Protein flexibility predictions using graph theory

Jacobs, Donald J.; Rader, Andrew J.; Kuhn, Leslie A.; Thorpe, M. F.

doi:10.1002/prot.1081

Cited by 705 publications

(912 citation statements)

References 50 publications

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“…For this, potential hydrogen bonds are ranked according to an energy function that takes into account the hybridization state of donor and acceptor atoms as well as their mutual orientation. 57 By tuning the energy threshold E HB , strong hydrogen bonds can be distinguished from weaker ones. Hydrogen bonds are included if their energy is e-1.0 kcal/mol.…”

Section: Methodsmentioning

confidence: 99%

HIV-1 TAR RNA Spontaneously Undergoes Relevant Apo-to-Holo Conformational Transitions in Molecular Dynamics and Constrained Geometrical Simulations

Fulle

Christ

Kestner

et al. 2010

J. Chem. Inf. Model.

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We report all-atom molecular dynamics and replica exchange molecular dynamics simulations on the unbound human immunodeficiency virus type-1 (HIV-1) transactivation responsive region (TAR) RNA structure and three TAR RNA structures in bound conformations of, in total, ∼250 ns length. We compare the extent of observed conformational sampling with that of the conceptually simpler and computationally much cheaper constrained geometrical simulation approach framework rigidity optimized dynamic algorithm (FRODA). Atomic fluctuations obtained by replica-exchange molecular dynamics (REMD) simulations agree quantitatively with those obtained by molecular dynamics (MD) and FRODA simulations for the unbound TAR structure. Regarding the stereochemical quality of the generated conformations, backbone torsion angles and puckering modes of the sugar-phosphate backbone were reproduced equally well by MD and REMD simulations, but further improvement is needed in the case of FRODA simulations. Essential dynamics analysis reveals that all three simulation approaches show a tendency to sample bound conformations when starting from the unbound TAR structure, with MD and REMD simulations being superior with respect to FRODA. These results are consistent with the experimental view that bound TAR RNA conformations are transiently sampled in the free ensemble, following a conformation selection model. The simulation-generated TAR RNA conformations have been successfully used as receptor structures for docking. This finding has important implications for RNA-ligand docking in that docking into an ensemble of simulation-generated RNA structures is shown to be a valuable means to cope with large apo-to-holo conformational transitions of the receptor structure.

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Section: Methodsmentioning

confidence: 99%

HIV-1 TAR RNA Spontaneously Undergoes Relevant Apo-to-Holo Conformational Transitions in Molecular Dynamics and Constrained Geometrical Simulations

Fulle

Christ

Kestner

et al. 2010

J. Chem. Inf. Model.

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“…Decompositions of the 33 protein structures (taken from PDB) into rigid clusters were performed using the FIRST software (28), which is an implementation of a network rigidity analysis algorithm for investigating protein rigidity and flexibility (29). Within each protein structure, decompositions were calculated for 100 values of the hydrogen bond cut-off energy, ranging from −0.05 kcal/mol to −5.00 kcal/mol thus producing 3300 rigid cluster decompositions.…”

Section: Methodsmentioning

confidence: 99%

“…We identify all sets of atoms that form rigid clusters by employing FIRST (Floppy Inclusion and Rigid Substructure Topography) software (28). The FIRST package is based on a "pebble game" algorithm (29). In less than a second of the computational time, it identifies all flexible and rigid regions in a protein structure and provides the essential information on local rigidity properties, such as whether a given atom belongs to a particular rigid cluster, overconstrained region, or region participating in a correlated motion.…”

Section: Introductionmentioning

confidence: 99%

New insight into long‐range nonadditivity within protein double‐mutant cycles

et al. 2008

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Additivity principles in chemistry, biochemistry, and biophysics have been used extensively for decades. Nevertheless, it is well known that additivity frequently breaks down in complex biomacromolecules. Nonadditivity within protein double mutant free energy cycles of spatially close residue pairs is a generally well-understood phenomenon, whereas a robust description of nonadditivity extending over large distances remains to be developed. Here, we test the hypothesis that the mutational effects tend to be nonadditive if two structurally well-separated mutated residues belong to the same rigid cluster within the wild type protein, and additive if they are located within different clusters. We find the hypothesis to be statistically significant with Pvalues that range from 10 −5 to 10 −6 . To the best of our knowledge, this result represents the first demonstration of a statistically significant preponderance for nonadditivity over long distances. These findings provide new insight into the origins of long-range nonadditivity in double mutant cycles, which complements the conventional wisdom that nonadditivity arises in double mutations involving contacting residues. Consequently, these results should have far-reaching implications for a proper understanding of protein stability, structure/function analyses, and protein design.

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“…StoneHingeP is unique in using constraint counting from rigidity theory, as implemented in ProFlex, as the basis for predictions. ProFlex (successor to the FIRST method 27 ) analyzes flexibility using a threedimensional constraint counting algorithm that decomposes a protein structure into rotatable and nonrotatable bonds. This analysis is based on bond rotational constraints placed by covalent and noncovalent bonds in the network.…”

Section: Identifying Hingesmentioning

confidence: 99%

“…The hydrogen bonds to internal waters can be important for the protein structure, whereas including surface waters tends to lead to overestimation of the rigidity of the protein. 27 All predictions presented here are made with internal water molecules only, as determined by PRO_ACT. 47 Predictions were also run using no water molecules (data not shown), as is done on the automated StoneHinge server.…”

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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Protein flexibility predictions using graph theory

Cited by 705 publications

References 50 publications

HIV-1 TAR RNA Spontaneously Undergoes Relevant Apo-to-Holo Conformational Transitions in Molecular Dynamics and Constrained Geometrical Simulations

HIV-1 TAR RNA Spontaneously Undergoes Relevant Apo-to-Holo Conformational Transitions in Molecular Dynamics and Constrained Geometrical Simulations

New insight into long‐range nonadditivity within protein double‐mutant cycles

StoneHinge: Hinge prediction by network analysis of individual protein structures

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