Configuration-dependent diffusion can shift the kinetic transition state and barrier height of protein folding

We show that diffusion can play an important role in protein-folding kinetics. We explicitly calculate the diffusion coefficient of protein folding in a lattice model. We found that diffusion typically is configuration- or reaction coordinate-dependent. The diffusion coefficient is found to be decreasing with respect to the progression of folding toward the native state, which is caused by the collapse to a compact state constraining the configurational space for exploration. The configuration- or position-dependent diffusion coefficient has a significant contribution to the kinetics in addition to the thermodynamic free-energy barrier. It effectively changes (increases in this case) the kinetic barrier height as well as the position of the corresponding transition state and therefore modifies the folding kinetic rates as well as the kinetic routes. The resulting folding time, by considering both kinetic diffusion and the thermodynamic folding free-energy profile, thus is slower than the estimation from the thermodynamic free-energy barrier with constant diffusion but is consistent with the results from kinetic simulations. The configuration- or coordinate-dependent diffusion is especially important with respect to fast folding, when there is a small or no free-energy barrier and kinetics is controlled by diffusion.Including the configurational dependence will challenge the transition state theory of protein folding.

The complex kinetics of protein folding in wide temperature ranges

The complex protein folding kinetics in wide temperature ranges is studied through diffusive dynamics on the underlying energy landscape. The well-known kinetic chevron rollover behavior is recovered from the mean first passage time, with the U-shape dependence on temperature. The fastest folding temperature T-0 is found to be smaller than the folding transition temperature T-f. We found that the fluctuations of the kinetics through the distribution of first passage time show rather universal behavior, from high-temperature exponential Poissonian kinetics to the relatively low-temperature highly nonexponential kinetics. The transition temperature is at T-k and T-0, T-k, T-f. In certain low-temperature regimes, a power law behavior at long time emerges. At very low temperatures ( lower than trapping transition temperature T< T-0/(4&SIM;6)), the kinetics is an exponential Poissonian process again.

Probing the kinetics of single molecule protein folding

We propose an approach to integrate the theory, simulations, and experiments in protein-folding kinetics. This is realized by measuring the mean and high-order moments of the first-passage time and its associated distribution. The full kinetics is revealed in the current theoretical framework through these measurements. In the experiments, information about the statistical properties of first-passage times can be obtained from the kinetic folding trajectories of single molecule experiments ( for example, fluorescence). Theoretical/simulation and experimental approaches can be directly related. We study in particular the temperature-varying kinetics to probe the underlying structure of the folding energy landscape. At high temperatures, exponential kinetics is observed; there are multiple parallel kinetic paths leading to the native state. At intermediate temperatures, nonexponential kinetics appears, revealing the nature of the distribution of local traps on the landscape and, as a result, discrete kinetic paths emerge. At very low temperatures, exponential kinetics is again observed; the dynamics on the underlying landscape is dominated by a single barrier.

First-passage time distribution and non-Markovian diffusion dynamics of protein folding

We study the kinetics of protein folding via statistical energy landscape theory. We concentrate on the local-connectivity case, where the configurational changes can only occur among neighboring states, with the folding progress described in terms of an order parameter given by the fraction of native conformations. The non-Markovian diffusion dynamics is analyzed in detail and an expression for the mean first-passage time (MFPT) from non-native unfolded states to native folded state is obtained. It was found that the MFPT has a V-shaped dependence on the temperature. We also find that the MFPT is shortened as one increases the gap between the energy of the native and average non-native folded states relative to the fluctuations of the energy landscape. The second- and higher-order moments are studied to infer the first-passage time distribution. At high temperature, the distribution becomes close to a Poisson distribution, while at low temperatures the distribution becomes a Levy-type distribution with power-law tails, indicating a nonself-averaging intermittent behavior of folding dynamics. We note the likely relevance of this result to single-molecule dynamics experiments, where a power law (Levy) distribution of the relaxation time of the underlined protein energy landscape is observed.

Diffusion dynamics, moments, and distribution of first-passage time on the protein-folding energy landscape, with applications to single molecules

We study the dynamics of protein folding via statistical energy-landscape theory. In particular, we concentrate on the local-connectivity case with the folding progress described by the fraction of native conformations. We found that the first passage-time (FPT) distribution undergoes a dynamic transition at a temperature below which the FPT distribution develops a power-law tail, a signature of the intermittent nonexponential kinetic phenomena for the folding dynamics. Possible applications to single-molecule dynamics experiments are discussed.

Cloning and expression of glucose regulated protein 78 (GRP78) in Fenneropenaeus chinensis

GRP78 (78 kDa glucose-regulated protein), also known as BiP (immunoglobulin heavy-chain-binding protein), is an essential regulator of endoplasmic reticulum (ER) homeostasis because of its multiple functions in protein folding, ER calcium binding, and controlling of the activation of transmembrane ER stress sensors. In this report, we cloned the full length cDNA of GRP78 (FcGRP78) from Chinese shrimp Fenneropenaeus chinensis. This cDNA revealed a 2,325 bp with 1,968 bp open reading frame encoding 655 amino acids. This is the first reported GRP78 gene in Crustacea. The deduced amino acid sequence of FcGRP78 shared high identity with previously reported insect GRP78s: 86, 87 and 85% identity with GRP78s of Drosophila melanogaster, Aedes aegypti and Bombyx mori, respectively. Northern blot analysis shows that FcGRP78 is ubiquitously expressed in tissues of shrimp. Heat shock at 35A degrees C significantly enhanced the expression of FcGRP78 at the first hour, reached the maximum at 4 h post heat shock, dropped after that and resumed to the normal level until 48 h of post recovery at 25A degrees C. Additionally, differential expression of FcGRP78 was detected in haemocytes, hepatopancreas and lymphoid organ when shrimp were challenged by white spot syndrome virus (WSSV). We inferred that FcGRP78 may play important roles in chaperoning, protein folding and immune function of shrimp.

Switch Region for Pathogenic Structural Change in Conformational Disease and Its Prediction

Many diseases are believed to be related to abnormal protein folding. In the first step of such pathogenic structural changes, misfolding occurs in regions important for the stability of the native structure. This destabilizes the normal protein conformation, while exposing the previously hidden aggregation-prone regions, leading to subsequent errors in the folding pathway. Sites involved in this first stage can be deemed switch regions of the protein, and can represent perfect binding targets for drugs to block the abnormal folding pathway and prevent pathogenic conformational changes. In this study, a prediction algorithm for the switch regions responsible for the start of pathogenic structural changes is introduced. With an accuracy of 94%, this algorithm can successfully find short segments covering sites significant in triggering conformational diseases (CDs) and is the first that can predict switch regions for various CDs. To illustrate its effectiveness in dealing with urgent public health problems, the reason of the increased pathogenicity of H5N1 influenza virus is analyzed; the mechanisms of the pandemic swine-origin 2009 A(H1N1) influenza virus in overcoming species barriers and in infecting large number of potential patients are also suggested. It is shown that the algorithm is a potential tool useful in the study of the pathology of CDs because: (1) it can identify the origin of pathogenic structural conversion with high sensitivity and specificity, and (2) it provides an ideal target for clinical treatment.

mRNA 很可能携带三维遗传信息

The forming mechanism of the three - dimensional structures of proteins，i.e.the mechanism of protein folding，is a basic problem in molecular biology which is still unsolved unitl now. In which a core problem is whether there is the three – dimensional genetic information that decide the three - dimensional structures of proteins. However, the research on this field has mot yet been reported. Recently，we made a comparative study on the folded structures of more than 70 mature messeneger RNAs (mRNAs) and the three - dimensional structures of the proteins encoded by them，it has been found that there exist marked correspondences between their featured structures in the following aspects: 1.The number of the structural units. An RNA molecule can form a secondary structure(stem and loop structure) by the folding and the base pairing of itself. The elementary structural unit of an RNA secondary structure is hairpin(or compound hair pin).The regular structural unit in the secondary structure of a protein is # alpha # - helix or #beta# - sheet . We have found that the hairpin number in the secondary structure of each mature mRNA is equal or approximately equal to the number of the regular secondary structural unis of the encoded protein. 2 .Turning region. Turn is a main structrual element in the secondary structure of a protein, which decides the backbone orientation of a protein molecule to some extent .Our analysis shows that the nucleotide sequence segments in an mRNA which encode the turns of the corresponding protein are overall situated in the turning regions of the mRNA secondary structure such as haipin，bulge loop or multibaranch loops. 3 .The arrangement of structural elements in space. In order to understand the backbone orientation of an RNA molecule and the arangement of its structural elements in space，we have modeled the three一dimensional structure of the mRNA molecule on SGI workstation based on its secondary structure.The result shows that the spatial arrangement of most of the nucleotide sequence segments encoding the structural elements of a protein is consistent with that of these stretural exements in the protein. For instance，the nucleotide sequences corresponding to each pleated sheet of a # beta # - sheet structure are close to each other in the mRNA secondary stucture and in the three - dimensional structure，although some of the nucleotide segments are far apart from each other in the one - dimensional sequence. For another instance，the two triplet codons of cysteines which form a disulphide bridge geneal1y are very close to each other in the mRNA folded structure. In addition，we also analyzed the locations of the codons proline - coding and the distrbution of the nucleotide sequences #alpha# - helix - coding in the folded structures of mRNAs . Some distribution laws have been found. All of these results suggest that the transfer of the genetic information from mRNA to protein not only is one – dimensional but also is three - dime ns ional. That is，there exists the genetic information that decide the three - dimensional structures of proteins. To a certain extent，we could say that the mRNA folding detemines the protein folding. Based on these results，it would be possible to predict the three - dimensional structures of proteins from the primary，secondary and tertiary structures of the m RNAs at a higher accuracy.And more important is that a new clue has been provided to uncover the“spatial coding" of the genetic information.

Downhill kinetics of biomolecular interface binding: Globally connected scenario

We study the kinetics of the biomolecular binding process at the interface using energy landscape theory. The global kinetic connectivity case is considered for a downhill funneled energy landscape. By solving the kinetic master equation, the kinetic time for binding is obtained and shown to have a U-shape curve-dependence on the temperature. The kinetic minimum of the binding time monotonically decreases when the ratio of the underlying energy gap between native state and average non-native states versus the roughness or the fluctuations of the landscape increases. At intermediate temperatures,fluctuations measured by the higher moments of the binding time lead to non-Poissonian, non-exponential kinetics. At both high and very low temperatures, the kinetics is nearly Poissonian and exponential.

Biophysical studies on the full-length human cyclin A(2): Protein stability and folding/unfolding thermodynamics

Human cyclin A(2) participates in cell cycle regulation, DNA replication, and transcription. Its overexpression has been implicated in the development and progression of a variety of human cancers. However, cyclin A(2) or its truncated form is very unstable in the absence of binding partner, which makes it difficult to get a deep insight of structural basis of the interactions. Therefore, biophysical studies of the full-length human cyclin A, would provide important information regarding protein stability and folding/unfolding process.

Single-molecule dynamics reveals cooperative binding-folding in protein recognition

The study of associations between two biomolecules is the key to understanding molecular function and recognition. Molecular function is often thought to be determined by underlying structures. Here, combining a single-molecule study of protein binding with an energy-landscape-inspired microscopic model, we found strong evidence that biomolecular recognition is determined by flexibilities in addition to structures. Our model is based on coarse-grained molecular dynamics on the residue level with the energy function biased toward the native binding structure ( the Go model). With our model, the underlying free-energy landscape of the binding can be explored. There are two distinct conformational states at the free-energy minimum, one with partial folding of CBD itself and significant interface binding of CBD to Cdc42, and the other with native folding of CBD itself and native interface binding of CBD to Cdc42. This shows that the binding process proceeds with a significant interface binding of CBD with Cdc42 first, without a complete folding of CBD itself, and that binding and folding are then coupled to reach the native binding state.

Generating artificial homologous proteins according to the representative family character in molecular mechanics properties - an attempt in validating an underlying rule of protein evolution

The molecular mechanics property is the foundation of many characters of proteins. Based on intramolecular hydrophobic force network, the representative family character underlying a protein’s mechanics property is described by a simple two-letter scheme. The tendency of a sequence to become a member of a protein family is scored according to this mathematical representation. Remote homologs of the WW-domain family could be easily designed using such a mechanistic signature of protein homology. Experimental validation showed that nearly all artificial homologs have the representative folding and bioactivity of their assigned family. Since the molecular mechanics property is the only consideration in this study, the results indicate its possible role in the generation of new members of a protein family during evolution.

The identification and quantification of highly stable 'common hairpin' in the dynamic process of co-transcriptional mRNA folding

In our studies, 88 human mRNA samples were collected from the Integrated Sequence-Structure database and then the dynamic process in co-transcriptional mRNA folding was simulated using the RNAstructure version 4.1 program. Through statistical analyses of the frequencies of occurrence of hairpins, a group of special folding structures-the 'common hairpins'-were identified. These 'common hairpins' have lower energies and occur in all the subsequent folding units that formed in the dynamic folding process. By applying the formulas (1)-(4) of the 'common hairpins' statistical model, 163 'common hairpins' were found, to make up about 7% of the total of 2286 hairpins. Classified studies further show that the 'common hairpins' that were studied may oscillate in the dynamic folding process. However, the hairpin loops of the 'common hairpins' and stems proximal to those 'common hairpins' loops maintain topologically stable structures, while other loops and stems distal to the 'common hairpins' loops are shown to be alterable structures. Strikingly, further studies indicate that the stable structures of these 'common hairpins' may have unbeknown effects on controlling the formation of protein structures in the translation process (unpublished results). (c) 2005 Elsevier B.V. All rights reserved.

Dominant kinetic paths on biomolecular binding-folding energy landscape

The identification of kinetic pathways is a central issue in understanding the nature of flexible binding. A new approach is proposed here to study the dynamics of this binding-folding process through the establishment of a path integral framework on the underlying energy landscape. The dominant kinetic paths of binding and folding can be determined and quantified. In this case, the corresponding kinetic paths of binding are shown to be intimately correlated with those of folding and the dynamics becomes quite cooperative. The kinetic time can be obtained through the contributions from the dominant paths and has a U-shape dependence on temperature.

Temperature dependence of the distribution of the first passage time: Results from discontinuous molecular dynamics simulations of an all-atom model of the second beta-hairpin fragment of protein G

More than 22 000 folding kinetic simulations were performed to study the temperature dependence of the distribution of first passage time (FPT) for the folding of an all-atom Go-like model of the second beta-hairpin fragment of protein G. We find that the mean FPT (MFPT) for folding has a U (or V)-shaped dependence on the temperature with a minimum at a characteristic optimal folding temperature T-opt*. The optimal folding temperature T-opt* is located between the thermodynamic folding transition temperature and the solidification temperature based on the Lindemann criterion for the solid. Both the T-opt* and the MFPT decrease when the energy bias gap against nonnative contacts increases. The high-order moments are nearly constant when the temperature is higher than T-opt* and start to diverge when the temperature is lower than T-opt*. The distribution of FPT is close to a log-normal-like distribution at T* greater than or equal to T-opt*. At even lower temperatures, the distribution starts to develop long power-law-like tails, indicating the non-self-averaging intermittent behavior of the folding dynamics. It is demonstrated that the distribution of FPT can also be calculated reliably from the derivative of the fraction not folded (or fraction folded), a measurable quantity by routine ensemble-averaged experimental techniques at dilute protein concentrations.