Temperature-dependent folding pathways of Pin1 WW domain: an all-atom molecular dynamics simulation of a Gō model

We study the folding thermodynamics and kinetics of the Pin1 WW domain, a three-stranded beta-sheet protein, by using all-atom (except nonpolar hydrogens) discontinuous molecular dynamics simulations at various temperatures with a Gō model. The protein exhibits a two-state folding kinetics near the folding transition temperature. A good agreement between our simulations and the experimental measurements by the Gruebele group has been found, and the simulation sheds new insights into the structure of transition state, which is hard to be straightforwardly captured in experiments. The simulation also reveals that the folding pathways at approximately the transition temperature and at low temperatures are much different, and an intermediate state at a low temperature is predicted. The transition state of this small beta-protein at its folding transition temperature has a well-established hairpin 1 made of beta1 and beta2 strands while its low-temperature kinetic intermediate has a formed hairpin 2 composed of beta2 and beta3 strands. Theoretical results are compared with other simulation results as well as available experimental data. This study confirms that specific side-chain packing in an all-atom Gō model can yield a reasonable prediction of specific folding kinetics for a given protein. Different folding behaviors at different temperatures are interpreted in terms of the interplay of entropy and enthalpy in folding process.     

Water dynamics clue to key residues in protein folding

A computational method independent of experimental protein structure information is proposed to recognize key residues in protein folding, from the study of hydration water dynamics. Based on all-atom molecular dynamics simulation, two key residues are recognized with distinct water dynamical behavior in a folding process of the Trp-cage protein. The identified key residues are shown to play an essential role in both 3D structure and hydrophobic-induced collapse. With observations on hydration water dynamics around key residues, a dynamical pathway of folding can be interpreted.     

Study of the Villin headpiece folding dynamics by combining coarse-grained Monte Carlo evolution and all-atom molecular dynamics

The folding mechanism of the Villin headpiece (HP36) is studied by means of a novel approach which entails an initial coarse-grained Monte Carlo (MC) scheme followed by all-atom molecular dynamics (MD) simulations in explicit solvent. The MC evolution occurs in a simplified free-energy landscape and allows an efficient selection of marginally-compact structures which are taken as viable initial conformations for the MD. The coarse-grained MC structural representation is connected to the one with atomic resolution through a "fine-graining" reconstruction algorithm. This two-stage strategy is used to select and follow the dynamics of seven different unrelated conformations of HP36. In a notable case the MD trajectory rapidly evolves towards the folded state, yielding a typical root-mean-square deviation (RMSD) of the core region of only 2.4 A from the closest NMR model (the typical RMSD over the whole structure being 4.0 A). The analysis of the various MC-MD trajectories provides valuable insight into the details of the folding and mis-folding mechanisms and particularly about the delicate influence of local and nonlocal interactions in steering the folding process.     

Combining optimal control theory and molecular dynamics for protein folding

A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the Cα atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the Cα atoms. In turn, MD simulation provides an all-atom conformation whose Cα positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the Cα atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization-MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages.     

Piecewise All-Atom SMD Simulations Reveal Key Secondary Structures in Luciferase Unfolding Pathway

Although the folding of single-domain proteins is well characterized theoretically and experimentally, the folding of large multidomain proteins is less well known. Firefly luciferase, a 550 residue three-domain protein, has been commonly used as a substrate to study chaperone reactions and as a model system for the study of folding of long polypeptide chains, including related phenomena such as cotranslational folding. Despite being characterized by various experimental techniques, the atomic-level contributions of various secondary structures of luciferase to its fold’s mechanical stability remain unknown. Here, we developed a piecewise approach for all-atom steered molecular dynamics simulations to examine specific secondary structures that resist mechanical unfolding while minimizing the amount of computational resources required by the large water box of standard all-atom steered molecular dynamics simulations. We validated the robustness of this approach with a small NI3C protein and used our approach to elucidate the specific secondary structures that provide the largest contributions to luciferase mechanostability. In doing so, we show that piecewise all-atom steered molecular dynamics simulations can provide novel atomic resolution details regarding mechanostability and can serve as a platform for novel mutagenesis studies as well as a point for comparison with high-resolution force spectroscopy experiments.     

All-atom Monte Carlo simulation of GCAA RNA folding

We report a detailed all-atom simulation of the folding of the GCAA RNA tetraloop. The GCAA tetraloop motif is a very common and thermodynamically stable secondary structure in natural RNAs. We use our simulation methods to study the folding behavior of a 12-base GCAA tetraloop structure with a four-base helix adjacent to the tetraloop proper. We implement an all-atom Monte Carlo (MC) simulation of RNA structural dynamics using a Go potential. Molecular dynamics (MD) simulation of RNA and protein has realistic energetics and sterics, but is extremely expensive in terms of computational time. By coarsely treating non-covalent energetics, but retaining all-atom sterics and entropic effects, all-atom MC techniques are a useful method for the study of protein and now RNA. We observe a sharp folding transition for this structure, and in simulations at room temperature the state histogram shows three distinct minima: an unfolded state (U), a more narrow intermediated state (I), and a narrow folded state (F). The intermediate consists primarily of structures with the GCAA loop and some helix hydrogen bonds formed. Repeated kinetic folding simulations reveal that the number of helix base-pairs forms a simple 1D reaction coordinate for the I-->N transition.     

Low-mass molecular dynamics simulation: A simple and generic technique to enhance configurational sampling

CLN025 is one of the smallest fast-folding proteins. Until now it has not been reported that CLN025 can autonomously fold to its native conformation in a classical, all-atom, and isothermal–isobaric molecular dynamics (MD) simulation. This article reports the autonomous and repeated folding of CLN025 from a fully extended backbone conformation to its native conformation in explicit solvent in multiple 500-ns MD simulations at 277 K and 1 atm with the first folding event occurring as early as 66.1 ns. These simulations were accomplished by using AMBER forcefield derivatives with atomic masses reduced by 10-fold on Apple Mac Pros. By contrast, no folding event was observed when the simulations were repeated using the original AMBER forcefields of FF12SB and FF14SB. The results demonstrate that low-mass MD simulation is a simple and generic technique to enhance configurational sampling. This technique may propel autonomous folding of a wide range of miniature proteins in classical, all-atom, and isothermal–isobaric MD simulations performed on commodity computers—an important step forward in quantitative biology.     

The protein folding 'speed limit'

How fast can a protein possibly fold? This question has stimulated experimentalists to seek fast folding proteins and to engineer them to fold even faster. Proteins folding at or near the speed limit are prime candidates for all-atom molecular dynamics simulations. They may also have no free energy barrier, allowing the direct observation of intermediate structures on the pathways from the unfolded to the folded state. Both experimental and theoretical approaches predict a speed limit of approximately N/100micros for a generic N-residue single-domain protein, with alpha proteins folding faster than beta or alphabeta. The predicted limits suggest that most known ultrafast folding proteins can be engineered to fold more than ten times faster.     

The folding thermodynamics and kinetics of crambin using an all-atom Monte Carlo simulation

We present a novel Monte Carlo simulation of protein folding, in which all heavy atoms are represented as interacting hard spheres. This model includes all degrees of freedom relevant to folding, all side-chain and backbone torsions, and uses a Go potential. In this study, we focus on the 46 residue alpha/beta protein crambin and two of its structural components, the helix and helix hairpin. For a wide range of temperatures, we recorded multiple folding events of these three structures from random coils to native conformations that differ by less than 1 A C(alpha) dRMS from their crystal structure coordinates. The thermodynamics and kinetic mechanism of the helix-coil transition obtained from our simulation shows excellent agreement with currently available experimental and molecular dynamics data. Based on insights obtained from folding its smaller structural components, a possible folding mechanism for crambin is proposed. We observed that the folding occurs via a cooperative, first order-like process, and that many folding pathways to the native state exist. One particular sequence of events constitutes a "fast-folding" pathway where kinetic traps are avoided. At very low temperatures, a kinetic trap arising from the incorrect packing of side-chains was observed. These results demonstrate that folding to the native state can be observed in a reasonable amount of time on desktop computers even when an all-atom representation is used, provided the energetics sufficiently stabilize the native state.     

Studies of folding and misfolding using simplified models

Computer simulations are as vital to our studies of biological systems as experiments. They bridge and rationalize experimental observations, extend the experimental "field of view", which is often limited to a specific time or length scale, and, most importantly, provide novel insights into biological systems, offering hypotheses about yet-to-be uncovered phenomena. These hypotheses spur further experimental discoveries. Simplified molecular models have a special place in the field of computational biology. Branded as less accurate than all-atom protein models, they have offered what all-atom molecular dynamics simulations could not--the resolution of the length and time scales of biological phenomena. Not only have simplified models proven to be accurate in explaining or reproducing several biological phenomena, they have also offered a novel multiscale computational strategy for accessing a broad range of time and length scales upon integration with traditional all-atom simulations. Recent computer simulations of simplified models have shaken or advanced the established understanding of biological phenomena. It was demonstrated that simplified models can be as accurate as traditional molecular dynamics approaches in identifying native conformations of proteins. Their application to protein structure prediction yielded phenomenal accuracy in recapitulating native protein conformations. New studies that utilize the synergy of simplified protein models with all-atom models and experiments yielded novel insights into complex biological processes, such as protein folding, aggregation and the formation of large protein complexes.     

All-atom folding of the three-helix HIV accessory protein with an adaptive parallel tempering method

All-atom protein structure prediction from the amino acid sequence alone remains an important goal of biophysical chemistry. Recent progress in force field development and validation suggests that the PFF01 free-energy force field correctly predicts the native conformation of various helical proteins as the global optimum of its free-energy surface. Reproducible protein structure prediction requires the availability of efficient optimization methods to locate the global minima of such complex potentials. Here we investigate an adapted version of the parallel tempering method as an efficient parallel stochastic optimization method for protein structure prediction. Using this approach we report the reproducible all-atom folding of the three-helix 40 amino acid HIV accessory protein from random conformations to within 2.4 A backbone RMS deviation from the experimental structure with modest computational resources.     

Effect of deamidation on folding of ribonuclease A

The folding of ribonuclease A (RNase A) has been extensively studied by characterizing the disulfide containing intermediates using different experimental conditions and analytical techniques. So far, some aspects still remain unclear such as the role of the loop 65-72 in the folding pathway. We have studied the oxidative folding of a RNase A derivative containing at position 67 the substitution Asn --> isoAsp where the local structure of the loop 65-72 has been modified keeping intact the C65-C72 disulfide bond. By comparing the folding behavior of this mutant to that of the wild-type protein, we found that the deamidation significantly decreases the folding rate and alters the folding pathway of RNase A. Results presented here shed light on the role of the 65-72 region in the folding process of RNase A and also clarifies the effect of the deamidation on the folding/unfolding processes. On a more general ground, this study represents the first characterization of the intermediates produced along the folding of a deamidated protein.     

1H NMR and CD evidence of the folding of the isolated ribonuclease 50-61 fragment

In our search for potential folding intermediates we have prepared and characterized the fragment of RNase A corresponding to residues 50-61. Proton chemical shift variations with temperature, addition of stabilizing (TFE) or denaturing agents (urea) provide a strong experimental basis for concluding that in aqueous solution this RNase fragment forms an alpha-helix structure similar to that in the intact RNase A crystal. This conclusion lends strong support to the idea that elements of secondary structure (mainly alpha-helices) can be formed in the absence of tertiary interactions and act as nucleation centers in the protein folding process.     

Folding time predictions from all-atom replica exchange simulations

We present an approach to predicting the folding time distribution from all-atom replica exchange simulations. This is accomplished by approximating the multidimensional folding process as stochastic reaction-coordinate dynamics for which effective drift velocities and diffusion coefficients are determined from the short-time replica exchange simulations. Our approach is applied to the folding of the second beta-hairpin of the B domain of protein G. The folding time prediction agrees quite well with experimental measurements. Therefore, we have in hand a fast numerical tool for calculating the folding kinetic properties from all-atom "first-principles" models.     

Comparison of pathways from the geometric targeting method and targeted molecular dynamics in nitrogen regulatory protein C

Geometric targeting (GT) is a recently introduced method for rapidly generating all-atom pathways from one protein state to another, based on geometric rather than energetic considerations. To generate pathways, a bias is applied that gradually moves atoms toward a target structure, while a set of geometric constraints between atoms is enforced to keep the structure stereochemically acceptable. In this work, we compare conformational pathways generated from GT to pathways from the much more computationally intensive and commonly used targeted molecular dynamics (TMD) technique, for a complicated conformational change in the signaling protein nitrogen regulatory protein C. We show that the all-atom pathways from GT are similar to previously reported TMD pathways for this protein, by comparing motion along six progress variables that describe the various structural changes. The results suggest that for nitrogen regulatory protein C, finding an all-atom pathway is primarily a problem of geometry, and that a detailed force field in this case constitutes an unnecessary extra layer of detail. We also show that the pathway snapshots from GT have good structure quality, by measuring various structure quality metrics. Transient hydrogen bonds detected by the two methods show some similarities but also some differences. The results justify the usage of GT as a rapid, approximate alternative to TMD for generating stereochemically acceptable all-atom pathways in highly constrained protein systems.     

Accurate and efficient description of protein vibrational dynamics: comparing molecular dynamics and Gaussian models

Current all-atom potential based molecular dynamics (MD) allows the identification of a protein's functional motions on a wide-range of timescales, up to few tens of nanoseconds. However, functional, large-scale motions of proteins may occur on a timescale currently not accessible by all-atom potential based MD. To avoid the massive computational effort required by this approach, several simplified schemes have been introduced. One of the most satisfactory is the Gaussian network approach based on the energy expansion in terms of the deviation of the protein backbone from its native configuration. Here, we consider an extension of this model that captures in a more realistic way the distribution of native interactions due to the introduction of effective side-chain centroids. Since their location is entirely determined by the protein backbone, the model is amenable to the same exact and computationally efficient treatment as previous simpler models. The ability of the model to describe the correlated motion of protein residues in thermodynamic equilibrium is established through a series of successful comparisons with an extensive (14 ns) MD simulation based on the AMBER potential of HIV-1 protease in complex with a peptide substrate. Thus, the model presented here emerges as a powerful tool to provide preliminary, fast yet accurate characterizations of protein near-native motion.     

Refolding simulations of an isolated fragment of barnase into a native-like β hairpin: Evidence for compactness and hydrogen bonding as concurrent stabilizing factors

Experimental evidence and theoretical models both suggest that protein folding is initiated within specific fragments intermittently adopting conformations close to that found in the protein native structure. These folding initiation sites encompassing short portions of the protein are ideally suited for study in isolation by computational methods aimed at peering into the very early events of folding. We have used Molecular Dynamics (MD) technique to investigate the behavior of an isolated protein fragment formed by residues 85 to 102 of barnase that folds into a β hairpin in the protein native structure. Three independent MD simulations of 1.3 to 1.8 ns starting from unfolded conformations of the peptide portrayed with an all-atom model in water were carried out at gradually decreasing temperature. A detailed analysis of the conformational preferences adopted by this peptide in the course of the simulations is presented. Two of the unfolded peptide conformations fold into a hairpin characterized by native and a larger bulk of nonnative interactions. Both refolding simulations substantiate the close relationship between interstrand compactness and hydrogen bonding network involving backbone atoms. Persistent compactness witnessed by side-chain interactions always occurs concomitantly with the formation of backbone hydrogen bonds. No highly populated conformations generated in a third simulation starting from the remotest unfolded conformer relative to the native structure are observed. However, nonnative long-range and medium-range contacts with the aromatic moiety of Trp94 are spotted, which are in fair agreement with a former nuclear magnetic resonance study of a denaturing solution of an isolated barnase fragment encompassing the β hairpin. All this lends reason to believe that the 85–102 barnase fragment is a strong initiation site for folding. Proteins 29:212–227, 1997. © 1997 Wiley-Liss, Inc.     

Disulfide bonds and protein folding

The applications of disulfide-bond chemistry to studies of protein folding, structure, and stability are reviewed and illustrated with bovine pancreatic ribonuclease A (RNase A). After surveying the general properties and advantages of disulfide-bond studies, we illustrate the mechanism of reductive unfolding with RNase A, and discuss its application to probing structural fluctuations in folded proteins. The oxidative folding of RNase A is then described, focusing on the role of structure formation in the regeneration of the native disulfide bonds. The development of structure and conformational order in the disulfide intermediates during oxidative folding is characterized. Partially folded disulfide species are not observed, indicating that disulfide-coupled folding is highly cooperative. Contrary to the predictions of "rugged funnel" models of protein folding, misfolded disulfide species are also not observed despite the potentially stabilizing effect of many nonnative disulfide bonds. The mechanism of regenerating the native disulfide bonds suggests an analogous scenario for conformational folding. Finally, engineered covalent cross-links may be used to assay for the association of protein segments in the folding transition state, as illustrated with RNase A.     

Ab initio folding of proteins with all-atom discrete molecular dynamics

Discrete molecular dynamics (DMD) is a rapid sampling method used in protein folding and aggregation studies. Until now, DMD was used to perform simulations of simplified protein models in conjunction with structure-based force fields. Here, we develop an all-atom protein model and a transferable force field featuring packing, solvation, and environment-dependent hydrogen bond interactions. We performed folding simulations of six small proteins (20-60 residues) with distinct native structures by the replica exchange method. In all cases, native or near-native states were reached in simulations. For three small proteins, multiple folding transitions are observed, and the computationally characterized thermodynamics are in qualitative agreement with experiments. The predictive power of all-atom DMD highlights the importance of environment-dependent hydrogen bond interactions in modeling protein folding. The developed approach can be used for accurate and rapid sampling of conformational spaces of proteins and protein-protein complexes and applied to protein engineering and design of protein-protein interactions.