Identifying protein folding cores from the evolution of flexible regions during unfolding

Hespenheide, Brandon M.; Rader, Andrew J.; Thorpe, M. F.; Kuhn, Leslie A.

doi:10.1016/s1093-3263(02)00146-8

Cited by 118 publications

(189 citation statements)

References 49 publications

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“…These data suggest that native-state dynamics are closely related to unfolding and folding dynamics, in agreement with our findings in the first simulations of protein unfolding (Daggett and Levitt 1992). Later, Hespenheide et al (2002) explored the relationship between flexibility and unfolding pathways in simulations of 10 monomeric proteins and compared the results to hydrogen-deuterium exchange experiments (Li and Woodward 1999). They found that the folding cores of proteins with the greatest structural stability against denaturation could be determined by flexibility.…”

Section: Native-state Flexibility and Early Unfolding Eventssupporting

confidence: 86%

Dynameomics: Large‐scale assessment of native protein flexibility

Benson

Daggett

2008

Protein Science

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Structure is only the first step in understanding the interactions and functions of proteins. In this paper, we explore the flexibility of proteins across a broad database of over 250 solvated protein molecular dynamics simulations in water for an aggregate simulation time of ;6 ms. These simulations are from our Dynameomics project, and these proteins represent approximately 75% of all known protein structures. We employ principal component analysis of the atomic coordinates over time to determine the primary axis and magnitude of the flexibility of each atom in a simulation. This technique gives us both a database of flexibility for many protein fold families and a compact visual representation of a particular protein's native-state conformational space, neither of which are available using experimental methods alone. These tools allow us to better understand the nature of protein motion and to describe its relationship to other structural and dynamical characteristics. In addition to reporting general properties of protein flexibility and detailing many dynamic motifs, we characterize the relationship between protein native-state flexibility and early events in thermal unfolding and show that flexibility predicts how a protein will begin to unfold. We provide evidence that fold families have conserved flexibility patterns, and family members who deviate from the conserved patterns have very low sequence identity. Finally, we examine novel aspects of highly inflexible loops that are as important to structural integrity as conventional secondary structure. These loops, which are difficult if not impossible to locate without dynamic data, may constitute new structural motifs.Keywords: protein; flexibility; folding; stability; families Much scientific effort has been spent attempting to catalog, describe, observe, and understand protein structure and function. Even when the structure of a protein is known, this knowledge is often not sufficient to elucidate details of the protein's function or its mode of action, both of which are pieces of information that are frequently of much greater importance to biologists than structure. As biologists increasingly seek to understand and modify aspects of cellular behavior and as protein databases gather more high-resolution three-dimensional structures, the ability to understand key features of a protein's dynamic behavior becomes more important.Flexibility is critical in determining protein behavior and function. Because proteins are not static entities (as they are represented in structural databases) and because crystal structures do not necessarily represent a protein in its active conformation, any attempt to determine potential biochemical interactions of a protein from these data suffers from a lack of information about its motion. A quantitative description of a protein's flexibility provides a summary of its dominant dynamical modes and significant information about potential conformations available to it. Flexibility may also provide insight into unfoldin...

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Section: Native-state Flexibility and Early Unfolding Eventssupporting

confidence: 86%

Dynameomics: Large‐scale assessment of native protein flexibility

Benson

Daggett

2008

Protein Science

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“…A study by Rader et al [12] analysed a set of 26 different protein structures using rigidity dilution, drawing an analogy between the loss of rigidity during this dilution and the thermal denaturation of a protein. A similar study by Hespenheide et al [13] made predictions for the "folding core" of several proteins based on the regions that retained rigidity longest during the dilution, obtaining a promising correlation with experimental data. This variation of rigidity as different constraints are included, however, is in a sense the Achilles heel of the method if it is to be used as a coarse-graining approach and a basis for simulation.…”

Section: Introductionmentioning

confidence: 76%

“…This was the approach taken by [6] when studying a major conformational change during assembly of a large protein complex. Previous studies on large numbers of proteins [12,13] have considered single examples of multiple unrelated proteins, and hence do not provide the comparative information we need. A study by Mamonova et al [14] examined the variation in RCD of a protein structure in the course of a 10ns MD simulation, finding that the RCD varied quite dramatically for different snapshots of the MD trajectory.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of rigidity across protein families

2009

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Abstract. Revision : 1.38, compiled 19 March 2018Rigidity analysis using the "pebble game" can usefully be applied to protein crystal structures to obtain information on protein folding, assembly and the structure-function relationship. However, previous work using this technique has not made clear how sensitive rigidity analysis is to small structural variations. We present a comparative study in which rigidity analysis is applied to multiple structures, derived from different organisms and different conditions of crystallisation, for each of several different proteins. We find that rigidity analysis is best used as a comparative tool to highlight the effects of structural variation. Our use of multiple protein structures brings out a previously unnoticed peculiarity in the rigidity of trypsin.

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“…ProFlex calculates a hydrogen-bond dilution profile, 50 which StoneHingeP analyzes to identify an energy level optimal for determining domains and intervening hinges (Supp. Info.…”

Section: Protein Preparationmentioning

confidence: 99%

StoneHinge: Hinge prediction by network analysis of individual protein structures

et al. 2009

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Hinge motions are important for molecular recognition, and knowledge of their location can guide the sampling of protein conformations for docking. Predicting domains and intervening hinges is also important for identifying structurally self-determinate units and anticipating the influence of mutations on protein flexibility and stability. Here we present StoneHinge, a novel approach for predicting hinges between domains using input from two complementary analyses of noncovalent bond networks: StoneHingeP, which identifies domain-hinge-domain signatures in ProFlex constraint counting results, and StoneHingeD, which does the same for DomDecomp Gaussian network analyses. Predictions for the two methods are compared to hinges defined in the literature and by visual inspection of interpolated motions between conformations in a series of proteins. For StoneHingeP, all the predicted hinges agree with hinge sites reported in the literature or observed visually, although some predictions include extra residues. Furthermore, no hinges are predicted in six hinge-free proteins. On the other hand, StoneHingeD tends to overpredict the number of hinges, while accurately pinpointing hinge locations. By determining the consensus of their results, StoneHinge improves the specificity, predicting 11 of 13 hinges found both visually and in the literature for nine different open protein structures, and making no false-positive predictions. By comparison, a popular hinge detection method that requires knowledge of both the open and closed conformations finds 10 of the 13 known hinges, while predicting four additional, false hinges.

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Identifying protein folding cores from the evolution of flexible regions during unfolding

Cited by 118 publications

References 49 publications

Dynameomics: Large‐scale assessment of native protein flexibility

Dynameomics: Large‐scale assessment of native protein flexibility

Comparative analysis of rigidity across protein families

StoneHinge: Hinge prediction by network analysis of individual protein structures

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