Ribosome Mechanics Informs about Mechanism

Tandem mass tag (TMT) labeling-based quantitative proteomic analysis reveals the cellular protein characteristics of 16HBE cells infected with coxsackievirus A10 and the potential effect of HMGB1 on viral replication

Coxsackievirus A10 (CV-A10) is recognized as one of the most important pathogens associated with hand, foot, and mouth disease (HFMD) in young children under 5 years of age worldwide, and it can lead to fatal neurological complications. However, available commercial vaccines fail to protect against CV-A10. Therefore, there is an urgent need to study new protein targets of CV-A10 and develop novel vaccine-based therapeutic strategies. Advances in proteomics in recent years have enabled a comprehensive understanding of host pathogen interactions. Here, to study CV-A10-host interactions, a global quantitative proteomic analysis was conducted to investigate the molecular characteristics of host cell proteins and identify key host proteins involved in CV-A10 infection. Using tandem mass tagging (TMT)-based mass spectrometry, a total of 6615 host proteins were quantified, with 293 proteins being differentially regulated. To ensure the validity and reliability of the proteomics data, three randomly selected proteins were verified by Western blot analysis, and the results were consistent with the TMT results. Further functional analysis showed that the upregulated and downregulated proteins were associated with diverse biological activities and signaling pathways, such as metabolic processes, biosynthetic processes, the AMPK signaling pathway, the neurotrophin signaling pathway, the MAPK signaling pathway, and the GABAergic synaptic signaling. Moreover, subsequent bioinformatics analysis demonstrated that these differentially expressed proteins contained distinct domains, were localized in different subcellular components, and generated a complex network. Finally, high-mobility group box 1 (HMGB1) might be a key host factor involved in CV-A10 replication. In summary, our findings provide comprehensive insights into the proteomic profile during CV-A10 infection, deepen our understanding of the relationship between CV-A10 and host cells, and establish a proteomic signature for this viral infection. Moreover, the observed effect of HMGB1 on CV-A10 replication suggests that it might be a potential therapeutic target treatment of CV-A10 infection.

Predicting allosteric pockets in protein biological assemblages

MOTIVATION

Allostery enables changes to the dynamic behavior of a protein at distant positions induced by binding. Here, we present APOP, a new allosteric pocket prediction method, which perturbs the pockets formed in the structure by stiffening pairwise interactions in the elastic network across the pocket, to emulate ligand binding. Ranking the pockets based on the shifts in the global mode frequencies, as well as their mean local hydrophobicities, leads to high prediction success when tested on a dataset of allosteric proteins, composed of both monomers and multimeric assemblages.

RESULTS

Out of the 104 test cases, APOP predicts known allosteric pockets for 92 within the top 3 rank out of multiple pockets available in the protein. In addition, we demonstrate that APOP can also find new alternative allosteric pockets in proteins. Particularly interesting findings are the discovery of previously overlooked large pockets located in the centers of many protein biological assemblages; binding of ligands at these sites would likely be particularly effective in changing the protein's global dynamics.

AVAILABILITY AND IMPLEMENTATION

APOP is freely available as an open-source code (https://github.com/Ambuj-UF/APOP) and as a web server at https://apop.bb.iastate.edu/.

Modeling the ribosome as a bipartite graph

Developing mathematical representations of biological systems that can allow predictions is a challenging and important research goal. It is demonstrated here how the ribosome, the nano-machine responsible for synthesizing all proteins necessary for cellular life, can be represented as a bipartite network. Ten ribosomal structures from Bacteria and six from Eukarya are explored. Ribosomal networks are found to exhibit unique properties despite variations in the nodes and edges of the different graphs. The ribosome is shown to exhibit very large topological redundancies, demonstrating mathematical resiliency. These results can potentially explain how it can function consistently despite changes in composition and connectivity. Furthermore, this representation can be used to analyze ribosome function within the large machinery of network theory, where the degrees of freedom are the possible interactions, and can be used to provide new insights for translation regulation and therapeutics.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

hdANM: a new comprehensive dynamics model for protein hinges

Hinge motions are essential for many protein functions, and their dynamics are important to understand underlying biological mechanisms. The ways that these motions are represented by various computational methods differ significantly. By focusing on a specific class of motion, we have developed a new hinge-domain anisotropic network model (hdANM) that is based on the prior identification of flexible hinges and rigid domains in the protein structure and the subsequent generation of global hinge motions. This yields a set of motions in which the relative translations and rotations of the rigid domains are modulated and controlled by the deformation of the flexible hinges, leading to a more restricted, specific view of these motions. hdANM is the first model, to our knowledge, that combines information about protein hinges and domains to model the characteristic hinge motions of a protein. The motions predicted with this new elastic network model provide important conceptual advantages for understanding the underlying biological mechanisms. As a matter of fact, the generated hinge movements are found to resemble the expected mechanisms required for the biological functions of diverse proteins. Another advantage of this model is that the domain-level coarse graining makes it significantly more computationally efficient, enabling the generation of hinge motions within even the largest molecular assemblies, such as those from cryo-electron microscopy. hdANM is also comprehensive as it can perform in the same way as the well-known protein dynamics models (anisotropic network model, rotations-translations of blocks, and nonlinear rigid block normal mode analysis), depending on the definition of flexible and rigid parts in the protein structure and on whether the motions are extrapolated in a linear or nonlinear fashion. Furthermore, our results indicate that hdANM produces more realistic motions as compared to the anisotropic network model. hdANM is an open-source software, freely available, and hosted on a user-friendly website.

Universal scanning-free initiation of eukaryote protein translation-a new normal

A unique feature of eukaryote initiation of protein translation is a so-called scanning of 5'-untranslated region (5'-UTR) by a ribosome initiation complex to enable bound Met-tRNA_i access to the initiation codon located further downstream. Here, we propose a universal scanning-free translation initiation model that is independent of 5'-UTR length and applicable to both 5'-m⁷G (capped) and uncapped mRNAs.

Comparative Analysis of Structural and Dynamical Features of Ribosome Upon Association With mRNA Reveals Potential Role of Ribosomal Proteins

Ribosomes play a critical role in maintaining cellular proteostasis. The binding of messenger RNA (mRNA) to the ribosome regulates kinetics of protein synthesis. To generate an understanding of the structural, mechanistic, and dynamical features of mRNA recognition in the ribosome, we have analysed mRNA-protein interactions through a structural comparison of the ribosomal complex in the presence and absence of mRNA. To do so, we compared the 3-Dimensional (3D) structures of components of the two assembly structures and analysed their structural differences because of mRNA binding, using elastic network models and structural network-based analysis. We observe that the head region of 30S ribosomal subunit undergoes structural displacement and subunit rearrangement to accommodate incoming mRNA. We find that these changes are observed in proteins that lie far from the mRNA-protein interface, implying allostery. Further, through perturbation response scanning, we show that the proteins S13, S19, and S20 act as universal sensors that are sensitive to changes in the inter protein network, upon binding of 30S complex with mRNA and other initiation factors. Our study highlights the significance of mRNA binding in the ribosome complex and identifies putative allosteric sites corresponding to alterations in structure and/or dynamics, in regions away from mRNA binding sites in the complex. Overall, our work provides fresh insights into mRNA association with the ribosome, highlighting changes in the interactions and dynamics of the ribosome assembly because of the binding.

Network theory of the bacterial ribosome

In the past two decades, research into the biochemical, biophysical and structural properties of the ribosome have revealed many different steps of protein translation. Nevertheless, a complete understanding of how they lead to a rapid and accurate protein synthesis still remains a challenge. Here we consider a coarse network analysis in the bacterial ribosome formed by the connectivity between ribosomal (r) proteins and RNAs at different stages in the elongation cycle. The ribosomal networks are found to be dis-assortative and small world, implying that the structure allows for an efficient exchange of information between distant locations. An analysis of centrality shows that the second and fifth domains of 23S rRNA are the most important elements in all of the networks. Ribosomal protein hubs connect to much fewer nodes but are shown to provide important connectivity within the network (high closeness centrality). A modularity analysis reveals some of the different functional communities, indicating some known and some new possible communication pathways Our mathematical results confirm important communication pathways that have been discussed in previous research, thus verifying the use of this technique for representing the ribosome, and also reveal new insights into the collective function of ribosomal elements.

Resolution-exchanged structural modeling and simulations jointly unravel that subunit rolling underlies the mechanism of programmed ribosomal frameshifting

MOTIVATION

Programmed ribosomal frameshifting (PRF) is widely used by viruses and bacteria to produce different proteins from a single mRNA template. How steric hindrance of a PRF-stimulatory mRNA structure transiently modifies the conformational dynamics of the ribosome, and thereby allows tRNA slippage, remains elusive.

RESULTS

Here, we leverage linear response theories and resolution-exchanged simulations to construct a structural/dynamics model that connects and rationalizes existing structural, single-molecule and mutagenesis data by resolution-exchanged structural modelling and simulations. Our combined theoretical techniques provide a temporal and spatial description of PRF with unprecedented mechanistic details. We discover that ribosomal unfolding of the PRF-stimulating pseudoknot exerts resistant forces on the mRNA entrance of the ribosome, and thereby drives 30S subunit rolling. Such motion distorts tRNAs, leads to tRNA slippage, and in turn serves as a delicate control of cis-element's unwinding forces over PRF.

AVAILABILITY AND IMPLEMENTATION

All the simulation scripts and computational implementations of our methods/analyses (including linear response theory) are included in the bioStructureM suite, provided through GitHub at https://github.com/Yuan-Yu/bioStructureM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Large-scale simulations of nucleoprotein complexes: ribosomes, nucleosomes, chromatin, chromosomes and CRISPR

Recent advances in biotechnology such as Hi-C, CRISPR/Cas9 and ribosome display have placed nucleoprotein complexes at center stage. Understanding the structural dynamics of these complexes aids in optimizing protocols and interpreting data for these new technologies. The integration of simulation and experiment has helped advance mechanistic understanding of these systems. Coarse-grained simulations, reduced-description models, and explicit solvent molecular dynamics simulations yield useful complementary perspectives on nucleoprotein complex structural dynamics. When combined with Hi-C, cryo-EM, and single molecule measurements, these simulations integrate disparate forms of experimental data into a coherent mechanism.

The Expansion Segments of 28S Ribosomal RNA Extensively Match Human Messenger RNAs

Eukaryote ribosomal RNAs (rRNAs) have expanded in the course of phylogeny by addition of nucleotides in specific insertion areas, the expansion segments. These number about 40 in the larger (25–28S) rRNA (up to 2,400 nucleotides), and about 12 in the smaller (18S) rRNA (<700 nucleotides). Expansion of the larger rRNA shows a clear phylogenetic increase, with a dramatic rise in mammals and especially in hominids. Substantial portions of expansion segments in this RNA are not bound to ribosomal proteins, and may engage extraneous interactants, including messenger RNAs (mRNAs). Studies on the ribosome-mRNA interaction have focused on proteins of the smaller ribosomal subunit, with some examination of 18S rRNA. However, the expansion segments of human 28S rRNA show much higher density and numbers of mRNA matches than those of 18S rRNA, and also a higher density and match numbers than its own core parts. We have studied that with frequent and potentially stable matches containing 7–15 nucleotides. The expansion segments of 28S rRNA average more than 50 matches per mRNA even assuming only 5% of their sequence as available for such interaction. Large expansion segments 7, 15, and 27 of 28S rRNA also have copious long (≥10-nucleotide) matches to most human mRNAs, with frequencies much higher than in other 28S rRNA parts. Expansion segments 7 and 27 and especially segment 15 of 28S rRNA show large size increase in mammals compared to other metazoans, which could reflect a gain of function related to interaction with non-ribosomal partners. The 28S rRNA expansion segment 15 shows very high increments in size, guanosine, and cytidine nucleotide content and mRNA matching in mammals, and especially in hominids. With these segments (but not with other 28S rRNA or any 18S rRNA expansion segments) the density and number of matches are much higher in 5′-terminal than in 3′-terminal untranslated mRNA regions, which may relate to mRNA mobilization via 5′ termini. Matches in the expansion segments 7, 15, and 27 of human 28S rRNA appear as candidates for general interaction with mRNAs, especially those associated with intracellular matrices such as the endoplasmic reticulum.

The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems

Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.

Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc.

The fluctuating ribosome: thermal molecular dynamics characterized by neutron scattering

Conformational changes associated with ribosome function have been identified by X-ray crystallography and cryo-electron microscopy. These methods, however, inform poorly on timescales. Neutron scattering is well adapted for direct measurements of thermal molecular dynamics, the ‘lubricant’ for the conformational fluctuations required for biological activity. The method was applied to compare water dynamics and conformational fluctuations in the 30 S and 50 S ribosomal subunits from Haloarcula marismortui, under high salt, stable conditions. Similar free and hydration water diffusion parameters are found for both subunits. With respect to the 50 S subunit, the 30 S is characterized by a softer force constant and larger mean square displacements (MSD), which would facilitate conformational adjustments required for messenger and transfer RNA binding. It has been shown previously that systems from mesophiles and extremophiles are adapted to have similar MSD under their respective physiological conditions. This suggests that the results presented are not specific to halophiles in high salt but a general property of ribosome dynamics under corresponding, active conditions. The current study opens new perspectives for neutron scattering characterization of component functional molecular dynamics within the ribosome.