Structural insights into cognate versus near-cognate discrimination during decoding
2011; Springer Nature; Volume: 30; Issue: 8 Linguagem: Inglês
10.1038/emboj.2011.58
ISSN1460-2075
AutoresXabier Agirrezabala, Eduard Schreiner, Leonardo G. Trabuco, Jianlin Lei, Rodrigo F. Ortiz‐Meoz, Klaus Schulten, Rachel Green, Joachim Frank,
Tópico(s)Machine Learning in Bioinformatics
ResumoArticle4 March 2011free access Structural insights into cognate versus near-cognate discrimination during decoding Xabier Agirrezabala Xabier Agirrezabala Structural Biology Unit, CIC-bioGUNE, Derio, Basque Country, Spain Search for more papers by this author Eduard Schreiner Eduard Schreiner Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA Search for more papers by this author Leonardo G Trabuco Leonardo G Trabuco Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USAPresent address: Cell Networks, University of Heidelberg, 69120 Heidelberg, Germany Search for more papers by this author Jianlin Lei Jianlin Lei MOE Key Laboratory of Bioinformatics, Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China Search for more papers by this author Rodrigo F Ortiz-Meoz Rodrigo F Ortiz-Meoz Department of Molecular Biology and Genetics, HHMI, Johns Hopkins University School of Medicine, Baltimore, MD, USA Search for more papers by this author Klaus Schulten Klaus Schulten Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA Search for more papers by this author Rachel Green Rachel Green Department of Molecular Biology and Genetics, HHMI, Johns Hopkins University School of Medicine, Baltimore, MD, USA Search for more papers by this author Joachim Frank Corresponding Author Joachim Frank Department of Biochemistry and Molecular Biophysics, HHMI, Columbia University, New York, NY, USA Department of Biological Sciences, Columbia University, New York, NY, USA Search for more papers by this author Xabier Agirrezabala Xabier Agirrezabala Structural Biology Unit, CIC-bioGUNE, Derio, Basque Country, Spain Search for more papers by this author Eduard Schreiner Eduard Schreiner Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA Search for more papers by this author Leonardo G Trabuco Leonardo G Trabuco Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USAPresent address: Cell Networks, University of Heidelberg, 69120 Heidelberg, Germany Search for more papers by this author Jianlin Lei Jianlin Lei MOE Key Laboratory of Bioinformatics, Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China Search for more papers by this author Rodrigo F Ortiz-Meoz Rodrigo F Ortiz-Meoz Department of Molecular Biology and Genetics, HHMI, Johns Hopkins University School of Medicine, Baltimore, MD, USA Search for more papers by this author Klaus Schulten Klaus Schulten Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA Search for more papers by this author Rachel Green Rachel Green Department of Molecular Biology and Genetics, HHMI, Johns Hopkins University School of Medicine, Baltimore, MD, USA Search for more papers by this author Joachim Frank Corresponding Author Joachim Frank Department of Biochemistry and Molecular Biophysics, HHMI, Columbia University, New York, NY, USA Department of Biological Sciences, Columbia University, New York, NY, USA Search for more papers by this author Author Information Xabier Agirrezabala1, Eduard Schreiner2, Leonardo G Trabuco2,3, Jianlin Lei4, Rodrigo F Ortiz-Meoz5, Klaus Schulten2,6, Rachel Green5 and Joachim Frank 7,8 1Structural Biology Unit, CIC-bioGUNE, Derio, Basque Country, Spain 2Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA 3Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA 4MOE Key Laboratory of Bioinformatics, Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China 5Department of Molecular Biology and Genetics, HHMI, Johns Hopkins University School of Medicine, Baltimore, MD, USA 6Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA 7Department of Biochemistry and Molecular Biophysics, HHMI, Columbia University, New York, NY, USA 8Department of Biological Sciences, Columbia University, New York, NY, USA *Corresponding author. Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, 630 168th Street, P&S Black Building 2-221, New York, NY 10032, USA. Tel.: +1 212 305 9510; Fax: +1 212 305 9500; E-mail: [email protected] The EMBO Journal (2011)30:1497-1507https://doi.org/10.1038/emboj.2011.58 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info The structural basis of the tRNA selection process is investigated by cryo-electron microscopy of ribosomes programmed with UGA codons and incubated with ternary complex (TC) containing the near-cognate Trp-tRNATrp in the presence of kirromycin. Going through more than 350 000 images and employing image classification procedures, we find ∼8% in which the TC is bound to the ribosome. The reconstructed 3D map provides a means to characterize the arrangement of the near-cognate aa-tRNA with respect to elongation factor Tu (EF-Tu) and the ribosome, as well as the domain movements of the ribosome. One of the interesting findings is that near-cognate tRNA's acceptor stem region is flexible and CCA end becomes disordered. The data bring direct structural insights into the induced-fit mechanism of decoding by the ribosome, as the analysis of the interactions between small and large ribosomal subunit, aa-tRNA and EF-Tu and comparison with the cognate case (UGG codon) offers clues on how the conformational signals conveyed to the GTPase differ in the two cases. Introduction The translation of the genetic code into proteins is a task carried out universally, and with high fidelity, by the ribosome. The decoding process relies on the complementary Watson-Crick base matching between the codon of the messenger RNA (mRNA) and the anticodon of the incoming aminoacyl-tRNA (aa-tRNA), delivered to the ribosome in a ternary complex (TC) with GTP and the GTPase elongation factor Tu (EF-Tu). For the required accuracy to be achieved, the ribosome must recognize the cognate aa-tRNA species and reject those near- and non-cognate species that form non-Watson-Crick pairing interactions with the mRNA (one and at least two mismatches, respectively). The ability of the protein synthesis machinery to differentiate between these species is fundamental to protein synthesis in all life forms. While the difference in free energy of binding between cognate and non-cognate aa-tRNAs is large enough, this difference is not sufficiently large to discriminate cognate versus near-cognate species. Moreover, we know that the events leading to discrimination must take place on a relatively fast time scale that is commensurate with the known rates of protein synthesis (Zaher and Green, 2009). This conundrum was resolved when kinetic studies showed that the ribosomal machinery uses a kinetic discrimination process to exclusively accelerate the two major steps of tRNA selection, GTPase activation and accommodation, for cognate aa-tRNA species (Pape et al, 1998, 1999; Blanchard et al, 2004; Gromadski and Rodnina, 2004; Cochella and Green, 2005; Gromadski et al, 2006), thus promoting rapid and high-fidelity tRNA selection. The differences in forward rates are attributed to an induced-fit mechanism (Pape et al, 1999), wherein instrumental conformational changes are induced only by binding of the cognate species. Some of these rearrangements have been characterized by structural approaches. First, a number of cryo-electron microscopy (cryo-EM) studies established (Stark et al, 2002; Valle et al, 2002, 2003; Li et al, 2008; Schuette et al, 2009; Villa et al, 2009) that the incoming cognate aa-tRNA is deformed, relative to the X-ray structure of free tRNA, during the early steps of tRNA selection before EF-Tu:GDP is released (in a state referred to as A/T). The details of this particular distortion of the tRNA have recently been confirmed by the first crystal structure of ribosome-bound TC (Schmeing et al, 2009). The deformation is characterized by a partial bending of the tRNA structure that permits interaction between the anticodon of the tRNA and the mRNA in the decoding centre while the aa-tRNA is still bound to EF-Tu. Second, X-ray crystallography of 30S subunits soaked with anticodon stem loops (ASLs) has demonstrated that the cognate codon–anticodon match triggers localized changes in the universally conserved G530, A1492 and A1493 of the 16S rRNA (Ogle et al, 2001). These nucleotides strictly monitor the Watson-Crick complementarity between the codon and the anticodon at the first two positions, but not the third (i.e. the wobble position). In addition to these local rearrangements, global concerted changes in the head and shoulder regions of the 30S subunit also appear to be triggered upon cognate codon–anticodon pairing. These conformational changes result in an overall more closed conformation of the 30S subunit (Ogle et al, 2002). Despite these many insights, a complete understanding of the structural basis for the induced-fit mechanism remains elusive, as fully functional 70S ribosomes in complex with near-cognate TCs have not been visualized to date. To address this issue, we have determined the structure of Escherichia coli ribosomes programmed with a near-cognate codon by means of cryo-EM single-particle reconstruction. Comparison with a ribosome complex programmed with the cognate species provides structural evidence that the near-cognate aa-tRNA is differently positioned. We further describe how the structural differences affect EF-Tu positioning and the structural context of the ribosome, ultimately bringing about high-fidelity discrimination. Results Overview of the structures Cryo-EM maps were generated from ribosomes programmed with an AUG codon in the P site and either a cognate (UGG) or near-cognate (UGA/stop) codon in the A site. These ribosome complexes were subsequently loaded with fMet-tRNAfMet and kirromycin-stalled TCs, Trp-tRNATrp•EF-Tu•GTP (see Materials and methods section). Kirromycin arrests the TC on the ribosome after the hydrolysis of GTP, but before the conformational change that takes place in EF-Tu (Parmeggiani and Swart, 1985). The study of this kirromycin-arrested conformer is of particular importance because the antibiotic is thought to lock EF-Tu in a state that resembles the earlier, pre-hydrolysis GTPase-activated state (Rodnina et al, 1994). This state is regarded as a state that comes after, but is still very close to, the GTP hydrolysis transition state. All the complexes were prepared at low Mg2+ concentration (3.5 mM) as it is well documented that excess amounts of Mg2+ increase the errors of decoding, thus altering the overall selectivity of the process (Gromadski et al, 2006). Due to the expected lower stability and higher dissociation rates of the tRNA in the near-cognate codon situation (Rodnina et al, 1996), which leads to decreased levels of A/T-site occupancy, we applied supervised classification methodology to sort the original data set into two major subsets (see Materials and methods section). To minimize any risk of reference bias in the final structures, the selected particles were then re-aligned using the map of an ‘empty’ ribosome (i.e. without TC and P-site tRNA) as a starting reference and refined iteratively during multiple rounds. This procedure allows structures to be obtained that diverge from the initial references due to the intrinsic structural information contained in the corresponding subsets. The first group (shown in Figure 1C) was composed of merely ∼8% of the initial particle set, and corresponded to ribosomes with A/T-bound near-cognate TCs (Figure 1C), similar to those shown in the cognate case (Figure 1B). The second group, composed of the remaining 92%, corresponded to ribosomes bearing a single tRNA in the P site (i.e. without A/T-bound TC in the A site) (Figure 1D). The conformation of this latter reconstructed ribosome was found to be virtually identical to that of the initiation 70S ribosome with the initiator P-site fMet-tRNAfMet generated as a control (Figure 1A). The final resolution of the maps was 8.25 Å (TC on cognate codon), 13.2 Å (TC on near-cognate codon), 8.05 Å (vacant near-cognate A site) and 8.65 Å (initiation-like 70S ribosome). Resolution was determined by 0.5 cutoff in the Fourier shell correlation (Supplementary Figure S1). Figure 1.Three-dimensional cryo-EM structures of 70S ribosomes. Cryo-EM densities are shown for the small (yellow) and large (blue) subunits, A/T- and P-site tRNAs (magenta and green, respectively) and EF-Tu (red). (A) Initiation 70S ribosome. Ribosomes bearing ternary complexes (B) with cognate codon and (C) with near-cognate codon. (D) Initiation-like ribosomes showing a vacant A site. Labels and landmarks: sp (spur), h (head), sh (shoulder), pt (platform), CP (central protuberance), L1 (L1 stalk), L7/L12 (L7/L12 stalk), h44 (small subunit helix 44), SRL (large subunit sarcin-ricin loop), GAC (GTPase-associated centre), H69 (large subunit helix 69), s12 (small subunit protein 12). Download figure Download PowerPoint In the reconstructions displayed in Figure 1, the densities of the TCs both for cognate (Figure 1B) and near-cognate (Figure 1C) species show EF-Tu bound to the base of the L7/L12 stalk of the large subunit, in proximity to the universally conserved α-sarcin-ricin loop (SRL; formed by helix H95 of the 23S rRNA), while the aa-tRNA binds to the GTPase-associated centre (GAC; formed by L11 and 58 nucleotides from H43 and H44) and H69 through its T loop (elbow region) and D arm, respectively. In the 30S subunit, the TCs interact with the shoulder region and helices h4, h5 and h15 of the 16S rRNA (note convention designating helices of 23S rRNA by ‘H’ and those of 16S rRNA by ‘h’). Ribosomal protein S12 is consistently visualized interacting with cognate and near-cognate tRNA species in the vicinity of the D stem. In both cognate and near-cognate cases, the tRNA contacts the tip of h44 (i.e. the decoding centre) via its anticodon region, but the interaction appears distinct in the near-cognate case. While the resolution of the reconstruction precluded any detailed characterization of the decoding site interactions based on the density alone, the flexibly fitted atomic models of the complexes show differences in the decoding centre (data to be introduced below). It is noteworthy that, in our 3D reconstruction, the acceptor stem of the near-cognate tRNA is not as well defined as the ASL, indicating some degree of flexibility (see Figure 2B and C). In addition, the structure is apparently completely disordered at the very 3′ CCA end, as the ultimate string of nucleotides forming the tRNA structure is completely blurred in the experimental density map. These apparent differences summarized here do persist when the two structures are displayed at the same resolution, ∼13.5 Å (Supplementary Figure S2). Figure 2.Interaction of ternary complexes with the ribosome. Cryo-EM densities are shown for the small (yellow), A/T- and P-site tRNAs (magenta and green, respectively) and EF-Tu (red). Small subunits bearing ternary complexes on (A) cognate and (B) near-cognate codons. Superimposition of the experimental cryo-EM densities corresponding to (C) A/T-tRNA and (D) EF-Tu on cognate and near-cognate codons. Cognate tRNA and EF-Tu are shown in grey, whereas near-cognate tRNA and EF-Tu are displayed in magenta and red, respectively (see coloured labels). The star in (B) indicates the missing CCA region of the near-cognate tRNA. Labels and landmarks: acceptor stem, T arm and ASL of tRNA, domains I, II and III of EF-Tu. All other labels are introduced in Figure 1. The orientation of the subunit is shown as a thumbnail on the left. Download figure Download PowerPoint The structures reveal distinct conformations of A/T-tRNA and EF-Tu To adopt the A/T state of binding, the tRNA must be distorted at its ASL. The superimposition of cryo-EM densities (Figure 2C) reveals that the A/T-tRNA in near-cognate complexes differs from that seen in the cognate case. First, the hinge region at the junction of the ASL and D stems exhibits a different arrangement. Second, there are differences in the T- and D-loop regions. These changes bring the resolved part of the near-cognate tRNA's acceptor stem into a different geometry at the binding interface with EF-Tu. To further analyse the results, we built atomic models from the experimental cryo-EM maps using molecular dynamics-based flexible fitting (MDFF) (Trabuco et al, 2008) (described in the Materials and methods section). This allowed us to interpret our density maps in molecular terms to the extent allowed by the resolution. For the comparison of tRNA conformations, structures resulting from MDFF refinements in water were used, since the secondary structure restraints necessary for MDFF performed in vacuo preclude local rearrangements. This approach permitted movements within the tRNA bodies to be more accurately characterized. In Figure 3A, we show the atomic models inferred for both TCs. We see for the near-cognate complex that the tRNA density is partially blurred, indicating the tRNA is more dynamic. In particular, the positions of the terminal portion of the acceptor stem and the 3′ CCA sequence cannot be determined unambiguously. In contrast, the density corresponding to EF-Tu in the near-cognate cryo-EM map is well defined, delineating the location of domains and secondary structure and allowing a meaningful three-dimensional model to be built (Figure 3B and C). Figure 3.Fitting of atomic structures into the cryo-EM densities for the stalled ternary complexes. (A) Cryo-EM densities are shown for cognate and near-cognate A/T and EF-Tu in transparent magenta (tRNA) and grey/red (for cognate and near-cognate EF-Tu, respectively). The fitted structures are shown in ribbons. (B) Close-up view of superimposed fitted structures for cognate (coloured by domains) and near-cognate EF-Tu (in red). (C) Stereo-view representation of EF-Tu structures. Cognate EF-Tu fragments 1–202 (domain I), 203–300 (domain II) and 301–393 (domain III) are shown in cyan, green and yellow, respectively. Switch I, II and P loop of domain I are represented in darker blue. Fragments 219–226 and 256–273 of domain II are represented in darker green. The position of residues Val20, Ile60 and His84 is highlighted for comparison in both fitted structures. The EF-Tu complexes are aligned with respect to the 70S ribosomes. Supplementary Figure S3 depicts the stereo-view representation of the same EF-Tu complexes but aligned with respect to each other. Download figure Download PowerPoint The superimposition of the ASL part of the A/T-tRNA shows that the overall ASL structure is similar for the cognate and near-cognate cases, but there are clear differences in the details. An interesting observation is that codon–anticodon interactions remain stable throughout the entire fitting process for the cognate maps, but break apart at the third basepair position already at the very beginning of the fitting for the near-cognate map (Figure 4A). Moreover, a reorganization of the T and D loops can be seen (Figure 4B). In particular, the D stem is shifted closer to the ASL (distances between phosphorus atoms of residues 11 and 27 are 9 and 13 Å for cognate and near-cognate complexes, respectively) and the T loop shifts away from the D loop in the near-cognate complex (distances between phosphorus atoms of residues 18 and 56 are 11 and 18 Å for cognate and near-cognate complexes, respectively). Apart from the shift of the T loop, the internal structure of the acceptor stem in the cognate and near-cognate complexes is similar. The largest differences are observed in the 3′ terminal part, though since this region is not resolved in the near-cognate complex, no rigorous comparison is possible. Figure 4.Comparison of the modelled A/T-tRNA in cognate and near-cognate complexes. (A) The superimposition of the ASL shows the basepair at the third position of the decoding minihelix (grey cylinders) in the cognate case (shown in cyan), which is disrupted in the near-cognate complex (shown in magenta). The alignment of the two structures was performed using the backbone atoms of tRNA residues 31–39. (B) Superimposition of the full tRNAs shows the differences in the elbow region between cognate and near-cognate case. Atoms used for calculation of internal distances are shown as spheres. The blue sphere corresponds to residue 56 in the T loop, while the red sphere shows residue 11 in the D loop. The calculated distance is indicated by a cylinder at the reference point, which is residue 18 and 27 for the T and D loop, respectively. The alignment of the structures was performed using the backbone of the resolved part of the tRNA, that is residues 1–70. Download figure Download PowerPoint The relative orientation between the various EF-Tu domains in the present structures is similar to that seen in the previously characterized GTP-bound form (Abel et al, 1996; Polekhina et al, 1996). However, due to the high flexibility of the acceptor stem in the near-cognate complex and subsequent modification of the interface between the aa-tRNA and EF-Tu, several changes are noticeable (Figures 2D and 3C; Supplementary Figure S3). In domain I, there are two main features to be noticed. First, the reconstructions show that the density corresponding to switch I (the effector loop, residues 40–62) is not completely resolved, suggesting its dynamic nature. It is worth noting that this region is better represented in the near-cognate than in the cognate complex when the maps are displayed at low threshold (data not shown). In addition, the atomic models suggest, supported by experimental density between residues 55 and 62 in both cases, that the switch I is positioned closer to the rest of domain I in the near-cognate case (Figure 3B). Considering that the P loop containing residue 20 is kept in place by the SRL in an identical manner in both complexes, this shift renders the ‘hydrophobic gate’ (formed by residues 20 and 60 and thought to control the access of the conserved catalytic His84 to GTP) (see Daviter et al (2003) and references therein) more closed in the near-cognate than in the cognate case (distance between residues forming the gate is 14 and 19 Å, respectively). Nevertheless, the gate is still more open in the near-cognate case than in the isolated TC (8 Å, PDB 1OB2), which may explain the reduced but still measurable rate of GTP hydrolysis of near-cognate species. We note that these results are qualitative due to the limited resolution of the EM data, and it is likely that the ribosome populations on which the reconstructions are based are to some extent heterogeneous with regards to the switch I position. Our results are nevertheless worth bringing into this forum as a contribution to the discussion. The switch II region (containing the critical His84 and extending from residues 80–100) is also distinctly structured in cognate versus near-cognate species. The differences in the orientation and positioning of the region of switch II are particularly well seen for the junction between domains I and III (see Figure 2D), and they probably reflect the higher flexibility/freedom of the switch II region in the near-cognate complex in the absence of a correctly structured acceptor stem. Indeed, cryo-EM and X-ray data have shown that upon binding to the ribosome the switch II loop is shifted toward the tRNA's acceptor stem (Schmeing et al, 2009; Villa et al, 2009). Our fitted structures show that residue Asp86 in particular moves by about 5 Å, inserting itself between the SRL and the acceptor stem of the tRNA in the near-cognate complex. This observation would be consistent with the more dynamic properties of the acceptor stem in the near-cognate case. However, we cannot exclude the possibility that this observed shift in the inferred model is an artifact of MDFF fitting in areas of the density affected by conformational averaging: the tRNA density is poorly resolved in this region for the near-cognate complex, so it may be that the residues around Asp86 were drawn into the density between the SRL and the acceptor stem. Finally, while domain III in the near-cognate case is rotated counter-clockwise when compared with its cognate counterpart, domain II, the region interacting with the 16S rRNA, displays no major rearrangements when aligned (see Supplementary Figure S3). Atomic data suggest that local changes in domain II may be implicated in GTPase activation (Schmeing et al, 2009), as residues 256–273 and 219–226, composing a β loop and presenting the highly conserved Gly222 (Vorstenbosch et al, 1996), shift toward the small subunit when compared with their position in solution. The conformation of domain II in our fitted structures is very similar as the same residues are found to interact with the 16S rRNA region formed by helices h4, h5 and h15. Exploring the domain closure of the small subunit As previously mentioned, initial X-ray crystallography of the 30S subunit identified local changes in the decoding centre that result in more global conformational changes. These large-scale movements of the head and shoulder, referred to as domain closure, involve the rotation of the head and shoulder toward the subunit interface where decoding takes place (Ogle et al, 2002). During this rearrangement, new contacts between S12 and 16S rRNA (h44 and h27) are formed. To investigate whether the binding of near-cognate TCs changes the global conformation of the small subunit, we compared the structures of cognate and near-cognate decoding 30S subunits by superimposing the relevant cryo-EM densities. The results presented in Figure 5A indicate that changes in the relative position of the head and shoulder regions of the small subunit occur only in the cognate situation. Figure 5.Domain closure and GAC movement during aa-tRNA incorporation. Cryo-EM densities are shown for the small (A) and large subunits (B). From left to right, close-up views of the superimposed cryo-EM densities from (i) initiation ribosome (30S and 50S subunits shown in yellow and blue, respectively) and ribosome bearing cognate (grey) ternary complex, (ii) initiation ribosome and ribosome bearing near-cognate (purple) ternary complex (see coloured labels) and (iii) ribosomes bearing cognate (grey) and near-cognate (purple) ternary complexes. Download figure Download PowerPoint To further analyse and quantify the details of the domain closure motion, we also compared the extent of this rearrangement for several existing X-ray structures with the atomic models inferred from our cryo-EM reconstructions (Table I). In particular, we considered the structures of the isolated 30S subunit, either in its apo form (Ogle et al, 2001) or in complex with cognate, near-cognate and non-cognate tRNA ASLs (Ogle et al, 2001, 2002). In addition, we analysed the structures of 70S ribosomes with an empty A site (Korostelev et al, 2006) or in complex with either A/T- (Schmeing et al, 2009) or A/A-tRNAs (Selmer et al, 2006). Tensors of inertia were computed for individual domains of the small subunit (see Materials and methods section and Supplementary Figure S4), which enabled us to characterize the movements of the body with respect to the platform (BPlopcl), tilt of the head domain towards the subunit interface (Htilt), opening/closing of the head relative to the shoulder (Hopcl) and swiveling of the head domain (Hswiv). We note that the variations in the values of the measured domain motions are large, even within the set of X-ray structures. However, the trends of motion, that is, which of the complexes is more closed or more open, is a robust descriptor. Table 1. Measurements of 30S subunit domain displacements PDB BPlopcl Htilt Hopcl Hswiv Note 2AVY −0.53 −1.87 0.44 −2.97 eco, 70S, apo 2AW7 −0.85 −6.40 −4.27 −7.09 eco, 70S, apo 3I1O 0.37 −3.31 −0.02 −2.26 eco, 70S, apo 3I1S 0.23 −0.25 0.78 −0.01 eco, 70S, P-site fMet-ASL 2I2U 0.00 0.00 0.00 0.00 eco, 70S, P-site Phe-ASL 2I2P 0.01 0.01 0.00 −0.02 eco, 70S, P-site Phe-ASL 3I21 1.21 0.59 1.08 0.71 eco, 70S, P-site Phe-ASL, A-site Phe-ASL 2OW8 1.88 1.54 2.13 1.70 tth, 70S, P-site Phe, E-site mix 2J00 3.22 2.06 1.59 2.53 tth, 70S, P-site fMet, A-site Phe-ASL, E-site noncog+PAR 2J02 3.80 2.23 1.73 2.82 tth, 70S, P-site fMet, A-site Phe-ASL, E-site noncog+PAR 2WRN 3.66 1.64 1.47 2.19 tth, 70S, P-site Phe, A/T Thr/tern, E-site Phe noncog+PAR 2WRQ 3.72 1.57 1.66 2.32 tth, 70S, P-site Phe, A/T Thr/tern, E-site Phe noncog+PAR EM5036 4.30 2.03 1.50 2.23 Refitted to the same density as 3FIH 3FIH 4.31 1.90 1.3
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