Probing the sequence of conformationally induced polarity changes in the molecular chaperonin GroEL with fluorescence spectroscopy

Hydrophobic interactions play a major role in binding non-native substrate proteins in the central cavity of the bacterial chaperonin GroEL. The sequence of local conformational changes by which GroEL and its cofactor GroES assist protein folding can be explored using the polarity-sensitive fluorescence probe Nile Red. A specific single-cysteine mutant of GroEL (Cys261), whose cysteine is located inside the central cavity at the apical region of the protein, was covalently labeled with synthetically prepared Nile Red maleimide (NR). Bulk fluorescence spectra of Cys261-NR were measured to examine the effects of binding of the stringent substrate, malate dehydrogenase (MDH), GroES, and nucleotide on the local environment of the probe. After binding denatured substrate, the fluorescence intensity increased by 32 +/- 7%, suggesting enhanced hydrophobicity at the position of the label. On the other hand, in the presence of ATP, the fluorescence intensity decreased by 13 +/- 3%, implying increased local polarity. To explore the sequence of local polarity changes, substrate, GroES, and various nucleotides were added in different orders; the resulting changes in emission intensity provide insight into the sequence of conformational changes occurring during GroEL-mediated protein folding.     

Protein Folding: A Perspective from Theory and Experiment

The mechanism of protein folding (represented schematically below) is one of the most fascinating problems in the field of chemical reactions. This review presents the progess made recently in understanding key elements of this reaction and describes a solution to the often quoted Levinthal Paradox.     

全新设计蛋白质的折叠机制

蛋白质全新设计和折叠研究是从两个不同的方向来理解蛋白质序列-结构-功能关系这一结构生物学重要问题. 蛋白质全新设计取得的成功实例一定程度上检验了人们对蛋白质结构和相互作用理解的准确性, 但它们中多数所表现的不同于天然蛋白质的折叠动力学特征也表明, 要达到最终的功能化实现目标还面临着不少的挑战. 本文综述了蛋白质全新设计的发展过程及现状, 蛋白质折叠研究在实验、理论及模拟方面的研究进展, 以及全新设计蛋白质的折叠机制的研究现状. 阐述了深入了解全新设计蛋白质与天然蛋白质折叠机制的不同, 可以为进一步有效地合理化设计蛋白质提供有益的参考.     

模型多肽Trp-Cage折叠形成机制的研究进展

蛋白质折叠是目前结构生物学领域的核心问题之一, 理解蛋白质结构折叠机制及其与生物功能之间的相互关系一直是生命科学家非常重要的研究内容, 并且该研究受到越来越多不同学科领域研究工作者的高度重视. 蛋白质大多数在数十毫秒、微秒或几秒内完成自我折叠过程, 但其折叠过程中所发生的分子结构精细转变却在纳秒甚至更短时间尺度内完成. 由于其折叠时间分辨率的限制, 目前无论是从常规实验还是理论计算角度对其研究都存在一定的难度. 本文首先概述了蛋白质折叠研究在实验和理论模拟方面存在的一些问题,然后以结构典型且可快速折叠的人工设计多肽Trp-cage为例,主要对其折叠过渡温度、折叠形成模型及其肽链上关键氨基酸残基在折叠过程中的作用三个方面进行了详细讨论, 综述了模型多肽Trp-cage的折叠动力学行为分别在实验和理论模拟方面的研究进展. 最后就如何有效化解蛋白质残基间相互作用网络进而降低其折叠机制的复杂性提出了一些新的建议, 不仅有助于阐明该迷你蛋白Trp-cage快速折叠、稳定形成的驱动力成因, 而且也能为蛋白质折叠机制研究和多肽设计提供有益参考.     

Fluorescent Probes and Quenchers in Studies of Protein Folding and Protein-Lipid Interactions

Fluorescence spectroscopy provides numerous methodological tools for structural and functional studies of biological macromolecules and their complexes. All fluorescence-based approaches require either existence of an intrinsic probe or an introduction of an extrinsic one. Moreover, studies of complex systems often require an additional introduction of a specific quencher molecule acting in combination with a fluorophore to provide structural or thermodynamic information. Here, we review the fundamentals and summarize the latest progress in applications of different classes of fluorescent probes and their specific quenchers, aimed at studies of protein folding and protein-membrane interactions. Specifically, we discuss various environment-sensitive dyes, FRET probes, probes for short-distance measurements, and several probe-quencher pairs for studies of membrane penetration of proteins and peptides. The goals of this review are: (a) to familiarize the readership with the general concept that complex biological systems often require both a probe and a quencher to decipher mechanistic details of functioning and (b) to provide example of the immediate applications of the described methods.     

From interactions of single transmembrane helices to folding of alpha-helical membrane proteins: analyzing transmembrane helix-helix interactions in bacteria

Despite a wide variety of biological functions, alpha-helical membrane proteins display a rather simple transmembrane architecture. Although not many high resolution structures of transmembrane proteins are available today, our understanding of membrane protein folding has emerged in the recent years. Now we begin to develop a basic understanding of the forces that guide folding and interaction of alpha-helical membrane proteins. Some structural requirements for transmembrane helix interactions are defined, and common motifs have been discovered in the recent years which can drive helix-helix interactions. Nevertheless, many open questions remain to be addressed in future studies. One general problem with investigating transmembrane helix interactions is the limited number of appropriate tools, which can be applied to investigate membrane protein folding. Only recently several new techniques have been developed and established, including genetic systems, which allow measuring transmembrane helix interactions in vitro and in vivo. In the first part of this review, we summarize several aspects of the current understanding of membrane protein folding and assembly. In the second part, we discuss genetic systems, which were developed in the recent years to measure interaction of transmembrane helices in the inner membrane of E. coli.     

Prediction of protein folding rates from primary sequences using hybrid sequence representation

The ability to predict protein folding rates constitutes an important step in understanding the overall folding mechanisms. Although many of the prediction methods are structure based, successful predictions can also be obtained from the sequence. We developed a novel method called prediction of protein folding rates (PPFR), for the prediction of protein folding rates from protein sequences. PPFR implements a linear regression model for each of the mainstream folding dynamics including two-, multi-, and mixed-state proteins. The proposed method provides predictions characterized by strong correlations with the experimental folding rates, which equal 0.87 for the two- and multistate proteins and 0.82 for the mixed-state proteins, when evaluated with out-of-sample jackknife test. Based on in-sample and out-of-sample tests, the PPFR's predictions are shown to be better than most of other sequence only and structure-based predictors and complementary to the predictions of the most recent sequence-based QRSM method. We show that simultaneous incorporation of several characteristics, including the sequence, physiochemical properties of residues, and predicted secondary structure provides improved quality. This hybridized prediction model was analyzed to reveal the complementary factors that can be used in tandem to predict folding rates. We show that bigger proteins require more time for folding, higher helical and coil content and the presence of Phe, Asn, and Gln may accelerate the folding process, the inclusion of Ile, Val, Thr, and Ser may slow down the folding process, and for the two-state proteins increased beta-strand content may decelerate the folding process. Finally, PPFR provides strong correlation when predicting sequences with low similarity.     

Alpha-helix and beta-hairpin Folding from experiment,analytical theory and molecular dynamics simulations

The alpha-helix and beta-hairpin are the minimal secondary structure elements of proteins. Identification of the factors governing the formation of these structures independently of the rest of the protein is important for understanding the determinants and rules driving the folding process to a unique native structure. It has been shown that some alpha-helices and beta-hairpins can fold autonomously into native-like structures, either in aqueous solution or in the presence of an organic co-solvent; possible mechanisms of these processes have been considered in literature. The characteristic times for folding of alpha and beta structures are estimated from experiments, simple analytical theories and more detailed computer models. Our aim is to review recent experimental and theoretical studies of folding of alpha and beta structures focusing much attention on beta-hairpins.     

Putting a lid on protein folding: structure and function of the co-chaperonin,GroES

The co-chaperonin GroES is an essential partner in protein folding mediated by the chaperonin, GroEL. Two recent crystal structures of GroES provide a structural basis to understand how GroES forms the lid on the folding-active cis ternary complex, and how the GroEL-GroES complex enhances folding.     

Robustness of atomistic Gō models in predicting native-like folding intermediates

Go? models are exceedingly popular tools in computer simulations of protein folding. These models are native-centric, i.e., they are directly constructed from the protein's native structure. Therefore, it is important to understand up to which extent the atomistic details of the native structure dictate the folding behavior exhibited by Go? models. Here we address this challenge by performing exhaustive discrete molecular dynamics simulations of a Go? potential combined with a full atomistic protein representation. In particular, we investigate the robustness of this particular type of Go? models in predicting the existence of intermediate states in protein folding. We focus on the N47G mutational form of the Spc-SH3 folding domain (x-ray structure) and compare its folding pathway with that of alternative native structures produced in silico. Our methodological strategy comprises equilibrium folding simulations, structural clustering, and principal component analysis.     

Protein Folding and β‐Sheet Proteins

The aim of this comprehensive review is to critically evaluate the progress in research in the area of protein folding. In the first section, we discuss the various models proposed to explain the protein folding paradox. In the succeeding section of the review, a detailed account of the developments in our understanding of the folding path ways of β‐sheet proteins is provided.     

Slow Unfolded-State Structuring in Acyl-CoA Binding Protein Folding Revealed by Simulation and Experiment

Protein folding is a fundamental process in biology, key to understanding many human diseases. Experimentally, proteins often appear to fold via simple two- or three-state mechanisms involving mainly native-state interactions, yet recent network models built from atomistic simulations of small proteins suggest the existence of many possible metastable states and folding pathways. We reconcile these two pictures in a combined experimental and simulation study of acyl-coenzyme A binding protein (ACBP), a two-state folder (folding time ～10 ms) exhibiting residual unfolded-state structure, and a putative early folding intermediate. Using single-molecule FRET in conjunction with side-chain mutagenesis, we first demonstrate that the denatured state of ACBP at near-zero denaturant is unusually compact and enriched in long-range structure that can be perturbed by discrete hydrophobic core mutations. We then employ ultrafast laminar-flow mixing experiments to study the folding kinetics of ACBP on the microsecond time scale. These studies, along with Trp-Cys quenching measurements of unfolded-state dynamics, suggest that unfolded-state structure forms on a surprisingly slow (～100 μs) time scale, and that sequence mutations strikingly perturb both time-resolved and equilibrium smFRET measurements in a similar way. A Markov state model (MSM) of the ACBP folding reaction, constructed from over 30 ms of molecular dynamics trajectory data, predicts a complex network of metastable stables, residual unfolded-state structure, and kinetics consistent with experiment but no well-defined intermediate preceding the main folding barrier. Taken together, these experimental and simulation results suggest that the previously characterized fast kinetic phase is not due to formation of a barrier-limited intermediate but rather to a more heterogeneous and slow acquisition of unfolded-state structure.     

Photocontrol of peptide secondary structure through non-azobenzene photoswitches

The rapidly expanding field of photoswitchable biomolecules is a major frontier in scientific research and provides unparalleled opportunities for studying biological pathways and disease progression. In particular, the development of photochromic peptides has delivered both scientific tools and candidates for photopharmaceuticals. The action and function of the peptide can be remotely altered using light, allowing detection of its biological role in complex biological settings, while also enabling folding studies that provide greater understanding of protein structure dynamics. In this review we provide a key, comprehensive overview of the different types of photoswitches that have been used to control peptide structure, excluding the already extensively reviewed azobenzene. This will help address the question as to which synthetic photoswitch to use in a given study.     

Enzymes catalyzing protein folding and their cellular functions

In live cells, protein folding often cannot occur spontaneously, but requires the participation of helper proteins - molecular chaperones and foldases. The mechanisms employed by chaperones markedly increase the effectiveness of protein folding, but have no bearing on the rate of this process, whereas foldases actually accelerate protein folding by exerting a direct influence on the rate-limiting steps of the overall reaction. Two types of foldases are known, using different principles of action. Peptidyl-prolyl cis/trans isomerase and protein-disulfide isomerase catalyze the folding of every protein that needs isomerization of prolyl peptide bonds or formation and isomerization of disulfide bonds for proper folding. By contrast, some foldases operating in the periplasm of bacterial cells are specifically designed to help in the folding of substrate proteins whose primary structure does not contain sufficient information for correct folding. In this review, we discuss recent data on the catalytic mechanisms of both types of foldases, focusing specifically on how a catalyst provides the structural information required for the folding of a target protein. Comparative analysis of the mechanisms employed by two different periplasmic foldases is used to substantiate the notion that combinations of a protein which is unable to fold independently and a specific catalyst delivering the necessary steric information are probably designed to achieve some particular biological purposes. The review also covers the problem of participation of peptidyl-prolyl cis/trans isomerase in different cellular functions, highlighting the role of this enzyme in conformational rearrangements of folded native proteins.     

A role for confined water in chaperonin function

Chaperonins engulf other proteins and accelerate their folding by an unknown mechanism. Here, we combine all-atom molecular dynamics simulations with data from experimental assays of the activity of the bacterial chaperonin GroEL to demonstrate that a chaperonin's ability to facilitate folding is correlated with the affinity of its interior surface for water. Our results suggest a novel view of the behavior of confined water for models of in vivo protein folding scenarios.     

超氧负离子在生物发光中的作用

活性氧物种和超氧负离子是生物体内的重要物质,本文通过超氧负离子在生物发光反应中的作用,针对几种不同的典型生物发光体系,综述了超氧负离子参与发光反应的相关理论和实验研究进展.     

Estimation of protein folding rate from Monte Carlo simulations and entropy capacity

The problem of protein self-organization is one of the most important problems of molecular biology nowadays. Despite the recent success in the understanding of general principles of protein folding, details of this process are yet to be elucidated. Moreover, the prediction of protein folding rates has its own practical value due to the fact that aggregation directly depends on the rate of protein folding. The time of folding has been calculated for 67 proteins with known experimental data at the point of thermodynamic equilibrium between unfolded and native states using a Monte Carlo model where each residue is considered to be either folded as in the native state or completely disordered. The times of folding for 67 proteins which reach the native state within the limit of 10(8) Monte Carlo steps are in a good correlation with the experimentally measured folding rate at the mid-transition point (the correlation coefficient is -0.82). Theoretical consideration of a capillarity model for the process of protein folding demonstrates that the difference in the folding rate for proteins sharing more spherical and less spherical folds is the result of differences in the conformational entropy due to a larger surface of the boundary between folded and unfolded phases in the transition state for proteins with more spherical fold. The capillarity model allows us to predict the folding rate at the same level of correlation as by Monte Carlo simulations. The calculated model entropy capacity (conformational entropy per residue divided by the average contact energy per residue) for 67 proteins correlates by about 78% with the experimentally measured folding rate at the mid-transition point.     

Computational approaches for understanding and predicting the self-assembled peptide hydrogels

Self-assembled peptide hydrogel is a promising biomaterial and has been widely applied in many fields. As a typical self-assembly material, peptide hydrogel exhibits properties different from traditional polymer hydrogel, and has unique features in molecular design, structural elements of hydrogel, and control strategies. With the desire to apply the principles of self-assembly to the design and prediction of peptide hydrogels, there has more and more emphasis on understanding the driving forces and microscopic behaviors involved in the self-assembly process. Computational methods have played an increasingly important role in recent research in helping to reveal the relationship between molecular chemical structure and self-assembly processes as well as assembled morphologies, thus determining the ability of supramolecular gelation. This review aims to summarize the application of computational tools to obtain a better fundamental understanding of the multi-scale structural details of self-assembled peptide hydrogels and to predict the gelation behavior of supramolecular nanofibers. It is expected that researchers will consider using these computational tools when investigating and designing novel peptide hydrogel materials.     

二氧化碳电还原反应的理论研究

Converting CO₂ into value-added products via sustainable energy, such as electrical energy, has several advantages. First, it is one of the most promising routes to close the carbon loop and plays a crucial role in significantly reducing the CO₂ concentration in the atmosphere. Second, it can utilize CO₂ as a valuable industry reactant that can store energy by converting electrical energy to chemical energy. Although the CO₂ reduction reaction has been studied for more than three decades, the sluggish kinetics remain a bottleneck, which requires a highly efficient catalyst. However, none of the reported catalysts meets the requirements for any practical application due to low activity and poor selectivity. To rationally design a more efficient CO₂ reduction catalyst, understanding the reaction mechanism is crucial. Although it is challenging to experimentally capture and characterize the reactive intermediates, atomic modeling serves as an alternative for providing an understanding of the elementary reactions on a microscale. Significant progress has been made in understanding the reaction mechanism using multiscale simulations. In this study, important progress in revealing the reaction mechanism of CO₂ reduction using computational simulation in recent years is summarized. First, the advances in simulation methods for electrochemical reactions are introduced, and the advantages and disadvantages of various methods are compared. Second, the detailed reaction mechanism of CO₂ reduction to various major products, such as CO, CH₄, and C₂H₄, and minor products, such as ethanol and acetate, are disused. Different results obtained from different approximations are compared, while a mechanism that can better explain the existing experimental results is recommended. Third, the operando technique, such as ambient pressure X-ray photoelectron spectroscopy, is disused. The operando analysis results are direct evidence to validate the theoretically proposed reaction pathway. In turn, the theoretical predictions can help resolve the experimental spectrum, which is usually too complex to refer to a reference system. The combination of theory and operando experiments should be one of the most promising directions in determining the reaction mechanism. Fourth, novel synthesis strategies are discussed. These new ideas are beneficial for simplifying the synthesis process or increasing the diversity of products. Finally, the recent progress in the application of machine learning to big data for CO₂ reduction is discussed. These new powerful tools may play a crucial role in reaction mechanism studies. Overall, in the study of electrochemical reaction mechanism, theoretical simulation can provide the reaction details and energy information of elementary reactions at the atomic level. Therefore, in the study of electrochemical reaction mechanism of carbon dioxide, the microscopic mechanism that the experiment cannot provide is supplemented. On the one hand, it explains the existing experimental phenomena; however, on the other hand, it provides new insights for the study of reaction mechanism. On this basis, the use of new research paradigms, such as high-throughput computing and machine learning, provides new ideas for a rational design for accelerating material development.