Profiling Ssb-Nascent Chain Interactions Reveals Principles of Hsp70-Assisted Folding.

The yeast Hsp70 chaperone Ssb interacts with ribosomes and nascent polypeptides to assist protein folding. To reveal its working principle, we determined the nascent chain-binding pattern of Ssb at near-residue resolution by in vivo selective ribosome profiling. Ssb associates broadly with cytosolic, nuclear, and hitherto unknown substrate classes of mitochondrial and endoplasmic reticulum (ER) nascent proteins, supporting its general chaperone function. Ssb engages most substrates by multiple binding-release cycles to a degenerate sequence enriched in positively charged and aromatic amino acids. Timely association with this motif upon emergence at the ribosomal tunnel exit requires ribosome-associated complex (RAC) but not nascent polypeptide-associated complex (NAC). Ribosome footprint densities along orfs reveal faster translation at times of Ssb binding, mainly imposed by biases in mRNA secondary structure, codon usage, and Ssb action. Ssb thus employs substrate-tailored dynamic nascent chain associations to coordinate co-translational protein folding, facilitate accelerated translation, and support membrane targeting of organellar proteins.

It is theoretically possible to avoid misfolding into non-covalent lasso entanglements using small molecule drugs.

A novel class of protein misfolding characterized by either the formation of non-native noncovalent lasso entanglements in the misfolded structure or loss of native entanglements has been predicted to exist and found circumstantial support through biochemical assays and limited-proteolysis mass spectrometry data. Here, we examine whether it is possible to design small molecule compounds that can bind to specific folding intermediates and thereby avoid these misfolded states in computer simulations under idealized conditions (perfect drug-binding specificity, zero promiscuity, and a smooth energy landscape). Studying two proteins, type III chloramphenicol acetyltransferase (CAT-III) and D-alanyl-D-alanine ligase B (DDLB), that were previously suggested to form soluble misfolded states through a mechanism involving a failure-to-form of native entanglements, we explore two different drug design strategies using coarse-grained structure-based models. The first strategy, in which the native entanglement is stabilized by drug binding, failed to decrease misfolding because it formed an alternative entanglement at a nearby region. The second strategy, in which a small molecule was designed to bind to a non-native tertiary structure and thereby destabilize the native entanglement, succeeded in decreasing misfolding and increasing the native state population. This strategy worked because destabilizing the entanglement loop provided more time for the threading segment to position itself correctly to be wrapped by the loop to form the native entanglement. Further, we computationally identified several FDA-approved drugs with the potential to bind these intermediate states and rescue misfolding in these proteins. This study suggests it is possible for small molecule drugs to prevent protein misfolding of this type.

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2.

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu. Here, using a coarse-grained model and replica-exchange umbrella sampling, we studied the free energy landscape of both the wild type and Omicron subvariants BA.1 and XBB.1.5 interacting with ACE2. In agreement with experiment, we find that the wild type and Omicron subvariants have similar xu values, but Omicron binds ACE2 more strongly than the wild type, having a lower dissociation constant KD.

Combinations of slow-translating codon clusters can increase mRNA half-life in Saccharomyces cerevisiae.

The presence of a single cluster of nonoptimal codons was found to decrease a transcript's half-life through the interaction of the ribosome-associated quality control machinery with stalled ribosomes in Saccharomyces cerevisiae The impact of multiple nonoptimal codon clusters on a transcript's half-life, however, is unknown. Using a kinetic model, we predict that inserting a second nonoptimal cluster near the 5' end can lead to synergistic effects that increase a messenger RNA's (mRNA's) half-life in S. cerevisiae Specifically, the 5' end cluster suppresses the formation of ribosome queues, reducing the interaction of ribosome-associated quality control factors with stalled ribosomes. We experimentally validate this prediction by introducing two nonoptimal clusters into three different genes and find that their mRNA half-life increases up to fourfold. The model also predicts that in the presence of two clusters, the cluster closest to the 5' end is the primary determinant of mRNA half-life. These results suggest the "translational ramp," in which nonoptimal codons are located near the start codon and increase translational efficiency, may have the additional biological benefit of allowing downstream slow-codon clusters to be present without decreasing mRNA half-life. These results indicate that codon usage bias plays a more nuanced role in controlling cellular protein levels than previously thought.

Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer.

BACKGROUND: Synonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations. RESULTS: Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation. CONCLUSION: Our study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.

Domain topology, stability, and translation speed determine mechanical force generation on the ribosome.

The concomitant folding of a nascent protein domain with its synthesis can generate mechanical forces that act on the ribosome and alter translation speed. Such changes in speed can affect the structure and function of the newly synthesized protein as well as cellular phenotype. The domain properties that govern force generation have yet to be identified and understood, and the influence of translation speed is unknown because all reported measurements have been carried out on arrested ribosomes. Here, using coarse-grained molecular simulations and statistical mechanical modeling of protein synthesis, we demonstrate that force generation is determined by a domain's stability and topology, as well as translation speed. The statistical mechanical models we create predict how force profiles depend on these properties. These results indicate that force measurements on arrested ribosomes will not always accurately reflect what happens in a cell, especially for slow-folding domains, and suggest the possibility that certain domain properties may be enriched or depleted across the structural proteome of organisms through evolutionary selection pressures to modulate protein synthesis speed and posttranslational protein behavior.

RiboA: a web application to identify ribosome A-site locations in ribosome profiling data.

BACKGROUND: Translation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations. RESULTS: We present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms. CONCLUSIONS: The Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service at https://a-site.vmhost.psu.edu/ . The code is publicly available at https://github.com/obrien-lab/aip_web_docker under the MIT license.

Ribosome Elongation Kinetics of Consecutively Charged Residues Are Coupled to Electrostatic Force.

The speed of protein synthesis can dramatically change when consecutively charged residues are incorporated into an elongating nascent protein by the ribosome. The molecular origins of this class of allosteric coupling remain unknown. We demonstrate, using multiscale simulations, that positively charged residues generate large forces that move the P-site amino acid away from the A-site amino acid. Negatively charged residues generate forces of similar magnitude but move the A- and P-sites closer together. These conformational changes, respectively, increase and decrease the transition state barrier height to peptide bond formation, explaining how charged residues mechanochemically alter translation speed. This mechanochemical mechanism is consistent with in vivo ribosome profiling data exhibiting proportionality between translation speed and the number of charged residues, experimental data characterizing nascent chain conformations, and a previously published cryo-EM structure of a ribosome-nascent chain complex containing consecutive lysines. These results expand the role of mechanochemistry in translation and provide a framework for interpreting experimental results on translation speed.

Forcing the ribosome to change its message.

Mechanical forces can be generated when nascent protein segments are integrated into a membrane. These forces are then transmitted through the nascent protein to the ribosome's catalytic core, but only a few biological consequences of this process have been identified to date. In this issue, Harrington et al. present evidence that these forces form a conserved mechanism to influence the efficiency of ribosomal frameshifting during translation of viral RNA, indicating that mechanical forces may play a broader regulatory role in translation than previously appreciated.

Electrostatic Interactions Govern Extreme Nascent Protein Ejection Times from Ribosomes and Can Delay Ribosome Recycling.

The ejection of nascent proteins out of the ribosome exit tunnel, after their covalent bond to transfer-RNA has been broken, has not been experimentally studied due to challenges in sample preparation. Here, we investigate this process using a combination of multiscale modeling, ribosome profiling, and gene ontology analyses. Simulating the ejection of a representative set of 122 E. coli proteins we find a greater than 1000-fold variation in ejection times. Nascent proteins enriched in negatively charged residues near their C-terminus eject the fastest, while nascent chains enriched in positively charged residues tend to eject much more slowly. More work is required to pull slowly ejecting proteins out of the exit tunnel than quickly ejecting proteins, according to all-atom simulations. An energetic decomposition reveals, for slowly ejecting proteins, that this is due to the strong attractive electrostatic interactions between the nascent chain and the negatively charged ribosomal-RNA lining the exit tunnel, and for quickly ejecting proteins, it is due to their repulsive electrostatic interactions with the exit tunnel. Ribosome profiling data from E. coli reveals that the presence of slowly ejecting sequences correlates with ribosomes spending more time at stop codons, indicating that the ejection process might delay ribosome recycling. Proteins that have the highest positive charge density at their C-terminus are overwhelmingly ribosomal proteins, suggesting the possibility that this sequence feature may aid in the cotranslational assembly of ribosomes by delaying the release of nascent ribosomal proteins into the cytosol. Thus, nascent chain ejection times from the ribosome can vary greatly between proteins due to differential electrostatic interactions, can influence ribosome recycling, and could be particularly relevant to the synthesis and cotranslational behavior of some proteins.

A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data.

Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S. cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.

Mechanochemistry in Translation.

As the influence of translation rates on protein folding and function has come to light, the mechanisms by which translation speed is modulated have become an important issue. One mechanism entails the generation of force by the nascent protein. Cotranslational processes, such as nascent protein folding, the emergence of unfolded nascent chain segments from the ribosome's exit tunnel, and insertion of the nascent chain into or translocation of the nascent chain through membranes, can generate forces that are transmitted back to the peptidyl transferase center and affect translation rates. In this Perspective, we examine the processes that generate these forces, the mechanisms of transmission along the ribosomal exit tunnel to the peptidyl transferase center, and the effects of force on the ribosome's catalytic cycle. We also discuss the physical models that have been developed to predict and explain force generation for individual processes and speculate about other processes that may generate forces that have yet to be tested.

Origins of the Mechanochemical Coupling of Peptide Bond Formation to Protein Synthesis.

Mechanical forces acting on the ribosome can alter the speed of protein synthesis, indicating that mechanochemistry can contribute to translation control of gene expression. The naturally occurring sources of these mechanical forces, the mechanism by which they are transmitted 10 nm to the ribosome's catalytic core, and how they influence peptide bond formation rates are largely unknown. Here, we identify a new source of mechanical force acting on the ribosome by using in situ experimental measurements of changes in nascent-chain extension in the exit tunnel in conjunction with all-atom and coarse-grained computer simulations. We demonstrate that when the number of residues composing a nascent chain increases, its unstructured segments outside the ribosome exit tunnel generate piconewtons of force that are fully transmitted to the ribosome's P-site. The route of force transmission is shown to be through the nascent polypetide's backbone, not through the wall of the ribosome's exit tunnel. Utilizing quantum mechanical calculations we find that a consequence of such a pulling force is to decrease the transition state free energy barrier to peptide bond formation, indicating that the elongation of a nascent chain can accelerate translation. Since nascent protein segments can start out as largely unfolded structural ensembles, these results suggest a pulling force is present during protein synthesis that can modulate translation speed. The mechanism of force transmission we have identified and its consequences for peptide bond formation should be relevant regardless of the source of the pulling force.

Fast Protein Translation Can Promote Co- and Posttranslational Folding of Misfolding-Prone Proteins.

Chemical kinetic modeling has previously been used to predict that fast-translating codons can enhance cotranslational protein folding by helping to avoid misfolded intermediates. Consistent with this prediction, protein aggregation in yeast and worms was observed to increase when translation was globally slowed down, possibly due to increased cotranslational misfolding. Observation of similar behavior in molecular simulations would confirm predictions from the simpler chemical kinetic model and provide a molecular perspective on cotranslational folding, misfolding, and the impact of translation speed on these processes. All-atom simulations cannot reach the timescales relevant to protein synthesis, and most conventional structure-based coarse-grained models do not allow for nonnative structure formation. Here, we introduce a protocol to incorporate misfolding using the functional forms of publicly available force fields. With this model we create two artificial proteins that are capable of undergoing structural transitions between a native and a misfolded conformation and simulate their synthesis by the ribosome. Consistent with the chemical kinetic predictions, we find that rapid synthesis of misfolding-prone nascent-chain segments increases the fraction of folded proteins by kinetically partitioning more molecules through on-pathway intermediates, decreasing the likelihood of sampling misfolded conformations. Novel to this study, to our knowledge, we observe that differences in protein dynamics, arising from different translation-elongation schedules, can persist long after the nascent protein has been released from the ribosome, and that a sufficient level of energetic frustration is needed for fast-translating codons to be beneficial for folding. These results provide further evidence that fast-translating codons can be as biologically important as pause sites in coordinating cotranslational folding.

Physical Origins of Codon Positions That Strongly Influence Cotranslational Folding: A Framework for Controlling Nascent-Protein Folding.

An emerging paradigm in the field of in vivo protein biophysics is that nascent-protein behavior is a type of nonequilibrium phenomenon, where translation-elongation kinetics can be more important in determining nascent-protein behavior than the thermodynamic properties of the protein. Synonymous codon substitutions, which change the translation rate at select codon positions along a transcript, have been shown to alter cotranslational protein folding, suggesting that evolution may have shaped synonymous codon usage in the genomes of organisms in part to increase the amount of folded and functional nascent protein. Here, we develop a Monte Carlo-master-equation method that allows for the control of nascent-chain folding during translation through the rational design of mRNA sequences to guide the cotranslational folding process. We test this framework using coarse-grained molecular dynamics simulations and find it provides optimal mRNA sequences to control the simulated, cotranslational folding of a protein in a user-prescribed manner. With this approach we discover that some codon positions in a transcript can have a much greater impact on nascent-protein folding than others because they tend to be positions where the nascent chain populates states that are far from equilibrium, as well as being dependent on a complex ratio of time scales. As a consequence, different cotranslational profiles of the same protein can have different critical codon positions and different numbers of synonymous mRNA sequences that encode for them. These findings explain that there is a fundamental connection between the nonequilibrium nature of cotranslational processes, nascent-protein behavior, and synonymous codon usage.

In vivo translation rates can substantially delay the cotranslational folding of the Escherichia coli cytosolic proteome.

A question of fundamental importance concerning protein folding in vivo is whether the kinetics of translation or the thermodynamics of the ribosome nascent chain (RNC) complex is the major determinant of cotranslational folding behavior. This is because translation rates can reduce the probability of cotranslational folding below that associated with arrested ribosomes, whose behavior is determined by the equilibrium thermodynamics of the RNC complex. Here, we combine a chemical kinetic equation with genomic and proteomic data to predict domain folding probabilities as a function of nascent chain length for Escherichia coli cytosolic proteins synthesized on both arrested and continuously translating ribosomes. Our results indicate that, at in vivo translation rates, about one-third of the Escherichia coli cytosolic proteins exhibit cotranslational folding, with at least one domain in each of these proteins folding into its stable native structure before the full-length protein is released from the ribosome. The majority of these cotranslational folding domains are influenced by translation kinetics which reduces their probability of cotranslational folding and consequently increases the nascent chain length at which they fold into their native structures. For about 20% of all cytosolic proteins this delay in folding can exceed the length of the completely synthesized protein, causing one or more of their domains to switch from co- to posttranslational folding solely as a result of the in vivo translation rates. These kinetic effects arise from the difference in time scales of folding and amino-acid addition, and they represent a source of metastability in Escherichia coli's proteome.

Understanding the influence of codon translation rates on cotranslational protein folding.

Protein domains can fold into stable tertiary structures while they are synthesized by the ribosome in a process known as cotranslational folding. If a protein does not fold cotranslationally, however, it has the opportunity to do so post-translationally, that is, after the nascent chain has been fully synthesized and released from the ribosome. The rate at which a ribosome adds an amino acid encoded by a particular codon to the elongating nascent chain can vary significantly and is called the codon translation rate. Recent experiments have illustrated the profound impact that codon translation rates can have on the cotranslational folding process and the acquisition of function by nascent proteins. Synonymous codon mutations in an mRNA molecule change the chemical identity of a codon and its translation rate without changing the sequence of the synthesized protein. This change in codon translation rate can, however, cause a nascent protein to malfunction as a result of cotranslational misfolding. In some situations, such dysfunction can have profound implications; for example, it can alter the substrate specificity of an ABC transporter protein, resulting in patients who are nonresponsive to chemotherapy treatment. Thus, codon translation rates are crucial in coordinating protein folding in a cellular environment and can affect downstream cellular processes that depend on the proper functioning of newly synthesized proteins. As the importance of codon translation rates makes clear, a necessary aspect of fully understanding cotranslational folding lies in considering the kinetics of the process in addition to its thermodynamics. In this Account, we examine the contributions that have been made to elucidating the mechanisms of cotranslational folding by using the theoretical and computational tools of chemical kinetics, molecular simulations, and systems biology. These efforts have extended our ability to understand, model, and predict the influence of codon translation rates on cotranslational protein folding and misfolding. The application of such approaches to this important problem is creating a framework for making quantitative predictions of the impact of synonymous codon substitutions on cotranslational folding that has led to a novel hypothesis regarding the role of fast-translating codons in coordinating cotranslational folding. In addition, it is providing new insights into proteome-wide cotranslational folding behavior and making it possible to identify potential molecular mechanisms by which molecular chaperones can influence such behavior during protein synthesis. As we discuss in this Account, bringing together these theoretical developments with experimental approaches is increasingly helping answer fundamental questions about the nature of nascent protein folding on the ribosome.

Modeling the effect of codon translation rates on co-translational protein folding mechanisms of arbitrary complexity.

In a cell, the folding of a protein molecule into tertiary structure can begin while it is synthesized by the ribosome. The rate at which individual amino acids are incorporated into the elongating nascent chain has been shown to affect the likelihood that proteins will populate their folded state, indicating that co-translational protein folding is a far from equilibrium process. Developing a theoretical framework to accurately describe this process is, therefore, crucial for advancing our understanding of how proteins acquire their functional conformation in living cells. Current state-of-the-art computational approaches, such as molecular dynamics simulations, are very demanding in terms of the required computer resources, making the simulation of co-translational protein folding difficult. Here, we overcome this limitation by introducing an efficient approach that predicts the effects that variable codon translation rates have on co-translational folding pathways. Our approach is based on Markov chains. By using as an input a relatively small number of molecular dynamics simulations, it allows for the computation of the probability that a nascent protein is in any state as a function of the translation rate of individual codons along a mRNA's open reading frame. Due to its computational efficiency and favorable scalability with the complexity of the folding mechanism, this approach could enable proteome-wide computational studies of the influence of translation dynamics on co-translational folding.

Timing is everything: unifying codon translation rates and nascent proteome behavior.

Experiments have demonstrated that changing the rate at which the ribosome translates a codon position in an mRNA molecule's open reading frame can alter the behavior of the newly synthesized protein. That is, codon translation rates can govern nascent proteome behavior. We emphasize that this phenomenon is a manifestation of the nonequilibrium nature of cotranslational processes, and as such, there exist theoretical tools that offer a potential means to quantitatively predict the influence of codon translation rates on the broad spectrum of nascent protein behaviors including cotranslational folding, aggregation, and translocation. We provide a review of the experimental evidence for the impact that codon translation rates can have, followed by a discussion of theoretical methods that can describe this phenomenon. The development and application of these tools are likely to provide fundamental insights into protein maturation and homeostasis, codon usage bias in organisms, the origins of translation related diseases, and new rational design methods for biotechnology and biopharmaceutical applications.