Browse
Submit Data
Databases
API
Help

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Contact order revisited: influence of protein size on the folding rate.

ABSTRACT: Guided by the recent success of empirical model predicting the folding rates of small two-state folding proteins from the relative contact order (CO) of their native structures, by a theoretical model of protein folding that predicts that logarithm of the folding rate decreases with the protein chain length L as L(2/3), and by the finding that the folding rates of multistate folding proteins strongly correlate with their sizes and have very bad correlation with CO, we reexamined the dependence of folding rate on CO and L in attempt to find a structural parameter that determines folding rates for the totality of proteins. We show that the Abs_CO = CO x L, is able to predict rather accurately folding rates for both two-state and multistate folding proteins, as well as short peptides, and that this Abs_CO scales with the protein chain length as L(0.70 +/- 0.07) for the totality of studied single-domain proteins and peptides.

SUBMITTER: Ivankov DN

PROVIDER: S-EPMC2324001 | biostudies-literature | 2003 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Contact order revisited: influence of protein size on the folding rate.

Ivankov Dmitry N DN Garbuzynskiy Sergiy O SO Alm Eric E Plaxco Kevin W KW Baker David D Finkelstein Alexei V AV

Protein science : a publication of the Protein Society 20030901 9

Guided by the recent success of empirical model predicting the folding rates of small two-state folding proteins from the relative contact order (CO) of their native structures, by a theoretical model of protein folding that predicts that logarithm of the folding rate decreases with the protein chain length L as L(2/3), and by the finding that the folding rates of multistate folding proteins strongly correlate with their sizes and have very bad correlation with CO, we reexamined the dependence o ...[more]

PMID: 12931003

Similar Datasets

Examining a Thermodynamic Order Parameter of Protein Folding.

Project description:Dimensionality reduction with a suitable choice of order parameters or reaction coordinates is commonly used for analyzing high-dimensional time-series data generated by atomistic biomolecular simulations. So far, geometric order parameters, such as the root mean square deviation, fraction of native amino acid contacts, and collective coordinates that best characterize rare or large conformational transitions, have been prevailing in protein folding studies. Here, we show that the solvent-averaged effective energy, which is a thermodynamic quantity but unambiguously defined for individual protein conformations, serves as a good order parameter of protein folding. This is illustrated through the application to the folding-unfolding simulation trajectory of villin headpiece subdomain. We rationalize the suitability of the effective energy as an order parameter by the funneledness of the underlying protein free energy landscape. We also demonstrate that an improved conformational space discretization is achieved by incorporating the effective energy. The most distinctive feature of this thermodynamic order parameter is that it works in pointing to near-native folded structures even when the knowledge of the native structure is lacking, and the use of the effective energy will also find applications in combination with methods of protein structure prediction.

| S-EPMC5940758 | biostudies-literature

Modulation of contact order effects in the two-state folding of stefins A and B.

Project description:It is well established that contact order and folding rates are correlated for small proteins. The folding rates of stefins A and B differ by nearly two orders of magnitude despite sharing an identical native fold and hence contact order. We break down the determinants of this behavior and demonstrate that the modulation of contact order effects can be accounted for by the combined contributions of a framework-like mechanism, characterized by intrinsic helix stabilities, together with nonnative helical backbone conformation and nonnative hydrophobic interactions within the folding transition state. These contributions result in the formation of nonnative interactions in the transition state as evidenced by the opposing effects on folding rate and stability of these proteins.

| S-EPMC3149235 | biostudies-literature

Contact Order Is a Determinant for the Dependence of GFP Folding on the Chaperonin GroEL.

Project description:The GroE chaperonin system facilitates protein folding in an ATP-dependent manner. It has remained unclear why some proteins are obligate clients of the GroE system, whereas other closely related proteins are able to fold efficiently in its absence. Factors that cause folding to be slower affect kinetic partitioning between spontaneous folding and chaperone binding in favor of the latter. One such potential factor is contact order (CO), which is the average separation in sequence between residues that are in contact in the native structure. Here, we generated variants of enhanced green fluorescent protein with different COs using circular permutations. We found that GroE dependence in vitro and in vivo increases with increasing CO. Thus, our results show that CO is relevant not only for folding in vitro of relatively simple model systems but also for chaperonin dependence and folding in vivo.

| S-EPMC6342685 | biostudies-literature

CONFOLD: Residue-residue contact-guided ab initio protein folding.

Project description:Predicted protein residue-residue contacts can be used to build three-dimensional models and consequently to predict protein folds from scratch. A considerable amount of effort is currently being spent to improve contact prediction accuracy, whereas few methods are available to construct protein tertiary structures from predicted contacts. Here, we present an ab initio protein folding method to build three-dimensional models using predicted contacts and secondary structures. Our method first translates contacts and secondary structures into distance, dihedral angle, and hydrogen bond restraints according to a set of new conversion rules, and then provides these restraints as input for a distance geometry algorithm to build tertiary structure models. The initially reconstructed models are used to regenerate a set of physically realistic contact restraints and detect secondary structure patterns, which are then used to reconstruct final structural models. This unique two-stage modeling approach of integrating contacts and secondary structures improves the quality and accuracy of structural models and in particular generates better β-sheets than other algorithms. We validate our method on two standard benchmark datasets using true contacts and secondary structures. Our method improves TM-score of reconstructed protein models by 45% and 42% over the existing method on the two datasets, respectively. On the dataset for benchmarking reconstructions methods with predicted contacts and secondary structures, the average TM-score of best models reconstructed by our method is 0.59, 5.5% higher than the existing method. The CONFOLD web server is available at http://protein.rnet.missouri.edu/confold/.

| S-EPMC4509844 | biostudies-literature

On the role of structural class of a protein with two-state folding kinetics in determining correlations between its size, topology, and folding rate.

Project description:The time it takes for proteins to fold into their native states varies over several orders of magnitude depending on their native-state topology, size, and amino acid composition. In a number of previous studies, it was found that there is strong correlation between logarithmic folding rates and contact order for proteins that fold with two-state kinetics, while such correlation is absent for three-state proteins. Conversely, strong correlations between folding rates and chain length occur within three-state proteins, but not in two-state proteins. Here, we demonstrate that chain lengths and folding rates of two-state proteins are not correlated with each other only when all-alpha, all-beta, and mixed-class proteins are considered together, which is typically the case. However, when considering all-alpha and all-beta two-state proteins separately, there is significant linear correlation between folding rate and size. Moreover, the sets of data points for the all-alpha and all-beta classes define asymptotes of lower and upper limits on folding rates of mixed-class proteins. By analyzing correlation of other topological parameters with folding rates of two-state proteins, we find that only the long-range order exhibits correlation with folding rates that is uniform over all three classes. It is also the only descriptor to provide statistically significant correlations for each of the three structural classes. We give an interpretation of this observation in terms of Makarov and Plaxco's diffusion-based topomer-search model.

| S-EPMC2211710 | biostudies-literature

Inferring the rate-length law of protein folding.

Project description:We investigate the rate-length scaling law of protein folding, a key undetermined scaling law in the analytical theory of protein folding. Available data yield statistically significant evidence for the existence of a rate-length law capable of predicting folding times to within about two orders of magnitude (over 9 decades of variation). Unambiguous determination of the functional form of such a law could provide key mechanistic insight into folding. Four proposed laws from literature (power law, exponential, and two stretched exponentials) are tested against one another, and it is found that the power law best explains the data by a modest margin. We conclude that more data is necessary to unequivocally infer the rate-length law. Such data could be obtained through a small number of protein folding experiments on large protein domains.

| S-EPMC3855161 | biostudies-literature

Running speed-induced changes in foot contact pattern influence impact loading rate.

Project description:Purpose. We aimed to determine the effect of speed-induced changes in foot contact patterns on the vertical instantaneous loading rate (VILR). We hypothesized that transition runners, i.e. runners that shift towards a mid- (MF) or forefoot contact pattern (FF) when running speed increases, show smaller increases in VILR than non-transition runners, i.e. runners that remain with a rearfoot contact pattern (RF). Methods. Fifty-two male and female runners ran overground at 3.2, 4.1, 5.1 and 6.2 m s-1. Ground reaction forces, lower limb sagittal plane knee and ankle kinematics and plantar pressures were recorded. Multi-level linear regression models were used to assess differences between transition and non-transition runners. Results. Non-transition runners experienced larger speed-induced increases in VILR (48.6 ± 2.6 BW s-1 per m s-1) than transition runners (-1.4 ± 7.6 BW s-1 per m s-1). Transition runners showed higher VILRs and a more flat foot touch down at the same pre-transition speed than non-transition runners. Conclusion. When running speed increases, some runners transition towards more anterior foot contact patterns. This reduces or even eliminates the speed-induced increase in VILR. This result is especially the case for those RF runners who already have relatively high VILRs and flat foot positioning at slower running speeds.

| S-EPMC9524621 | biostudies-literature

PON-Fold: Prediction of Substitutions Affecting Protein Folding Rate.

Project description:Most proteins fold into characteristic three-dimensional structures. The rate of folding and unfolding varies widely and can be affected by variations in proteins. We developed a novel machine-learning-based method for the prediction of the folding rate effects of amino acid substitutions in two-state folding proteins. We collected a data set of experimentally defined folding rates for variants and used them to train a gradient boosting algorithm starting with 1161 features. Two predictors were designed. The three-class classifier had, in blind tests, specificity and sensitivity ranging from 0.324 to 0.419 and from 0.256 to 0.451, respectively. The other tool was a regression predictor that showed a Pearson correlation coefficient of 0.525. The error measures, mean absolute error and mean squared error, were 0.581 and 0.603, respectively. One of the previously presented tools could be used for comparison with the blind test data set, our method called PON-Fold showed superior performance on all used measures. The applicability of the tool was tested by predicting all possible substitutions in a protein domain. Predictions for different conformations of proteins, open and closed forms of a protein kinase, and apo and holo forms of an enzyme indicated that the choice of the structure had a large impact on the outcome. PON-Fold is freely available.

| S-EPMC10455311 | biostudies-literature

Predicting protein folding rates from geometric contact and amino acid sequence.

Project description:Protein folding speeds are known to vary over more than eight orders of magnitude. Plaxco, Simons, and Baker (see References) first showed a correlation of folding speed with the topology of the native protein. That and subsequent studies showed, if the native structure of a protein is known, its folding speed can be predicted reasonably well through a correlation with the "localness" of the contacts in the protein. In the present work, we develop a related measure, the geometric contact number, N (alpha), which is the number of nonlocal contacts that are well-packed, by a Voronoi criterion. We find, first, that in 80 proteins, the largest such database of proteins yet studied, N (alpha) is a consistently excellent predictor of folding speeds of both two-state fast folders and more complex multistate folders. Second, we show that folding rates can also be predicted from amino acid sequences directly, without the need to know the native topology or other structural properties.

| S-EPMC2441995 | biostudies-literature

Cysteine-cysteine contact preference leads to target-focusing in protein folding.

Project description:We perform a statistical analysis of amino-acid contacts to investigate possible preferences of amino-acid interactions. We include in the analysis only tertiary contacts, because they are less constrained--compared to secondary contacts--by proteins' backbone rigidity. Using proteins from the protein data bank, our analysis reveals an unusually high frequency of cysteine pairings relative to that expected from random. To elucidate the possible effects of cysteine interactions in folding, we perform molecular simulations on three cysteine-rich proteins. In particular, we investigate the difference in folding dynamics between a Gō-like model (where attraction only occurs between amino acids forming a native contact) and a variant model (where attraction between any two cysteines is introduced to mimic the formation/dissociation of native/nonnative disulfide bonds). We find that when attraction among cysteines is nonspecific and comparable to a solvent-averaged interaction, they produce a target-focusing effect that expedites folding of cysteine-rich proteins as a result of a reduction of conformational search space. In addition, the target-focusing effect also helps reduce glassiness by lowering activation energy barriers and kinetic frustration in the system. The concept of target-focusing also provides a qualitative understanding of a correlation between the rates of protein folding and parameters such as contact order and total contact distance.

| S-EPMC1913149 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data