Flexible Multi-scale Fitting of Atomic Structures into Low-resolution Electron Density Maps with Elastic Network Normal Mode Analysis

Tama, Florence; Miyashita, Osamu; Brooks, Charles L.

doi:10.1016/j.jmb.2004.01.048

Cited by 215 publications

(244 citation statements)

References 49 publications

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“…solved through x-ray crystallography) and R c is a distance cutoff that specifies which pairs of nodes are interacting. Note that k 4 = 0 corresponds to the widely used elastic network model (ENM) [41][42][43], which has proven useful for quantitatively describing amino acid fluctuations at room temperature [41,42,44,45], as well as for predicting or characterizing large-amplitude functional motions of proteins [46][47][48][49][50] in agreement with all-atom models [51][52][53], paving the way for numerous applications in structural biology [54][55][56][57].…”

Section: Methodsmentioning

confidence: 99%

Long-range energy transfer in proteins

Piazza

Sanejouand

2009

Phys. Biol.

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Proteins are large and complex molecular machines. In order to perform their function, most of them need energy, e.g. either in the form of a photon, as in the case of the visual pigment rhodopsin, or through the breaking of a chemical bond, as in the presence of adenosine triphosphate (ATP). Such energy, in turn, has to be transmitted to specific locations, often several tens ofÅ away from where it is initially released. Here we show, within the framework of a coarse-grained nonlinear network model, that energy in a protein can jump from site to site with high yields, covering in many instances remarkably large distances. Following single-site excitations, few specific sites are targeted, systematically within the stiffest regions. Such energy transfers mark the spontaneous formation of a localized mode of nonlinear origin at the destination site, which acts as an efficient energy-accumulating center. Interestingly, yields are found to be optimum for excitation energies in the range of biologically relevant ones.

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Section: Methodsmentioning

confidence: 99%

Long-range energy transfer in proteins

Piazza

Sanejouand

2009

Phys. Biol.

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“…23 The final Ca trace obtained was refitted to the cryoEM density manually using Chimera. 22 The Ca trace was then refined to produce a full atomic structure.…”

Section: Fitting Of Cryoem Density Map Into Negative Stain Density Mapmentioning

confidence: 99%

Three dimensional structure of the anthrax toxin translocon–lethal factor complex by cryo‐electron microscopy

et al. 2013

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We have visualized by cryo-electron microscopy (cryo-EM) the complex of the anthrax protective antigen (PA) translocon and the N-terminal domain of anthrax lethal factor (LF N ) inserted into a nanodisc model lipid bilayer. We have determined the structure of this complex at a nominal resolution of 16 Å by single-particle analysis and three-dimensional reconstruction. Consistent with our previous analysis of negatively stained unliganded PA, the translocon comprises a globular structure (cap) separated from the nanodisc bilayer by a narrow stalk that terminates in a transmembrane channel (incompletely distinguished in this reconstruction). The globular cap is larger than the unliganded PA pore, probably due to distortions introduced in the previous negatively stained structures. The cap exhibits larger, more distinct radial protrusions, previously identified with PA domain three, fitted by elements of the NMFF PA prepore crystal structure. The presence of LF N , though not distinguished due to the seven-fold averaging used in the reconstruction, contributes to the distinct protrusions on the cap rim volume distal to the membrane. Furthermore, the lumen of the cap region is less resolved than the unliganded negatively stained PA, due to the low contrast obtained in our images of this specimen. Presence of the LF N extended helix and N terminal unstructured regions may also contribute to this additional internal density within the interior of the cap. Initial NMFF fitting of the cryoEM-defined PA pore cap region positions the Phe clamp region of the PA pore translocon directly above an internal vestibule, consistent with its role in toxin translocation.

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“…Large deformations can, however, lead to sidechain distortions and thus there is need for a sidechain rebuilding step. Normal modes have also been applied to the optimization of complexes against electron density maps [42,43] and the refinement of protein-DNA models [44]. Such approaches should lead to improved docking results, provided that the identified modes are relevant to the binding process; this is again related to our ability to predict motions.…”

Section: Describing Large Conformational Changes In Dockingmentioning

confidence: 99%

Flexible protein–protein docking

Bonvin

2006

Current Opinion in Structural Biology

277

225

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Predicting the structure of protein-protein complexes using docking approaches is a difficult problem whose major challenges include identifying correct solutions, and properly dealing with molecular flexibility and conformational changes. Flexibility can be addressed at several levels: implicitly, by smoothing the protein surfaces or allowing some degree of interpenetration (soft docking) or by performing multiple docking runs from various conformations (cross or ensemble docking); or explicitly, by allowing sidechain and/or backbone flexibility. Although significant improvements have been achieved in the modeling of sidechains, methods for the explicit inclusion of backbone flexibility in docking are still being developed. A few novel approaches have emerged involving collective degrees of motion, multicopy representations and multibody docking, which should allow larger conformational changes to be modeled. IntroductionGiven the increased focus on interactions in the current post-genomic era, structural knowledge of complexes is required to understand how the various biomolecular units work together to fulfill their tasks. The number of expected biomolecular complexes will, however, exceed the number of proteins in a proteome by at least one order of magnitude; a significant fraction of these will be extremely difficult to study using classical structural methods such as NMR and X-ray crystallography. Therefore, the importance of computational approaches such as docking, the process of predicting the three-dimensional structure of a complex based on its known constituents, is evident. Unfortunately, predicting the structure of protein-protein complexes is a difficult problem, with major challenges that include identifying correct solutions, and properly dealing with flexibility and conformational changes. In this review, recent progress in the latter area will be addressed.To monitor the performance of current docking methods, CAPRI (Critical Assessment of Predicted Interactions), a community-wide blind docking experiment, has been established (http://capri.ebi.ac.uk). The recent CAPRI results [1 ] indicate that, although for 'easy' targets that show only small backbone conformational changes, excellent predictions can be obtained by the modeling community as whole, targets for which conformational changes take place upon binding are extremely challenging (even for backbone RMSD changes as small as 2 Å !). Initially, most protein-protein docking approaches have been developed based on rigid-body docking algorithms, thus ignoring any conformational change that might occur upon binding. However, the realization of the importance of flexibility in docking is leading to new developments. Flexibility can be introduced at several levels: implicitly, by smoothing the protein surfaces or allowing some degree of interpenetration (soft docking) or by performing multiple docking runs from various conformations (cross or ensemble docking); or explicitly, by allowing sidechain and/or backbone flexibility, either during...

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Flexible Multi-scale Fitting of Atomic Structures into Low-resolution Electron Density Maps with Elastic Network Normal Mode Analysis

Cited by 215 publications

References 49 publications

Long-range energy transfer in proteins

Long-range energy transfer in proteins

Three dimensional structure of the anthrax toxin translocon–lethal factor complex by cryo‐electron microscopy

Flexible protein–protein docking

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