tRNA Dissociation from EF-Tu after GTP Hydrolysis: Primary Steps and Antibiotic Inhibition

Conformational changes of ribosomes during translation elongation resolved by molecular dynamics simulations

Molecular dynamics simulations have emerged as a powerful set of tools to unravel the intricate dynamics of ribosomes during protein synthesis. Recent advancements in this field have enabled simulations to delve deep into the conformational rearrangements of ribosomes and associated factors, providing invaluable insights into the intricacies of translation. Emphasis on simulations has recently been on translation elongation, such as tRNA selection, translocation, and ribosomal head-swivel motions. These studies have offered crucial structural interpretations of how genetic information is faithfully translated into proteins. This review outlines recent discoveries concerning ribosome conformational changes occurring during translation elongation, as elucidated through molecular dynamics simulations.

The energy landscape of the ribosome

The ribosome is a prototypical assembly that can be used to establish general principles and techniques for the study of biological molecular machines. Motivated by the fact that the dynamics of every biomolecule is governed by an underlying energy landscape, there has been great interest to understand and quantify ribosome energetics. In the present review, we will focus on theoretical and computational strategies for probing the interactions that shape the energy landscape of the ribosome, with an emphasis on more recent studies of the elongation cycle. These efforts include the application of quantum mechanical methods for describing chemical kinetics, as well as classical descriptions to characterize slower (microsecond to millisecond) large-scale (10-100 Å) rearrangements, where motion is described in terms of diffusion across an energy landscape. Together, these studies provide broad insights into the factors that control a diverse range of dynamical processes in this assembly.

Geometric alignment of aminoacyl-tRNA relative to catalytic centers of the ribosome underpins accurate mRNA decoding

Accurate protein synthesis is determined by the two-subunit ribosome's capacity to selectively incorporate cognate aminoacyl-tRNA for each mRNA codon. The molecular basis of tRNA selection accuracy, and how fidelity can be affected by antibiotics, remains incompletely understood. Using molecular simulations, we find that cognate and near-cognate tRNAs delivered to the ribosome by Elongation Factor Tu (EF-Tu) can follow divergent pathways of motion into the ribosome during both initial selection and proofreading. Consequently, cognate aa-tRNAs follow pathways aligned with the catalytic GTPase and peptidyltransferase centers of the large subunit, while near-cognate aa-tRNAs follow pathways that are misaligned. These findings suggest that differences in mRNA codon-tRNA anticodon interactions within the small subunit decoding center, where codon-anticodon interactions occur, are geometrically amplified over distance, as a result of this site's physical separation from the large ribosomal subunit catalytic centers. These insights posit that the physical size of both tRNA and ribosome are key determinants of the tRNA selection fidelity mechanism.

Translation machinery captured in motion

Translation accuracy is one of the most critical factors for protein synthesis. It is regulated by the ribosome and its dynamic behavior, along with translation factors that direct ribosome rearrangements to make translation a uniform process. Earlier structural studies of the ribosome complex with arrested translation factors laid the foundation for an understanding of ribosome dynamics and the translation process as such. Recent technological advances in time-resolved and ensemble cryo-EM have made it possible to study translation in real time at high resolution. These methods provided a detailed view of translation in bacteria for all three phases: initiation, elongation, and termination. In this review, we focus on translation factors (in some cases GTP activation) and their ability to monitor and respond to ribosome organization to enable efficient and accurate translation. This article is categorized under: Translation > Ribosome Structure/Function Translation > Mechanisms.

Decoding and Recoding of mRNA Sequences by the Ribosome

Faithful translation of messenger RNA (mRNA) into protein is essential to maintain protein homeostasis in the cell. Spontaneous translation errors are very rare due to stringent selection of cognate aminoacyl transfer RNAs (tRNAs) and the tight control of the mRNA reading frame by the ribosome. Recoding events, such as stop codon readthrough, frameshifting, and translational bypassing, reprogram the ribosome to make intentional mistakes and produce alternative proteins from the same mRNA. The hallmark of recoding is the change of ribosome dynamics. The signals for recoding are built into the mRNA, but their reading depends on the genetic makeup of the cell, resulting in cell-specific changes in expression programs. In this review, I discuss the mechanisms of canonical decoding and tRNA-mRNA translocation; describe alternative pathways leading to recoding; and identify the links among mRNA signals, ribosome dynamics, and recoding.

Binding of the peptide deformylase on the ribosome surface modulates the exit tunnel interior

Proteosynthesis on ribosomes is regulated at many levels. Conformational changes of the ribosome, possibly induced by external factors, may transfer over large distances and contribute to the regulation. The molecular principles of this long-distance allostery within the ribosome remain poorly understood. Here, we use structural analysis and atomistic molecular dynamics simulations to investigate peptide deformylase (PDF), an enzyme that binds to the ribosome surface near the ribosomal protein uL22 during translation and chemically modifies the emerging nascent peptide. Our simulations of the entire ribosome-PDF complex reveal that the PDF undergoes a swaying motion on the ribosome surface at the submicrosecond timescale. We show that the PDF affects the conformational dynamics of parts of the ribosome over distances of more than 5 nm. Using a supervised-learning algorithm, we demonstrate that the exit tunnel is influenced by the presence or absence of PDF. Our findings suggest a possible effect of the PDF on the nascent peptide translocation through the ribosome exit tunnel.

Assignment of structural domains in proteins using diffusion kernels on graphs

Though proposing algorithmic approaches for protein domain decomposition has been of high interest, the inherent ambiguity to the problem makes it still an active area of research. Besides, accurate automated methods are in high demand as the number of solved structures for complex proteins is on the rise. While majority of the previous efforts for decomposition of 3D structures are centered on the developing clustering algorithms, employing enhanced measures of proximity between the amino acids has remained rather uncharted. If there exists a kernel function that in its reproducing kernel Hilbert space, structural domains of proteins become well separated, then protein structures can be parsed into domains without the need to use a complex clustering algorithm. Inspired by this idea, we developed a protein domain decomposition method based on diffusion kernels on protein graphs. We examined all combinations of four graph node kernels and two clustering algorithms to investigate their capability to decompose protein structures. The proposed method is tested on five of the most commonly used benchmark datasets for protein domain assignment plus a comprehensive non-redundant dataset. The results show a competitive performance of the method utilizing one of the diffusion kernels compared to four of the best automatic methods. Our method is also able to offer alternative partitionings for the same structure which is in line with the subjective definition of protein domain. With a competitive accuracy and balanced performance for the simple and complex structures despite relying on a relatively naive criterion to choose optimal decomposition, the proposed method revealed that diffusion kernels on graphs in particular, and kernel functions in general are promising measures to facilitate parsing proteins into domains and performing different structural analysis on proteins. The size and interconnectedness of the protein graphs make them promising targets for diffusion kernels as measures of affinity between amino acids. The versatility of our method allows the implementation of future kernels with higher performance. The source code of the proposed method is accessible at https://github.com/taherimo/kludo . Also, the proposed method is available as a web application from https://cbph.ir/tools/kludo .

A topological data analytic approach for discovering biophysical signatures in protein dynamics

Identifying structural differences among proteins can be a non-trivial task. When contrasting ensembles of protein structures obtained from molecular dynamics simulations, biologically-relevant features can be easily overshadowed by spurious fluctuations. Here, we present SINATRA Pro, a computational pipeline designed to robustly identify topological differences between two sets of protein structures. Algorithmically, SINATRA Pro works by first taking in the 3D atomic coordinates for each protein snapshot and summarizing them according to their underlying topology. Statistically significant topological features are then projected back onto a user-selected representative protein structure, thus facilitating the visual identification of biophysical signatures of different protein ensembles. We assess the ability of SINATRA Pro to detect minute conformational changes in five independent protein systems of varying complexities. In all test cases, SINATRA Pro identifies known structural features that have been validated by previous experimental and computational studies, as well as novel features that are also likely to be biologically-relevant according to the literature. These results highlight SINATRA Pro as a promising method for facilitating the non-trivial task of pattern recognition in trajectories resulting from molecular dynamics simulations, with substantially increased resolution.

Structural features of proteins often serve as signatures of their biological function and molecular binding activity. Elucidating these structural features is essential for a full understanding of underlying biophysical mechanisms. While there are existing methods aimed at identifying structural differences between protein variants, such methods do not have the capability to jointly infer both geometric and dynamic changes, simultaneously. In this paper, we propose SINATRA Pro, a computational framework for extracting key structural features between two sets of proteins. SINATRA Pro robustly outperforms standard techniques in pinpointing the physical locations of both static and dynamic signatures across various types of protein ensembles, and it does so with improved resolution.

Effects of cryo-EM cooling on structural ensembles

Structure determination by cryo electron microscopy (cryo-EM) provides information on structural heterogeneity and ensembles at atomic resolution. To obtain cryo-EM images of macromolecules, the samples are first rapidly cooled down to cryogenic temperatures. To what extent the structural ensemble is perturbed during cooling is currently unknown. Here, to quantify the effects of cooling, we combined continuum model calculations of the temperature drop, molecular dynamics simulations of a ribosome complex before and during cooling with kinetic models. Our results suggest that three effects markedly contribute to the narrowing of the structural ensembles: thermal contraction, reduced thermal motion within local potential wells, and the equilibration into lower free-energy conformations by overcoming separating free-energy barriers. During cooling, barrier heights below 10 kJ/mol were found to be overcome, which is expected to reduce B-factors in ensembles imaged by cryo-EM. Our approach now enables the quantification of the heterogeneity of room-temperature ensembles from cryo-EM structures.

Folding of VemP into translation-arresting secondary structure is driven by the ribosome exit tunnel

The ribosome is a fundamental biomolecular complex that synthesizes proteins in cells. Nascent proteins emerge from the ribosome through a tunnel, where they may interact with the tunnel walls or small molecules such as antibiotics. These interactions can cause translational arrest with notable physiological consequences. Here, we studied the arrest caused by the regulatory peptide VemP, which is known to form α-helices inside the ribosome tunnel near the peptidyl transferase center under specific conditions. We used all-atom molecular dynamics simulations of the entire ribosome and circular dichroism spectroscopy to study the driving forces of helix formation and how VemP causes the translational arrest. To that aim, we compared VemP dynamics in the ribosome tunnel with its dynamics in solution. We show that the VemP peptide has a low helical propensity in water and that the propensity is higher in mixtures of water and trifluorethanol. We propose that helix formation within the ribosome is driven by the interactions of VemP with the tunnel and that a part of VemP acts as an anchor. This anchor might slow down VemP progression through the tunnel enabling α-helix formation, which causes the elongation arrest.

The Structural Dynamics of Translation

Accurate protein synthesis (translation) relies on translation factors that rectify ribosome fluctuations into a unidirectional process. Understanding this process requires structural characterization of the ribosome and translation-factor dynamics. In the 2000s, crystallographic studies determined high-resolution structures of ribosomes stalled with translation factors, providing a starting point for visualizing translation. Recent progress in single-particle cryogenic electron microscopy (cryo-EM) has enabled near-atomic resolution of numerous structures sampled in heterogeneous complexes (ensembles). Ensemble and time-resolved cryo-EM have now revealed unprecedented views of ribosome transitions in the three principal stages of translation: initiation, elongation, and termination. This review focuses on how translation factors help achieve high accuracy and efficiency of translation by monitoring distinct ribosome conformations and by differentially shifting the equilibria of ribosome rearrangements for cognate and near-cognate substrates. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

2-Pyridone natural products as inhibitors of SARS-CoV-2 main protease

The disease, COVID-19, is caused by the severe acute respiratory coronavirus 2 (SARS-CoV-2) for which there is currently no treatment. The SARS-CoV-2 main protease (M^pro) is an important enzyme for viral replication. Small molecules that inhibit this protease could lead to an effective COVID-19 treatment. The 2-pyridone scaffold was previously identified as a possible key pharmacophore to inhibit SARS-CoV-2 M^pro. A search for natural, antimicrobial products with the 2-pyridone moiety was undertaken herein, and their calculated potency as inhibitors of SARS-CoV-2 M^pro was investigated. Thirty-three natural products containing the 2-pyridone scaffold were identified from the literature. An in silico methodology using AutoDock was employed to predict the binding energies and inhibition constants (K_i values) for each 2-pyridone-containing compound with SARS-CoV-2 M^pro. This consisted of molecular optimization of the 2-pyridone compound, docking of the compound with a crystal structure of SARS-CoV-2 M^pro, and evaluation of the predicted interactions and ligand-enzyme conformations. All compounds investigated bound to the active site of SARS-CoV-2 M^pro, close to the catalytic dyad (His-41 and Cys-145). Thirteen molecules had predicted K_i values <1 μM. Glu-166 formed a key hydrogen bond in the majority of the predicted complexes, while Met-165 had some involvement in the complex binding as a close contact to the ligand. Prominent 2-pyridone compounds were further evaluated for their ADMET properties. This work has identified 2-pyridone natural products with calculated potent inhibitory activity against SARS-CoV-2 M^pro and with desirable drug-like properties, which may lead to the rapid discovery of a treatment for COVID-19.

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2-pyridone-scaffold is an inhibitory pharmacophore for SARS-CoV-2 M^pro.

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Thirty-three natural, antimicrobial products identified with 2-pyridone moiety.

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All 2-pyridone natural products bind to active site of SARS-CoV-2 M^proin silico.

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Thirteen molecules found to have potent inhibitory activity against SARS-CoV-2 M^pro.

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Inhibition of SARS-CoV-2 by natural 2-pyridones may lead to treatment of COVID-19.

Elongation Factor Tu Switch I Element is a Gate for Aminoacyl-tRNA Selection

Selection of correct aminoacyl (aa)-tRNA at the ribosomal A site is fundamental to maintaining translational fidelity. Aa-tRNA selection is a multistep process facilitated by the guanosine triphosphatase elongation factor (EF)-Tu. EF-Tu delivers aa-tRNA to the ribosomal A site and participates in tRNA selection. The structural mechanism of how EF-Tu is involved in proofreading remains to be fully resolved. Here, we provide evidence that switch I of EF-Tu facilitates EF-Tu's involvement during aa-tRNA selection. Using structure-based and explicit solvent molecular dynamics simulations based on recent cryo-electron microscopy reconstructions, we studied the conformational change of EF-Tu from the guanosine triphosphate to guanine diphosphate conformation during aa-tRNA accommodation. Switch I of EF-Tu rapidly converts from an α-helix into a β-hairpin and moves to interact with the acceptor stem of the aa-tRNA. In doing so, switch I gates the movement of the aa-tRNA during accommodation through steric interactions with the acceptor stem. Pharmacological inhibition of the aa-tRNA accommodation pathway prevents the proper positioning of switch I with the aa-tRNA acceptor stem, suggesting that the observed interactions are specific for cognate aa-tRNA substrates, and thus capable of contributing to the fidelity mechanism.