Evidence map›Paper›PMID 18223000›Full record

ArticleBiophysical journal2008

An error analysis for two-state protein-folding kinetic parameters and phi-values: progress toward precision by exploring pH dependencies on Leffler plots.

Eva S Cobos, Adela M Candel, Jose C Martinez

Abstract read
In one paragraph

Article in Biophysical journal, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Eva S CobosDepartment of Physical Chemistry and Institute of Biotechnology, Faculty of Sciences, University of Granada, 18071 Granada, Spain.
Adela M Candel
Jose C Martinez

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interpretation of phi-values has led to an understanding of the folding transition state ensemble of a variety of proteins. Although the main guidelines and equations for calculating phi are well established, there remains some controversy about the quality of the numerical values obtained. By analyzing a complete set of results from kinetic experiments with the SH3 domain of alphaspectrin (Spc-SH3) and applying classical error methods and error-propagation formulas, we evaluated the uncertainties involved in two-state-folding kinetic experimental parameters and the corresponding calculated phi-values. We show that kinetic constants in water and m values can be properly estimated from a judicious weighting of fitting errors and describe some procedures to calculate the errors in Gibbs energies and phi-values from a traditional two-point Leffler analysis. Furthermore, on the basis of general assumptions made with the protein engineering method, we show how to generate multipoint Leffler plots via the analysis of pH dependencies of kinetic parameters. We calculated the definitive phi-values for a collection of single mutations previously designed to characterize the folding transition state of the alphaspectrin SH3 domain. The effectiveness of the pH-scanning procedure is also discussed in the context of error analysis. Judging from the magnitudes of the error bars obtained from two-point and multipoint Leffler plots, we conclude that the precision obtained for phi-values should be approximately 25%, a reasonable limit that takes into account the propagation of experimental errors.

Indexed as

Models, ChemicalModels, MolecularComputer SimulationHydrogen-Ion ConcentrationKineticsPhase TransitionProtein FoldingProteinsReproducibility of ResultsSensitivity and SpecificityProteins

Identifiers

PMID18223000
PMCPMC2480672

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.