressed to highlight the diversity of the processes in which mechanical signaling plays a key role. We also provide an overview of future challenges and perspectives for this rapidly developing field.

Large Protein Dynamics Described by Hierarchical-Component Mode Synthesis

Protein dynamics has played a pivotal role in understanding the biological function of protein. For investigation of such dynamics, normal-mode analysis (NMA) has been broadly employed with atomistic model and/or coarse-grained models such as elastic network model (ENM). For large protein complexes, NMA with even ENM encounters the expensive computational process such as diagonalization of Hessian (stiffness) matrix. Here, we suggest the hierarchical-component mode synthesis (hCMS), which allows the fast computation of low-frequency normal modes related to conformational change. Specifically, a large protein structure is regarded as a combination of several structural units, for which the eigen-value problem is utilized for obtaining the frequencies and their normal modes for each structural unit, and consequently, such frequencies and normal modes are assembled with geometrical constraint for interface between structural units in order to find the low-frequency normal modes of a large protein complex. It is shown that hCMS is able to provide the normal modes with accuracy, quantitatively comparable to those of original NMA. This implies that hCMS may enable the computationally efficient analysis of large protein dynamics.

Insights from coarse-grained Gō models for protein folding and dynamics

Exploring the landscape of large scale conformational changes such as protein folding at atomistic detail poses a considerable computational challenge. Coarse-grained representations of the peptide chain have therefore been developed and over the last decade have proved extremely valuable. These include topology-based Gō models, which constitute a smooth and funnel-like approximation to the folding landscape. We review the many variations of the Gō model that have been employed to yield insight into folding mechanisms. Their success has been interpreted as a consequence of the dominant role of the native topology in folding. The role of local contact density in determining protein dynamics is also discussed and is used to explain the ability of Gō-like models to capture sequence effects in folding and elucidate conformational transitions.

Predicting the order in which contacts are broken during single molecule protein stretching experiments

We combine two methods to enable the prediction of the order in which contacts are broken under external stretching forces in single molecule experiments. These two methods are Gō-like models and elastic network models. The Gō-like models have shown remarkable success in representing many aspects of protein behavior, including the reproduction of experimental data obtained from atomic force microscopy. The simple elastic network models are often used successfully to predict the fluctuations of residues around their mean positions, comparing favorably with the experimentally measured crystallographic B-factors. The behavior of biomolecules under external forces has been demonstrated to depend principally on their elastic properties and the overall shape of their structure. We have studied in detail the muscle protein titin and green fluorescent protein and tested for ten other proteins. First, we stretch the proteins computationally by performing stochastic dynamics simulations with the Gō-like model. We obtain the force-displacement curves and unfolding scenarios of possible mechanical unfolding. We then use the elastic network model to calculate temperature factors (B-factors) and compare the slowest modes of motion for the stretched proteins and compare them with the predicted order of breaking contacts between residues in the Gō-like model. Our results show that a simple Gaussian network model is able to predict contacts that break in the next time stage of stretching. Additionally, we have found that the contact disruption is strictly correlated with the highest force exerted by the backbone on these residues. Our prediction of bond-breaking agrees well with the unfolding scenario obtained with the Gō-like model. We anticipate that this method will be a useful new tool for interpreting stretching experiments.

Toward a molecular understanding of the anisotropic response of proteins to external forces: insights from elastic network models

With recent advances in single-molecule manipulation techniques, it is now possible to measure the mechanical resistance of proteins to external pulling forces applied at specific positions. Remarkably, such recent studies demonstrated that the pulling/stretching forces required to initiate unfolding vary considerably depending on the location of the application of the forces, unraveling residue/position-specific response of proteins to uniaxial tension. Here we show that coarse-grained elastic network models based on the topology of interresidue contacts in the native state can satisfactory explain the relative sizes of such stretching forces exerted on different residue pairs. Despite their simplicity, such models presumably capture a fundamental property that dominates the observed behavior: deformations that can be accommodated by the relatively lower frequency modes of motions intrinsically favored by the structure require weaker forces and vice versa. The mechanical response of proteins to external stress is therefore shown to correlate with the anisotropic fluctuation dynamics intrinsically accessible in the folded state. The dependence on the overall fold implies that evolutionarily related proteins sharing common structural features tend to possess similar mechanical properties. However, the theory cannot explain the differences observed in a number of structurally similar but sequentially distant domains, such as the fibronectin domains.

Mapping folding energy landscapes with theory and experiment

The detailed characterization of the overall free energy landscape associated with the folding process of a protein is the ultimate goal in protein folding studies. Modern experimental techniques and all-atom simulations provide a way to obtain accurate thermodynamic and kinetic measurements, but they are oftentimes restricted to probe limited regions of a protein landscape. Although simplified protein models can access larger regions of the landscape, they are built on assumptions and approximations that can affect the accuracy of the results. We review here recent promising approaches that allow to combine the complementary strengths of theory and experiment for a more complete characterization of a protein folding landscape at multiple resolutions. Recent results and possible applications are discussed.

Mechanical unfolding of ubiquitin molecules

Mechanical stretching of ubiquitin and of its several repeats are studied through molecular-dynamics simulations. A Go-type model [H. Abe and N. Go, Biopolymers 20, 1013 (1981)] with a realistic contact map and with Lennard-Jones contact interactions is used. The model qualitatively reproduces the experimentally observed differences between force-extension patterns obtained on polyubiquitins stretched by various linkages. The terminal-to-terminal stretching of polyubiquitin results in peak forces similar to those measured for titin-based polyproteins and of a magnitude that matches measurements. Consistent with the experimental measurements, the simulated peak forces depend on the pulling speed logarithmically when thermal fluctuations are explicitly introduced. These results validate the application of topology-based models in the study of the mechanical stretching of proteins.

Mechanical unfolding revisited through a simple but realistic model

Single-molecule experiments and their application to probe the mechanical resistance and related properties of proteins provide a new dimension in our knowledge of these important and complex biological molecules. Single-molecule techniques may not have yet overridden solution experiments as a method of choice to characterize biophysical and biological properties of proteins, but have stimulated a debate and contributed considerably to bridge theory and experiment. Here we demonstrate this latter contribution by illustrating the reach of some theoretical findings using a solvable but nontrivial molecular model whose properties are analogous to those of the corresponding experimental systems. In particular, we show the relationship between the thermodynamic and the mechanical properties of a protein. The simulations presented here also illustrate how forced and spontaneous unfolding occur through different pathways and that folding and unfolding rates at equilibrium cannot in general be obtained from forced unfolding experiments or simulations. We also study the relationship between the energy surface and the mechanical resistance of a protein and show how a simple analysis of the native state can predict much of the mechanical properties of a protein.

Coarse-grained peptide modeling using a systematic multiscale approach

A systematic new approach to derive multiscale coarse-grained (MS-CG) models has been recently developed. The approach employs information from atomistically detailed simulations to derive CG forces and associated effective potentials. In this work, the MS-CG methodology is extended to study two peptides representing distinct structural motifs, alpha-helical polyalanine and the beta-hairpin V(5)PGV(5). These studies represent the first known application of this approach to peptide systems. Good agreement between the MS-CG and atomistic models is achieved for several structural properties including radial distribution functions, root mean-square deviation, and radius of gyration. The new MS-CG models are able to preserve the native states of these peptides within approximately 1 A backbone root mean-square deviation during CG simulations. The MS-CG approach, as with most coarse-grained models, has the potential to increase the length and timescales accessible to molecular simulations. However, it is also able to maintain a clear connection to the underlying atomistic-scale interactions.

Optimal allocation of replicas in parallel tempering simulations

We have studied the efficiency of parallel tempering simulations for a variety of systems including a coarse-grained protein, an atomistic model polypeptide, and the Lennard-Jones fluid. A scheme is proposed for the optimal allocation of temperatures in these simulations. The method is compared to the existing empirical approaches used for this purpose. Accuracy associated with the computed thermodynamic quantities such as specific heat is also computed and their dependence on the trial-exchange acceptance rate is reported.

Molecular mechanisms of cellular mechanics

Mechanical forces play an essential role in cellular processes as input, output, and signals. Various protein complexes in the cell are designed to handle, transform and use such forces. For instance, proteins of muscle and the extracellular matrix can withstand considerable stretching forces, hearing-related and mechanosensory proteins can transform weak mechanical stimuli into electrical signals, and regulatory proteins are suited to forcing DNA into loops to control gene expression. Here we review the structure-function relationship of four protein complexes with well defined and representative mechanical functions. The first example is titin, a protein that confers passive elasticity on muscle. The second system is the elastic extracellular matrix protein, fibronectin, and its cellular receptor integrin. The third protein system is the transduction apparatus in hearing and other mechanical senses, likely containing cadherin and ankyrin repeats. The last system is the lac repressor protein, which regulates gene expression by looping DNA. This review focuses on atomic level descriptions of the physical mechanisms underlying the various mechanical functions of the stated proteins.

Mechanical properties of the domains of titin in a Go-like model

Comparison of properties of three domains of titin, I1, I27, and I28, in a simple geometry-based model shows that despite a high structural homology between their native states different domains show similar but distinguishable mechanical properties. Folding properties of the separate domains are predicted to be diversified which reflects sensitivity of the kinetics to the details of native structures. The Go-like model corresponding to the experimentally resolved native structure of the I1 domain is found to provide the biggest thermodynamic and mechanical stability compared to the other domains studied here. We analyze elastic, thermodynamic, and kinetic properties of several structures corresponding to the I28 domain as obtained through homology-based modeling. We discuss the ability of the models of the I28 domain to reproduce experimental results qualitatively. A strengthening of contacts that involve hydrophobic amino acids does not affect theoretical comparisons of the domains. Tandem linkages of up to five identical or different domains unravel in a serial fashion at low temperatures. We study the nature of the intermediate state that arises in the early stages of the serial unraveling and find it to qualitatively agree with the results of Marszalek et al.

Pulling single bacteriorhodopsin out of a membrane: Comparison of simulation and experiment

Mechanical unfolding of single bacteriorhodopsins from a membrane bilayer is studied using molecular dynamics simulations. The initial conformation of the lipid membrane is determined through all-atom simulations and then its coarse-grained representation is used in the studies of stretching. A Go-like model with a realistic contact map and with Lennard-Jones contact interactions is applied to model the protein-membrane system. The model qualitatively reproduces the experimentally observed differences between force-extension patterns obtained on bacteriorhodopsin at different temperatures and predicts a lack of symmetry in the choice of the terminus to pull by. It also illustrates the decisive role of the interactions of the protein with the membrane in determining the force pattern and thus the stability of transmembrane proteins.

Thermal unfolding of proteins

Thermal unfolding of proteins is compared to folding and mechanical stretching in a simple topology-based dynamical model. We define the unfolding time and demonstrate its low-temperature divergence. Below a characteristic temperature, contacts break at separate time scales and unfolding proceeds approximately in a way reverse to folding. Features in these scenarios agree with experiments and atomic simulations on titin.

Simulations of multi-directional forced unfolding of titin I27

Mechanical resistance of a protein under external force is known to depend on the amino acid sequence, unfolding rate constant, topology and the direction of force applied. To assess the affect of force direction on mechanical resistance, molecular dynamics (MD) simulations of the partial unfolding of titin I27 have been carried out by applying a ramp of force between the N-terminus and the alpha-carbon of each amino acid, respectively. The results arbitrarily place the amino acids in a hierarchy in terms of the time at which an unfolding intermediate is formed. The onset of unfolding is indeed affected by force direction; directions that give maximum leverage (for the A strand to detach) unfold to the intermediate quicker than directions that give least leverage. Moreover, the change in the time taken to reach the intermediate, hence the change in mechanical resistance, can be attributed to beta-strand topology. The simulations indicate that experimentally multi-directional forced unfolding could be used to reveal and study strand topology, and suggests that direction of applied force, topology and mechanical resistance are all closely related.

Mechanical resistance of proteins explained using simple molecular models

Recent experiments have demonstrated that proteins unfold when two atoms are mechanically pulled apart, and that this process is different to when heated or when a chemical denaturant is added to the solution. Experiments have also shown that the response of proteins to external forces is very diverse, some of them being "hard," and others "soft." Mechanical resistance originates from the presence of barriers on the energy landscape; together, experiment and simulation have demonstrated that unfolding occurs through alternative pathways when different pairs of atoms undergo mechanical extension. Here we use simulation to probe the mechanical resistance of six structurally diverse proteins when pulled in different directions. For this, we use two very different models: a detailed, transferable one, and a coarse-grained, structure-based one. The coarse-grained model gives results that are surprisingly similar to the detailed one and qualitatively agree with experiment; i.e., the mechanical resistance of different proteins or of a single protein pulled in different directions can be predicted by simulation. The results demonstrate the importance of pulling direction relative to the local topology in determining mechanical stability, and rationalize the effect of the location of importation/degradation tags on the rates of mitochondrial import or protein degradation in vivo.

Structure and stability of a model three-helix-bundle protein on tailored surfaces

The interaction of protein molecules with surfaces is important in numerous applications. Theoretical work on protein adsorption has been limited. In particular, it is difficult to obtain quantitative predictions about the structure and stability of proteins on surfaces. In this study, density-of-states-based simulations were performed on a Gō-like model of a three-helix-bundle fragment from protein A (PDB ID: 1bdd). Both mechanical and thermal stability were investigated on neutral and attractive surfaces and compared to that in the absence of a surface. It was found that attaching the peptide to any type of surface decreases its melting temperature by as much as 9 K, depending upon orientation. Calorimetric cooperativity, as measured by van't Hoff to calorimetric enthalpy ratios, similarly decreased. It was also found that the mechanical strength of the peptide attached to surfaces is degraded to varying extents, depending upon the surface type and protein orientation. A comparison of mechanical and thermal stability showed that the two are not synonymous, but occur through different pathways, and that system configurations that are more thermally stable are not always so mechanically.

Inferring the diameter of a biopolymer from its stretching response

We investigate the stretching response of a thick polymer model by means of extensive stochastic simulations. The computational results are synthesized in an analytic expression that characterizes how the force versus elongation curve depends on the polymer structural parameters: its thickness and granularity (spacing of the monomers). The expression is used to analyze experimental data for the stretching of various different types of biopolymers: polypeptides, polysaccharides, and nucleic acids. Besides recovering elastic parameters (such as the persistence length) that are consistent with those obtained from standard entropic models, the approach allows us to extract viable estimates for the polymers diameter and granularity. This shows that the basic structural polymer features have such a profound impact on the elastic behavior that they can be recovered with the sole input of stretching measurements.

Theoretical studies of the kinetics of mechanical unfolding of cross-linked polymer chains and their implications for single-molecule pulling experiments

We have used kinetic Monte Carlo simulations to study the kinetics of unfolding of cross-linked polymer chains under mechanical loading. As the ends of a chain are pulled apart, the force transmitted by each cross-link increases until it ruptures. The stochastic cross-link rupture process is assumed to be governed by first order kinetics with a rate that depends exponentially on the transmitted force. We have performed random searches to identify optimal cross-link configurations whose unfolding requires a large applied force (measure of strength) and/or large dissipated energy (measure of toughness). We found that such optimal chains always involve cross-links arranged to form parallel strands. The location of those optimal strands generally depends on the loading rate. Optimal chains with a small number of cross-links were found to be almost as strong and tough as optimal chains with a large number of cross-links. Furthermore, optimality of chains with a small number of cross-links can be easily destroyed by adding cross-links at random. The present findings are relevant for the interpretation of single molecule force probe spectroscopy studies of the mechanical unfolding of "load-bearing" proteins, whose native topology often involves parallel strand arrangements similar to the optimal configurations identified in the study.

Stretching of homopolymers and contact order

Mechanical stretching of self-interacting homopolymers is studied through molecular dynamics simulations in which the polymers are pulled with constant speed. At temperatures below the compactification temperature, the force-extension curves show a plateau that corresponds to the situation in which the polymer adopts "ball-string" configurations. The dependence of rupture distances on contact order and the effects of temperature are similar to those found in the case of model proteins. The dependence of behavior on the pulling speed is logarithmic. In the entropic limit, above the compactification temperature, the rupturing of contacts shows a monotonic decrease of extension with the contact order. The attainment of this limit depends on the system size and the pulling speed.

Thermal effects in stretching of Go-like models of titin and secondary structures

The effect of temperature on mechanical unfolding of proteins is studied using a Go-like model with a realistic contact map and Lennard-Jones contact interactions. The behavior of the I27 domain of titin and its serial repeats is contrasted to that of simple secondary structures. In all cases, thermal fluctuations accelerate the unraveling process, decreasing the unfolding force nearly linearly at low temperatures. However, differences in bonding geometry lead to different sensitivity to temperature and different changes in the unfolding pattern. Due to its special native-state geometry, titin is much more thermally and elastically stable than the secondary structures. At low temperatures, serial repeats of titin show a parallel unfolding of all domains to an intermediate state, followed by serial unfolding of the domains. At high temperatures, all domains unfold simultaneously, and the unfolding distance decreases monotonically with the contact order, that is, the sequence distance between the amino acids that form the native contact.

Stretching of a polymer below the theta point

The unfolding of a polymer below the theta point when pulled by an external force is studied both in d=2 on the lattice and in d=3 off the lattice. At T=0 and for finite length chains, it is found that the globule unfolds via multiple steps, corresponding to transitions between different minima, in both cases. In d=3 one of these intermediates is a regular helix. In the infinite length limit, these steps have a qualitative effect only in d=2. The phase diagram in d=2 is determined via the transfer matrix. To rationalize these results, energy-entropy and renormalization group arguments are given.

Universality classes in folding times of proteins

Molecular dynamics simulations in simplified models allow one to study the scaling properties of folding times for many proteins together under a controlled setting. We consider three variants of the Go models with different contact potentials and demonstrate scaling described by power laws and no correlation with the relative contact order parameter. We demonstrate existence of at least three kinetic universality classes that are correlated with the types of structure: the alpha-, alpha-beta-, and beta- proteins have the scaling exponents of approximately 1.7, 2.5, and 3.2, respectively. The three classes merge into one when the contact range is truncated at a reasonable value. We elucidate the role of the potential associated with the chirality of a protein.