Bacterial Polypeptide Release Factor RF2 Is Structurally Distinct from Eukaryotic eRF1

Vestergaard, Bente; Van, Lan B.; Andersen, G.R.; Nyborg, Jens; Buckingham, Richard H.; Kjeldgaard, Morten

doi:10.1016/s1097-2765(01)00415-4

Cited by 194 publications

(233 citation statements)

References 21 publications

(4 reference statements)

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“…Grids containing E. coli 70S ribosomes were generated as described previously (Vestergaard et al, 2001). Micrographs were collected under low-dose conditions on an FEI Tecnai F20 at a nominal magnification of 49,700, with defocus values ranging from 1.1 to 3.1 µm underfocus, and digitized on a Z/I scanner (Huntsville, AL) at a step size of 14 µm, corresponding to a pixel size of 2.82 Å.…”

Section: Methodsmentioning

confidence: 99%

Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification

Shaikh

Trujillo

LeBarron

et al. 2008

Journal of Structural Biology

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As collection of electron microscopy data for single-particle reconstruction becomes more efficient, due to electronic image capture, one of the principal limiting steps in a reconstruction remains particle verification, which is especially costly in terms of user input. Recently, some algorithms have been developed to window particles automatically, but the resulting particle sets typically need to be verified manually. Here we describe a procedure to speed up verification of windowed particles using multivariate data analysis and classification. In this procedure, the particle set is subjected to multireference alignment before the verification. The aligned particles are first binned according to orientation and are binned further by K-means classification. Rather than selection of particles individually, an entire class of particles can be selected, with an option to remove outliers. Since particles in the same class present the same view, distinction between good and bad images becomes more straightforward. We have also developed a graphical interface, written in Python/Tkinter, to facilitate this implementation of particle-verification. For the demonstration of the particleverification scheme presented here, electron micrographs of ribosomes are used.

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Section: Methodsmentioning

confidence: 99%

Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification

Shaikh

Trujillo

LeBarron

et al. 2008

Journal of Structural Biology

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“…in its native open, tri-lobed conformation ( Figure 4A), which is in contrast to the closed conformation that it exhibits in its unbound crystal structure [55][56][57][58]. The conserved GGQ amino-acid motif that is essential to peptidyl-tRNA hydrolysis is located at the distal end of domain 3 [59,60], whereas the SPF loop that is essential to stop codon recognition is located in domains 2 and 4, which form a compact super-domain [54].…”

Section: Ribosome-bound Termination Factor Rf2mentioning

confidence: 99%

Conformational dynamics of supramolecular protein assemblies

Kim

Nguyen

Bathe

2011

Journal of Structural Biology

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Supramolecular protein assemblies including molecular motors, cytoskeletal filaments, chaperones, and ribosomes play a central role in a broad array of cellular functions ranging from cell division and motility to RNA and protein synthesis and folding. Single-particle reconstructions of such assemblies have been growing rapidly in recent years, providing increasingly high resolution structural information under native conditions. While the static structure of these assemblies provides essential insight into their mechanism of biological function, their dynamical motions provide additional important information that cannot be inferred from structure alone. Here we present an unsupervised computational framework for the analysis of high molecular weight assemblies and use it to analyze the conformational dynamics of structures deposited in the Electron Microscopy Data Bank. Protein assemblies are modeled using a recently introduced coarse-grained modeling framework based on the finite element method, which is used to compute equilibrium thermal fluctuations, elastic strain energy distributions associated with specific conformational transitions, and dynamical correlations in distant molecular domains. Results are presented in detail for the ribosome-bound termination factor RF2 from Escherichia coli, the nuclear pore complex from Dictyostelium discoideum, and the chaperonin GroEL from E. coli. Elastic strain energy distributions reveal hinge-regions associated with specific conformational change pathways, and correlations in collective molecular motions reveal dynamical coupling between distant molecular domains that suggest new, as well as confirm existing, allosteric mechanisms. Results are publically available for use in further investigation and interpretation of biological function including cooperative transitions, allosteric communication, and molecular mechanics, as well as in further classification and refinement of electron microscopy based structures.

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“…What of the bacterial decoding RFs? After many unsuccessful attempts by several groups, a structure of a bacterial factor (RF2) was finally published in 2001 [15]. Highly surprising was that it did not resemble the human eRF1 structure, nor was it tRNA-like, but rather it was considerably more compact.…”

Section: Is the Decoding Rf A Trna Mimic?mentioning

confidence: 99%

“…One radioactive peptide was identified and shown to contain the sequence DIQ. This placed the crosslink within the a5 helix region of RF2 [15] towards the N terminus of the molecule (131-133), somewhat distant from the SPF motif (207-209) identified by Ito et al [28] as discriminatory at the second and third bases of the stop codon, but closer to the site of a number of charge-switch mutations that result in relaxed codon recognition [34,35]. Nevertheless, we did not publish details of the crosslink site on the RF since there was no supporting biochemical evidence or a contextual biological explanation.…”

Section: How Do the Bacterial Rfs Function At The Decoding Site?mentioning

confidence: 99%

“…The decoding RF seems not to use the same escape route but rather a complex mechanism to 'back out' of the A site by the route it entered with the help of a second class of RF and guanine nucleotide. Interestingly, not only has this mechanism uniquely different features in eukaryotes and prokaryotes [13] but also the eukaryotic decoding factor (eRF1) [14] and prokaryotic factors [15][16][17] are structurally distinct. This implies that the termination mechanism involving these extrinsic factors might have evolved more than once and the similarities observed today are an example of convergent evolution.…”

Section: Introductionmentioning

confidence: 99%

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Accommodating the bacterial decoding release factor as an alien protein among the RNAs at the active site of the ribosome

et al. 2007

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The decoding release factor (RF) triggers termination of protein synthesis by functionally mimicking a tRNA to span the decoding centre and the peptidyl transferase centre (PTC) of the ribosome. Structurally, it must fit into a site crafted for a tRNA and surrounded by five other RNAs, namely the adjacent peptidyl tRNA carrying the completed polypeptide, the mRNA and the three rRNAs. This is achieved by extending a structural domain from the body of the protein that results in a critical conformational change allowing it to contact the PTC. A structural model of the bacterial termination complex with the accommodated RF shows that it makes close contact with the first, second and third bases of the stop codon in the mRNA with two separate loops of structure: the anticodon loop and the loop at the tip of helix a5. The anticodon loop also makes contact with the base following the stop codon that is known to strongly influence termination efficiency. It confirms the close contact of domain 3 of the protein with the key RNA structures of the PTC. The mRNA signal for termination includes sequences upstream as well as downstream of the stop codon, and this may reflect structural restrictions for specific combinations of tRNA and RF to be bound onto the ribosome together. An unbiased SELEX approach has been investigated as a tool to identify potential rRNA-binding contacts of the bacterial RF in its different binding conformations within the active centre of the ribosome.

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Bacterial Polypeptide Release Factor RF2 Is Structurally Distinct from Eukaryotic eRF1

Cited by 194 publications

References 21 publications

Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification

Particle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification

Conformational dynamics of supramolecular protein assemblies

Accommodating the bacterial decoding release factor as an alien protein among the RNAs at the active site of the ribosome

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