Topological Quantities Determining the Folding/Unfolding Rate of Two-state Folding Proteins

Jung, Jaewoon; Buglass, Alan J.; Lee, Eok-Kyun

doi:10.1007/s10953-010-9556-3

Cited by 8 publications

(15 citation statements)

References 36 publications

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“…Similarity of the folding rates among extant Trx proteins is not an unexpected finding, because we are assessing the kinetics of a specific fold, and there are several reports correlating various topology metrics to folding kinetic rates (49)(50)(51)(52). Moreover, the observed robust folding rates suggest that the Trx energy landscapes are unfrustrated (3,5,29,36,53,54).…”

Section: Resultsmentioning

confidence: 68%

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Tzul

Vasilchuk

Makhatadze

2017

Proc. Natl. Acad. Sci. U.S.A.

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Theoretical and experimental studies have firmly established that protein folding can be described by a funneled energy landscape. This funneled energy landscape is the result of foldable protein sequences evolving following the principle of minimal frustration, which allows proteins to rapidly fold to their native biologically functional conformations. For a protein family with a given functional fold, the principle of minimal frustration suggests that, independent of sequence, all proteins within this family should fold with similar rates. However, depending on the optimal living temperature of the organism, proteins also need to modulate their thermodynamic stability. Consequently, the difference in thermodynamic stability should be primarily caused by differences in the unfolding rates. To test this hypothesis experimentally, we performed comprehensive thermodynamic and kinetic analyses of 15 different proteins from the thioredoxin family. Eight of these thioredoxins were extant proteins from psychrophilic, mesophilic, or thermophilic organisms. The other seven protein sequences were obtained using ancestral sequence reconstruction and can be dated back over 4 billion years. We found that all studied proteins fold with very similar rates but unfold with rates that differ up to three orders of magnitude. The unfolding rates correlate well with the thermodynamic stability of the proteins. Moreover, proteins that unfold slower are more resistant to proteolysis. These results provide direct experimental support to the principle of minimal frustration hypothesis.protein folding | protein stability | protein evolution T he energy landscape theory provides a conceptual physicochemical framework for understanding protein folding. This theory is based on the principle of minimal frustration that ". . .quantifies the dominance of interactions stabilizing the specific native structure over other interactions that would favor nonnative, topologically distinct traps" (1). A consequence of this is that the folding energy landscape of naturally occurring proteins is funnel-shaped (1-22). The shape of this funnel depends on two main factors that can introduce frustration and roughness: topology and the extent of nonnative interactions. Topological frustration can occur when certain native interactions are formed too early and need to be undone to allow for other interactions to form first, leading to backtracking and/or cracking (23-28). Weak nonnative interactions can have complex effects on the folding landscape (29-31): small amounts of weak nonnative interactions can assist folding, whereas larger amounts can create internal friction that will slow folding (32-35). For a given protein fold, both topological and energetic frustrations will depend on the amino acid sequence. Theoretical studies have suggested that naturally occurring proteins have selected sequences that are compatible with the principle of minimal frustration (36).The goal of this study is to experimentally test the evolutionary validity of the principle...

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Section: Resultsmentioning

confidence: 68%

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Tzul

Vasilchuk

Makhatadze

2017

Proc. Natl. Acad. Sci. U.S.A.

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“…We have made a comparison of various topological parameters derived from the native structures of two-state proteins in relating them with their unfolding rates. The Table II have been taken from Jung et al 22 It is observed that for the full set of 25 two-state proteins, except LRO and the relative impact of edge removal (IER/L), all the topological parameters shows a minimal correlation with experimental ln(k u ). The correlation computed between experimental ln(k u ) and various topological parameters are relative contact order (RCO) r 5 20.17, total contact distance (TCD) r 5 20.32, LRO r 5 20.65, CC (clustering co-efficient) r 5 20.30, IER/N (the impact of edge removal per residue) r 5 0.59, and IER/L r 5 0.61.…”

Section: Comparison Of Various Topological Parameters In Relation Witmentioning

confidence: 99%

Application of long‐range order to predict unfolding rates of two‐state proteins

Balasubramanian

Selvaraj

2010

Proteins

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Predicting the experimental unfolding rates of two-state proteins and models describing the unfolding rates of these proteins is quite limited because of the complexity present in the unfolding mechanism and the lack of experimental unfolding data compared with folding data. In this work, 25 two-state proteins characterized by Maxwell et al. (Protein Sci 2005;14:602–616) using a consensus set of experimental conditions were taken, and the parameter long-range order (LRO) derived from their three-dimensional structures were related with their experimental unfolding rates ln(k(u)). From the total data set of 30 proteins used by Maxwell et al. (Protein Sci 2005;14:602–616), five slow-unfolding proteins with very low unfolding rates were considered to be outliers and were not included in our data set. Except all beta structural class, LRO of both the all-alpha and mixed-class proteins showed a strong inverse correlation of r = -0.99 and -0.88, respectively, with experimental ln(k(u)). LRO shows a correlation of -0.62 with experimental ln(k(u)) for all-beta proteins. For predicting the unfolding rates, a simple statistical method has been used and linear regression equations were developed for individual structural classes of proteins using LRO, and the results obtained showed a better agreement with experimental results.

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“…To create our database on protein folding kinetics, we combined all entries from the 15 datasets mentioned above, which yielded a total of 184 possible entries . For each possible entry, we verified the following information using the original experimental source(s): the experimental construct used and its associated PDB code (with fragments specified by start and end residues), whether the protein is a two‐ or multi‐state folding protein, the temperature, pH, buffer, denaturant, folding/detection method used, and the experimental kinetics results (folding rate constant ln k f and associated m ‐value, if reported).…”

Section: The Database Includes Comprehensive and Verified Kinetics Datamentioning

confidence: 99%

“…is a gold standard, it is limited to those 30 two‐state proteins. In an effort to include multi‐state folding proteins (multi‐state proteins) and take advantage of folding kinetics studies on additional two‐state proteins, many research groups have created their own datasets by aggregating additional folding kinetics data from reports that may not conform to the consensus conditions or reporting standards . In many cases, extracting the complete information relevant to the experiment (an extrapolated ln k f value, experimental conditions, associated protein databank (PDB) code, and the details of the actual construct used for the folding studies) is challenging, if not impossible.…”

Section: Introductionmentioning

confidence: 99%

“…The consequences of the unstandardized reporting in the protein folding community are apparent from numerous discrepancies among the different databases, in the reported rate constants, and associated PDB files. Recognizing these issues, we compiled folding rate constants from 15 published collections/online databases that have varying degrees of overlap in included proteins . We resolved discrepancies by verifying the experimental conditions, rate constants, and construct information from the original experimental sources.…”

Section: Introductionmentioning

confidence: 99%

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A comprehensive database of verified experimental data on protein folding kinetics

et al. 2014

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Insights into protein folding rely increasingly on the synergy between experimental and theoretical approaches. Developing successful computational models requires access to experimental data of sufficient quantity and high quality. We compiled folding rate constants for what initially appeared to be 184 proteins from 15 published collections/web databases. To generate the highest confidence in the dataset, we verified the reported lnk f value and exact experimental construct and conditions from the original experimental report(s). The resulting comprehensive database of 126 verified entries, ACPro, will serve as a freely accessible resource (https://www.ats. amherst.edu/protein/) for the protein folding community to enable confident testing of predictive models. In addition, we provide a streamlined submission form for researchers to add new folding kinetics results, requiring specification of all the relevant experimental information according to the standards proposed in 2005 by the protein folding consortium organized by Plaxco. As the number and diversity of proteins whose folding kinetics are studied expands, our curated database will enable efficient and confident incorporation of new experimental results into a standardized collection. This database will support a more robust symbiosis between experiment and theory, leading ultimately to more rapid and accurate insights into protein folding, stability, and dynamics.

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Topological Quantities Determining the Folding/Unfolding Rate of Two-state Folding Proteins

Cited by 8 publications

References 36 publications

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Application of long‐range order to predict unfolding rates of two‐state proteins

A comprehensive database of verified experimental data on protein folding kinetics

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