Flipping of the Ribosomal A-Site Adenines Provides a Basis for tRNA Selection

Abstract

Ribosomes control the missense error rate of ~10−4 during translation though quantitative contributions of individual mechanistic steps of the conformational changes yet to be fully determined. Biochemical and biophysical studies led to a qualitative tRNA selection model in which ribosomal A-site residues A1492 and A1493 (A1492/3) flip out in response to cognate tRNA binding, promoting the subsequent reactions, but not in the case of near cognate or non-cognate tRNA. However, this model was recently questioned by X-ray structures revealing conformations of extrahelical A1492/3 and domain closure of the decoding center in both cognate and near-cognate tRNA bound ribosome complexes, suggesting that the non-specific flipping of A1492/3 has no active role in tRNA selection. We explore this question by carrying out molecular dynamics (MD) simulations, aided with fluorescence and NMR experiments, to probe the free energy cost of extrahelical flipping of 1492/3 and the strain energy associated with domain conformational change. Our rigorous calculations demonstrate that the A1492/3 flipping is indeed a specific response to the binding of cognate tRNA, contributing 3 kcal/mol to the specificity of tRNA selection. Furthermore, the different A-minor interactions in cognate and near-cognate complexes propagate into the conformational strain and contribute another 4 kcal/mol in domain closure. The recent structure of ribosome with features of extrahelical A1492/3 and closed domain in near-cognate complex is reconciled by possible tautomerization of the wobble base pair in mRNA-tRNA. These results quantitatively rationalize other independent experimental observations and explain the ribosomal discrimination mechanism of selecting cognate versus near-cognate tRNA.

Hierarchy of RNA Functional Dynamics

“…For the ribosomal A-site, the higher energy CS sequesters adenine residues that otherwise need to be free to carry out decoding functions (5, 62), and may play a role in processes that bypass decoding such as frameshifting or stop-codon read-through (Figure 5B) (54). In another potential tuning role, a conserved non-canonical motif in one of the helices of the purine riboswitch aptamer was shown to tune ligand affinity and binding kinetics by altering the local pairing dynamics of the ligand-free state (63).…”

“…A recent study reported that uridine tautomerization can allow a non-cognate G-U pair in the mRNA-tRNA minihelix to adopt a WC-like rather than a wobble conformation, changing the steric profile of the pair and circumventing the mechanism used by the ribosome to reject non-cognate codons (79). It should be noted, however, that the high free energy cost of such tautomerizations ensures that decoding accuracy is not significantly comprised (62). Alternatively, post-transcriptional chemical modifications of some tRNA anticodons appear to play an important role in decreasing the energetic cost of tautomerization, allowing the tRNA to form WC-like pairs with multiple different mRNA codons and thus expanding its decoding capacity (83–85).…”

“…During tRNA initial selection, tertiary structure dynamics involving formation of A-minor interactions between the ribosomal A-site and anticodon-codon minihelix serve to stabilize cognate mRNA-tRNA pairs, preventing tRNA dissociation and driving ‘domain-closure’ conformational changes in the ribosome that activate GTP hydrolysis in EF-Tu (Figure 5B) (62, 101–106). Remarkably, a single incorrect base-pair between the mRNA and tRNA is sufficient to disfavor these conformational changes, forming the basis for the 10 2 –10 3 selectively of initial selection (107).…”

A close-up view of codon selection in eukaryotic initiation

“…Hence it is clear that computer simulations have become very useful for addressing some of the key problems of the ribosomal translational machinery, ranging from large movements involving the full ribosome 34 to the mechanisms of tRNA selection, 10,[35][36][37] peptide elongation, 27,32,[38][39][40] translocation 41,42 and mechanisms of translation termination. 11,12,[43][44][45] The whole toolbox of computational chemistry is powerful and includes quantum mechanical calculations, molecular dynamics free energy simulations, coarse-grained methods and elastic network models, as well as molecular docking 44 and homology modeling.…”

Using Molecular Simulation to Model High-Resolution Cryo-EM Reconstructions

“…In addition to crystallographic (Dunkle et al, 2011;Tourigny, Fernandez, Kelley, & Ramakrishnan, 2013), cryo-electron microscopy (cryo-EM) (Dashti et al, 2014), single molecule (Blanchard, Kim, Gonzalez, Puglisi, & Chu, 2004;Munro, Wasserman, Altman, Wang, & Blanchard, 2010;Olivier et al, 2014; and rapid kinetics studies (Rodnina & Wintermeyer, 2011), computational studies by other groups have been performed on ratchet motion (Bock et al, 2013;Ishida & Matsumoto, 2014;Kurkcuoglu, Doruker, Sen, Kloczkowski, & Jernigan, 2008;Trylska, Konecny, Tama, Brooks, & McCammon, 2004), decoding (Adamczyk & Warshel, 2011;Zeng, Chugh, Casiano-Negroni, Al-Hashimi, & Brooks, 2014), protein translocation (Ishida & Hayward, 2008;Rychkova, Mukherjee, Bora, & Warshel, 2013), and other aspects of the ribosome (Baker, Sept, Joseph, Holst, & McCammon, 2001;Trabuco et al, 2010). Outstanding research has advanced molecular dynamics of RNA (Bergonzo et al, 2014;Cheatham & Case, 2013;Chen, Marucho, Baker, & Pappu, 2009;Henriksen, Davis, & Cheatham, 2012;Liu, Janowski, & Case, 2015).…”