模拟蛋白质折叠过程的新算法研究

蛋白质折叠过程模拟是当前蛋白质研究领域的一个难点问题。针对这一问题,提出了一个描述蛋白质折叠过程的算法-拟蛇算法,并且从分子振荡和分子动力学理论两个方面来证明该算法的核心函数是可行和正确的。经过实验总结出所有蛋白质空间结构都可以通过两种类型函数构造出来,提出了描述蛋白质折叠过程模型。与其它蛋白质折叠过程模拟算法的实验结果比较表明,拟蛇算法所构造的空间结构能量值最小、相似度最好。进而说明拟蛇算法和蛋白质折叠过程模型在描述蛋白质折叠过程方面具有明显优势。     

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.     

Prediction of the initial folding sites and the entire folding processes for Ig-like beta-sandwich proteins

Describing the whole story of protein folding is currently the main enigmatic problem in molecular bioinformatics study. Protein folding mechanisms have been intensively investigated with experimental as well as simulation techniques. Since a protein folds into its specific 3D structure from a unique amino acid sequence, it is interesting to extract as much information as possible from the amino acid sequence of a protein. Analyses based on inter-residue average distance statistics and a coarse-grained Gō-model simulation were conducted on Ig and FN3 domains of a titin protein to decode the folding mechanisms from their sequence data and native structure data, respectively. The central region of all domains was predicted to be an initial folding unit, that is, stable in an early state of folding. This common feature coincides well with the experimental results and underscores the significance of the β-sandwich proteins' common structure, namely, the key strands for folding and the Greek-key motif, which is located in the central region. We confirmed that our sequence-based techniques were able to predict the initial folding event just next to the denatured state and that a 3D-based Gō-model simulation can be used to investigate the whole process of protein folding.     

Lattice simulations of aggregation funnels for protein folding.

A computer model of protein aggregation competing with productive folding is proposed. Our model adapts techniques from lattice Monte Carlo studies of protein folding to the problem of aggregation. However, rather than starting with a single string of residues, we allow independently folding strings to undergo collisions and consider their interactions in different orientations. We first present some background into the nature and significance of protein aggregation and the use of lattice Monte Carlo simulations in understanding other aspects of protein folding. The results of a series of simulation experiments involving simple versions of the model illustrate the importance of considering aggregation in simulations of protein folding and provide some preliminary understanding of the characteristics of the model. Finally, we discuss the value of the model in general and of our particular design decisions and experiments. We conclude that computer simulation techniques developed to study protein folding can provide insights into protein aggregation, and that a better understanding of aggregation may in turn provide new insights into and constraints on the more general protein folding problem.     

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.     

Rattling the cage: computational models of chaperonin-mediated protein folding

Chaperonins are known to maintain the stability of the proteome by facilitating the productive folding of numerous misfolded or aggregation-prone proteins and are thus essential for cell viability. Despite their established importance, the mechanism by which chaperonins facilitate protein folding remains unknown. Computer simulation techniques are now being employed to complement experimental ones in order to shed light on this mystery. Here we review previous computational models of chaperonin-mediated protein folding in the context of the two main hypotheses for chaperonin function: iterative annealing and landscape modulation. We then discuss new results pointing to the importance of solvent (a previously neglected factor) in chaperonin activity. We conclude with our views on the future role of simulation in studying chaperonin activity as well as protein folding in other biologically relevant confined contexts.     

An analysis of protein folding pathways

We have developed a model of the protein folding process based on three primary assumptions: that burying of hydrophobic area is the dominant contribution to the relative free energy of a conformation, that a record of the folding process is largely preserved in the final structure, and that the denatured state is a random coil. Detailed folding pathways are identified for 19 protein structures. The picture of the folding process that emerges from this analysis is one of nucleation by regions of 8-16 residues. Nucleation sites then lead to larger structures by two mechanisms: propagation and diffusion/collision. A Monte Carlo simulation is used to follow the folding pathway when propagation is the dominant mechanism. Because detailed pathways are derived for each protein, the models are susceptible to experimental verification.     

Combining experiment and simulation in protein folding: closing the gap for small model systems

All-atom molecular dynamics (MD) simulations on increasingly powerful computers have been combined with experiments to characterize protein folding in detail over wider time ranges. The folding of small ultrafast folding proteins is being simulated on micros timescales, leading to improved structural predictions and folding rates. To what extent is 'closing the gap' between simulation and experiment for such systems providing insights into general mechanisms of protein folding?     

Methods for molecular dynamics simulations of protein folding/unfolding in solution

All atom molecular dynamics simulations have become a standard method for mapping equilibrium protein dynamics and non-equilibrium events like folding and unfolding. Here, we present detailed methods for performing such simulations. Generic protocols for minimization, solvation, simulation, and analysis derived from previous studies are also presented. As a measure of validation, our water model is compared with experiment. An example of current applications of these methods, simulations of the ultrafast folding protein Engrailed Homeodomain are presented including the experimental evidence used to verify their results. Ultrafast folders are an invaluable tool for studying protein behavior as folding and unfolding events measured by experiment occur on timescales accessible with the high-resolution molecular dynamics methods we describe. Finally, to demonstrate the prospect of these methods for folding proteins, a temperature quench simulation of a thermal unfolding intermediate of the Engrailed Homeodomain is described.     

Refined models for computer simulation of protein folding. Applications to the study of conserved secondary structure and flexible hinge points during the folding of pancreatic trypsin inhibitor

A new model and parameters are proposed for the computer simulation of protein folding, which satisfy requirements for a fully automatic simulation as discussed in recent critical reviews.The parameters were obtained, refined or checked by empirical observations on proteins of known sequence and conformation, in order to avoid as much as possible theoretical deductions about the nature of the interactions between groups in proteins, which may not be justified by the current status of the art.The major improvement over previous methods is to retain a more realistic and complete representation of the protein backbone, and to alternatively reduce the number of variables by coupling their behaviour. As an example, the method is applied to simulate the folding of pancreatic trypsin inhibitor, and leads to a root-mean-square fit of 6·0 Å with good secondary structure.This also allows a more detailed examination of secondary structure transitions during protein folding than has been possible hitherto. Although, in the simulation discussed most extensively, the advantage of initial statistical predictions is demonstrated, the secondary structure was free to change in the simulation. A simulation from an extended chain is also described, and refinements tested.By observing changes in secondary structure during the simulated folding, it is shown that α-helices and extended chain regions predicted at the outset, or formed early in the simulation, are conserved, and that certain residues are crucial as flexible hinge-points to bring the secondary structure together in order to achieve tertiary packing.In view of recent debate about the importance of glycyl residues as hinge-points, and the danger of imparting glycyl-like backbone behaviour to non-glycyl residues suspected to be hinge-points, it is of considerable interest that the hinge-point residues identified by us are not, in general, glycyl residues. This makes an important distinction between a “reverse turn region”, for which glycine is statistically a strong candidate, and a hinge-point in the protein backbone. It is discussed that reverse turns are locally determined and likely to be fairly stable during the folding process, while hinge-points are determined by tertiary interactions. This distinction, implicit in most papers concerned with statistical methods of secondary structure prediction, has not been made clearly in recent reports of folding simulations.     

基于HP模型的蛋白质折叠问题的研究

基于蛋白质二维HP模型提出改进的遗传算法对真实蛋白质进行计算机折叠模拟。结果显示疏水能量函数最小值的蛋白质构象对应含疏水核心的稳定结构,疏水作用在蛋白质折叠中起主要作用。研究表明二维HP模型在蛋白质折叠研究中是可行的和有效的并为进一步揭示蛋白质折叠机理提供重要参考信息。     

Protein folding: the free energy surface

Quantitative models and experiments are revealing how the folding free energy surface of a protein is sculpted by sequence and environment. The sometimes conflicting demands of folding, structure and function determine which folding pathways, if any, dominate. Recent advances include experimental estimates of diffusive barrier-crossing times, the observation of ultrafast folders amenable to full-atom simulation, the use of thermodynamic tuning and nonconservative mutations to probe 'hidden' parts of the free energy surface, and a complete microscopic theory of folding.     

Ultrafast and downhill protein folding

Ultrafast folding proteins have served an important role in benchmarking molecular dynamics simulations and testing protein folding theories. These proteins are simple enough and fold fast enough that realistic simulations are possible, which facilitates the direct comparison of absolute folding rates and folding mechanisms with those observed experimentally. Such comparisons have achieved remarkable success, but have also revealed the shortcomings that remain in experiment, theory and simulation alike. Some ultrafast folding proteins may fold without encountering an activation barrier (downhill folding), allowing the exploration of the molecular timescale of folding and the roughness of the energy landscape. The biological significance of ultrafast folding remains uncertain, but its practical significance is crucial to progress in understanding how proteins fold.     

Molecular simulations of cotranslational protein folding: fragment stabilities, folding cooperativity, and trapping in the ribosome

Although molecular simulation methods have yielded valuable insights into mechanistic aspects of protein refolding in vitro, they have up to now not been used to model the folding of proteins as they are actually synthesized by the ribosome. To address this issue, we report here simulation studies of three model proteins: chymotrypsin inhibitor 2 (CI2), barnase, and Semliki forest virus protein (SFVP), and directly compare their folding during ribosome-mediated synthesis with their refolding from random, denatured conformations. To calibrate the methodology, simulations are first compared with in vitro data on the folding stabilities of N-terminal fragments of CI2 and barnase; the simulations reproduce the fact that both the stability and thermal folding cooperativity increase as fragments increase in length. Coupled simulations of synthesis and folding for the same two proteins are then described, showing that both fold essentially post-translationally, with mechanisms effectively identical to those for refolding. In both cases, confinement of the nascent polypeptide chain within the ribosome tunnel does not appear to promote significant formation of native structure during synthesis; there are however clear indications that the formation of structure within the nascent chain is sensitive to location within the ribosome tunnel, being subject to both gain and loss as the chain lengthens. Interestingly, simulations in which CI2 is artificially stabilized show a pronounced tendency to become trapped within the tunnel in partially folded conformations: non-cooperative folding, therefore, appears in the simulations to exert a detrimental effect on the rate at which fully folded conformations are formed. Finally, simulations of the two-domain protease module of SFVP, which experimentally folds cotranslationally, indicate that for multi-domain proteins, ribosome-mediated folding may follow different pathways from those taken during refolding. Taken together, these studies provide a first step toward developing more realistic methods for simulating protein folding as it occurs in vivo.     

A spatio-temporal mining approach towards summarizing and analyzing protein folding trajectories

Understanding the protein folding mechanism remains a grand challenge in structural biology. In the past several years, computational theories in molecular dynamics have been employed to shed light on the folding process. Coupled with high computing power and large scale storage, researchers now can computationally simulate the protein folding process in atomistic details at femtosecond temporal resolution. Such simulation often produces a large number of folding trajectories, each consisting of a series of 3D conformations of the protein under study. As a result, effectively managing and analyzing such trajectories is becoming increasingly important.     

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.     

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.     

Kinetics analysis methods for approximate folding landscapes

MOTIVATION: Protein motions play an essential role in many biochemical processes. Lab studies often quantify these motions in terms of their kinetics such as the speed at which a protein folds or the population of certain interesting states like the native state. Kinetic metrics give quantifiable measurements of the folding process that can be compared across a group of proteins such as a wild-type protein and its mutants. RESULTS: We present two new techniques, map-based master equation solution and map-based Monte Carlo simulation, to study protein kinetics through folding rates and population kinetics from approximate folding landscapes, models called maps. From these two new techniques, interesting metrics that describe the folding process, such as reaction coordinates, can also be studied. In this article we focus on two metrics, formation of helices and structure formation around tryptophan residues. These two metrics are often studied in the lab through circular dichroism (CD) spectra analysis and tryptophan fluorescence experiments, respectively. The approximated landscape models we use here are the maps of protein conformations and their associated transitions that we have presented and validated previously. In contrast to other methods such as the traditional master equation and Monte Carlo simulation, our techniques are both fast and can easily be computed for full-length detailed protein models. We validate our map-based kinetics techniques by comparing folding rates to known experimental results. We also look in depth at the population kinetics, helix formation and structure near tryptophan residues for a variety of proteins. AVAILABILITY: We invite the community to help us enrich our publicly available database of motions and kinetics analysis by submitting to our server: http://parasol.tamu.edu/foldingserver/.