Kinetic class analysis of hydrogen-exchange data

Biochemistry ◽  
1970 ◽  
Vol 9 (7) ◽  
pp. 1547-1553 ◽  
Author(s):  
Stuart L. Laiken ◽  
Morton P. Printz
Keyword(s):  
Hydrogen Exchange ◽  
Class Analysis ◽  
Kinetic Class ◽  
Exchange Data

Acquisition and Interpretation of Hydrogen Exchange Data from Peptides, Polymers, and Proteins

2006 ◽  
pp. 1-113 ◽  
Author(s):  
Alfred D. Barksdale ◽  
Andreas Rosenberg
Keyword(s):  
Hydrogen Exchange ◽  
Exchange Data

scholarly journals SWOTein: A structure-based approach to predict stability Strengths and Weaknesses of prOTEINs

2020 ◽  
Author(s):  
Q. Hou ◽  
F. Pucci ◽  
F. Ancien ◽  
J.M. Kwasigroch ◽  
R. Bourgeas ◽  
...  
Keyword(s):  
Free Energy ◽  
Large Scale ◽  
Hydrogen Exchange ◽  
Energy Functions ◽  
Functional Regions ◽  
Apocytochrome B ◽  
Amino Acid Binding ◽  
The Individual ◽  
Structured Proteins ◽  
Exchange Data

AbstractMotivationAlthough structured proteins adopt their lowest free energy conformation in physiological conditions, the individual residues are generally not in their lowest free energy conformation. Residues that are stability weaknesses are often involved in functional regions, whereas stability strengths ensure local structural stability. The detection of strengths and weaknesses provides key information to guide protein engineering experiments aiming to modulate folding and various functional processes.ResultsWe developed the SWOTein predictor which identifies strong and weak residues in proteins on the basis of three types of statistical energy functions describing local interactions along the chain, hydrophobic forces and tertiary interactions. The large-scale comparison of the different types of strengths and weaknesses showed their complementarity and the enhancement of the information they provide. We applied SWOTein to apocytochrome b562 and found good agreement between predicted strengths and weaknesses and native hydrogen exchange data. Its application to an amino acid-binding protein identified the hinge at the basis of the conformational change. SWOTein is both fast and accurate and can be applied at small and large scale to analyze and modulate folding and molecular recognition processes.AvailabilityThe SWOTein webserver provides the list of predicted strengths and weaknesses and a protein structure visualization tool that facilitates the interpretation of the predictions. It is freely available for academic use at http://babylone.ulb.ac.be/SWOTein.

A statistical appraisal of native state hydrogen exchange data: evidence for a burst phase continuum?11Edited by P. E. Wright

2000 ◽  
Vol 300 (5) ◽  
pp. 1361-1375 ◽  
Author(s):  
Martin J. Parker ◽  
Susan Marqusee
Keyword(s):  
Hydrogen Exchange ◽  
Native State ◽  
Burst Phase ◽  
Exchange Data

scholarly journals Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data

2018 ◽  
Vol 19 (11) ◽  
pp. 3406
Author(s):  
Didier Devaurs ◽  
Dinler Antunes ◽  
Lydia Kavraki
Keyword(s):  
Protein Structure ◽  
Computational Methods ◽  
Hydrogen Exchange ◽  
Protein Structures ◽  
Conformational Space ◽  
Conformational Sampling ◽  
Computational Framework ◽  
Large Proteins ◽  
Unknown Protein ◽  
Exchange Data

Both experimental and computational methods are available to gather information about a protein’s conformational space and interpret changes in protein structure. However, experimentally observing and computationally modeling large proteins remain critical challenges for structural biology. Our work aims at addressing these challenges by combining computational and experimental techniques relying on each other to overcome their respective limitations. Indeed, despite its advantages, an experimental technique such as hydrogen-exchange monitoring cannot produce structural models because of its low resolution. Additionally, the computational methods that can generate such models suffer from the curse of dimensionality when applied to large proteins. Adopting a common solution to this issue, we have recently proposed a framework in which our computational method for protein conformational sampling is biased by experimental hydrogen-exchange data. In this paper, we present our latest application of this computational framework: generating an atomic-resolution structural model for an unknown protein state. For that, starting from an available protein structure, we explore the conformational space of this protein, using hydrogen-exchange data on this unknown state as a guide. We have successfully used our computational framework to generate models for three proteins of increasing size, the biggest one undergoing large-scale conformational changes.

scholarly journals Coarse-Grained Conformational Sampling of Protein Structure Improves the Fit to Experimental Hydrogen-Exchange Data

2017 ◽  
Vol 4 ◽  
Author(s):  
Didier Devaurs ◽  
Dinler A. Antunes ◽  
Malvina Papanastasiou ◽  
Mark Moll ◽  
Daniel Ricklin ◽  
...  
Keyword(s):  
Protein Structure ◽  
Hydrogen Exchange ◽  
Coarse Grained ◽  
Conformational Sampling ◽  
Exchange Data
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