Hinge‐bending motion in citrate synthase arising from normal mode calculations

Marques, Osni; Sanejouand, Yves‐Henri

doi:10.1002/prot.340230410

Cited by 192 publications

(204 citation statements)

References 24 publications

(1 reference statement)

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“…(Aj) and (⌬R) represent the corresponding root mean square values. The overlap O j describes the similarity between the direction of observed conformational change and the jth normal mode of the protein (29). It is defined:…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, the trajectory of protein motion will rarely be in a straight line, and therefore an otherwise correctly predicted initial direction of motion might deviate noticeably from the observed conformational change (22). Despite these limitations, many studies have found agreement between features of the motion predicted by NMA and the observed or simulated conformational change of one or a small number of proteins (23)(24)(25)(26)(27)(28)(29)(30). A number of large-scale studies have assessed the success of normal modes at describing protein motion as defined by the database of macromolecular movements (31).…”

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confidence: 99%

See 1 more Smart Citation

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Dobbins

Lesk²,

Sternberg³

2008

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

206

216

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Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 Å C␣ RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.conformational selection ͉ elastic network model ͉ induced fit ͉ protein interactions ͉ protein recognition P roteins are not static, and many undergo substantial rearrangements upon binding to other molecules (1). Such changes are central to protein function (2). The limitations of our understanding of conformational change impact markedly on our ability to model such changes. A successful approach to modeling protein flexibility, one of the key current challenges in developing protein-protein docking algorithms, would have far-reaching consequences for the fields of drug design and function prediction.The initial lock-and-key description of protein interaction, first introduced by Fischer in 1894 (3), did not account for conformational change and has since been modified, beginning with Koshland's induced fit hypothesis in 1958 (4). However, a range of studies including molecular dynamics (picosecondnanosecond time scales), NMR, and single-molecule FRET experiments (microsecond-millisecond time scales) (5-7), have questioned the extent to which conformational change can be considered induced by the binding partner.An alternative mechanism is conformational selection, where the native state of the protein exists in an ensemble of conformations, with the partner binding selectively to a specific conformation, thus shifting the equilibrium toward the binding conformation (8). An elaboration, proposed by Grunberg et al. (9), describes a three-stage process consisting of (i) independent diffusion of the receptor and ligand each subject to conformational fluctuations, (ii) an encounter between the receptor and ligand leading to a series of microcollisions that may result in the formation of a recognition complex, and (iii) either dissociation of the encounter complex or formation of the bound complex with possible further conformational changes resulting from induced fit. An important question to address is, therefore, ...

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Dobbins

Lesk²,

Sternberg³

2008

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

206

216

View full text Add to dashboard Cite

show abstract

“…This is a valid assumption especially for supermolecular complexes, in which the functionally important conformational changes, such as domain movements (3), are mediated by collective global deformational motions of the structure. As shown in numerous studies of the standard normal mode analysis (NMA) (4)(5)(6)(7)(8)(9)(10)(11)(12), the pathways of the functionally important conformational changes can be matched by the intrinsic low-energy deformational modes. Moreover, these collective global motions are not sensitive to the local connectivity of the molecular structure, instead, they are primarily influenced by the global shape and mass distribution of the molecule (13).…”

mentioning

confidence: 99%

How to describe protein motion without amino acid sequence and atomic coordinates

Ming

Kong

Lambert

et al. 2002

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

161

148

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This paper reports a computational method, the quantized elastic deformational model, that can reliably describe the conformational flexibility of a protein in the absence of the amino acid sequence and atomic coordinates. The essence of this method lies in the fact that, in modeling the functionally important conformational changes such as domain movements, it is possible to abandon the traditional concepts of protein structure (bonds, angles, dihedrals, etc.) and treat the protein as an elastic object. The shape and mass distribution of the object are described by the electron density maps, at various resolutions, from methods such as x-ray diffraction or cryo-electron microscopy. The amplitudes and directionality of the elastic deformational modes of a protein, whose patterns match the biologically relevant conformational changes, can then be derived solely based on the electron density map. The method yields an accurate description of protein dynamics over a wide range of resolutions even as low as 15-20 Å at which there is nearly no visually distinguishable internal structures. Therefore, this method dramatically enhances the capability of studying protein motions in structural biology. It is also expected to have ample applications in related fields such as bioinformatics, structural genomics, and proteomics, in which one's ability to extract functional information from the not-so-well-defined structural models is vitally important.conformational flexibility ͉ elastic deformation ͉ large conformational change ͉ elastic network ͉ normal mode analysis C omputational simulations of protein dynamics (1, 2) play an important role in deciphering protein functions in modern structural biology. To date, all the procedures for describing the motions of a protein require the knowledge of the atomic coordinates-i.e., the precise locations of the atoms. However, as the field of structural biology moves into an era of supermolecular complexes and membrane-bound proteins, there have been an increasing number of cases in which one can only obtain fuzzy images of the molecules by means of, for example, cryoelectron microscopy (cryo-EM). The knowledge of structures in these cases is not much more than the rough shapes of the molecules. Therefore, a challenging question is whether one can describe the motions of a protein, at least the gross features, based on its fuzzy image. The success of such a method would not only advance one's ability to model protein motions to a completely new level in structure biology, but it will also profoundly inf luence broader fields such as bioinformatics, structural genomics, and proteomics, in which one's ability to extract functional information from the not-so-well-defined structural models is vitally important.In the light of such a challenge, we developed a computational method, the quantized elastic deformational model (QEDM), by combining and extending several existing methods that were developed for related, but different, purposes. The results clearly demonstrate that, without the...

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“…[9][10][11] The dynamics is observed directly in multiple structures of the same, or similar proteins, as revealed by principal component analysis (PCA), 12 which shows close agreement with the elastic network models (ENMs). 8,[13][14][15][16][17][18][19][20][21] The ENMs have proven their ability to sample efficiently conformational space. Especially noteworthy has been their ability to agree with the conformational transition direction between two forms of the same protein.…”

Section: Introductionmentioning

confidence: 99%

Elastic network normal modes provide a basis for protein structure refinement

Gniewek

Koliński

Jernigan

et al. 2012

The Journal of Chemical Physics

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It is well recognized that thermal motions of atoms in the protein native state, the fluctuations about the minimum of the global free energy, are well reproduced by the simple elastic network models (ENMs) such as the anisotropic network model (ANM). Elastic network models represent protein dynamics as vibrations of a network of nodes (usually represented by positions of the heavy atoms or by the C α atoms only for coarse-grained representations) in which the spatially close nodes are connected by harmonic springs. These models provide a reliable representation of the fluctuational dynamics of proteins and RNA, and explain various conformational changes in protein structures including those important for ligand binding. In the present paper, we study the problem of protein structure refinement by analyzing thermal motions of proteins in non-native states. We represent the conformational space close to the native state by a set of decoys generated by the I-TASSER protein structure prediction server utilizing template-free modeling. The protein substates are selected by hierarchical structure clustering. The main finding is that thermal motions for some substates, overlap significantly with the deformations necessary to reach the native state. Additionally, more mobile residues yield higher overlaps with the required deformations than do the less mobile ones. These findings suggest that structural refinement of poorly resolved protein models can be significantly enhanced by reduction of the conformational space to the motions imposed by the dominant normal modes.

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Hinge‐bending motion in citrate synthase arising from normal mode calculations

Cited by 192 publications

References 24 publications

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

How to describe protein motion without amino acid sequence and atomic coordinates

Elastic network normal modes provide a basis for protein structure refinement

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