Cotranslational protein assembly imposes evolutionary constraints on homomeric proteins

Cellular location shapes quaternary structure of enzymes

The main forces driving protein complex evolution are currently not well understood, especially in homomers, where quaternary structure might frequently evolve neutrally. Here we examine the factors determining oligomerisation by analysing the evolution of enzymes in circumstances where homomers rarely evolve. We show that 1) In extracellular environments, most enzymes with known structure are monomers, while in the cytoplasm homomers, indicating that the evolution of oligomers is cellular environment dependent; 2) The evolution of quaternary structure within protein orthogroups is more consistent with the predictions of constructive neutral evolution than an adaptive process: quaternary structure is gained easier than it is lost, and most extracellular monomers evolved from proteins that were monomers also in their ancestral state, without the loss of interfaces. Our results indicate that oligomerisation is context-dependent, and even when adaptive, in many cases it is probably not driven by the intrinsic properties of enzymes, like their biochemical function, but rather the properties of the environment where the enzyme is active. These factors might be macromolecular crowding and excluded volume effects facilitating the evolution of interfaces, and the maintenance of cellular homeostasis through shaping cytoplasm fluidity, protein degradation, or diffusion rates.

Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes

Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.

Hallmarks and evolutionary drivers of cotranslational protein complex assembly

Recent discoveries have highlighted the prevalence of cotranslational assembly in proteomes, revealing a range of mechanisms that enables the assembly of protein complex subunits on the ribosome. Structural analyses have uncovered emergent properties that may inherently control whether a subunit undergoes cotranslational assembly. However, the evolutionary paths that have yielded such complexes over an extended timescale remain largely unclear. In this review, we reflect on historical experiments that contributed to the field, including breakthroughs that have made possible the proteome-wide detection of cotranslational assembly, and the technical challenges yet to be overcome. We introduce a simple framework that encapsulates the hallmarks of cotranslational assembly and discuss how results from new experiments are shaping our view of the mechanistic, structural and evolutionary factors driving the phenomenon.

The Effects of Codon Usage on Protein Structure and Folding

The rate of protein synthesis is slower than many folding reactions and varies depending on the synonymous codons encoding the protein sequence. Synonymous codon substitutions thus have the potential to regulate cotranslational protein folding mechanisms, and a growing number of proteins have been identified with folding mechanisms sensitive to codon usage. Typically, these proteins have complex folding pathways and kinetically stable native structures. Kinetically stable proteins may fold only once over their lifetime, and thus, codon-mediated regulation of the pioneer round of protein folding can have a lasting impact. Supporting an important role for codon usage in folding, conserved patterns of codon usage appear in homologous gene families, hinting at selection. Despite these exciting developments, there remains few experimental methods capable of quantifying translation elongation rates and cotranslational folding mechanisms in the cell, which challenges the development of a predictive understanding of how biology uses codons to regulate protein folding.

AutoRNC: An automated modeling program for building atomic models of ribosome-nascent chain complexes

The interpretation of experimental studies of co-translational protein folding often benefits from the use of computational methods that seek to model or simulate the nascent chain and its interactions with the ribosome. Building realistic 3D models of ribosome-nascent chain (RNC) constructs often requires expert knowledge, so to circumvent this issue, we describe here AutoRNC, an automated modeling program capable of constructing large numbers of plausible atomic models of RNCs within minutes. AutoRNC takes input from the user specifying any regions of the nascent chain that contain secondary or tertiary structure and attempts to build conformations compatible with those specifications-and with the constraints imposed by the ribosome-by sampling and progressively piecing together dipeptide conformations extracted from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB). Despite using only modest computational resources, we show here that AutoRNC can build plausible conformations for a wide range of RNC constructs for which experimental data have already been reported.

Co-translational Assembly Pathways of Nuclear Multiprotein Complexes Involved in the Regulation of Gene Transcription

Most factors that regulate gene transcription in eukaryotic cells are multimeric, often large, protein complexes. The understanding of the biogenesis pathways of such large and heterogeneous protein assemblies, as well as the dimerization partner choice among transcription factors, is crucial to interpret and control gene expression programs and consequent cell fate decisions. Co-translational assembly (Co-TA) is thought to play key roles in the biogenesis of protein complexes by directing complex formation during protein synthesis. In this review we discuss the principles of Co-TA with a special focus for the assembly of transcription regulatory complexes. We outline the expected molecular advantages of establishing co-translational interactions, pointing at the available, or missing, evidence for each of them. We hypothesize different molecular mechanisms based on Co-TA to explain the allocation "dilemma" of paralog proteins and subunits shared by different transcription complexes. By taking as a paradigm the different assembly pathways employed by three related transcription regulatory complexes (TFIID, SAGA and ATAC), we discuss alternative Co-TA strategies for nuclear multiprotein complexes and the widespread - yet specific - use of Co-TA for the formation of nuclear complexes involved in gene transcription. Ultimately, we outlined a series of open questions which demand well-defined lines of research to investigate the principles of gene regulation that rely on the coordinated assembly of protein complexes.

Puzzling out nuclear pore complex assembly

Nuclear pore complexes (NPCs) are sophisticated multiprotein assemblies embedded within the nuclear envelope and controlling the exchanges of molecules between the cytoplasm and the nucleus. In this review, we summarize the mechanisms by which these elaborate complexes are built from their subunits, the nucleoporins, based on our ever-growing knowledge of NPC structural organization and on the recent identification of additional features of this process. We present the constraints faced during the production of nucleoporins, their gathering into oligomeric complexes, and the formation of NPCs within nuclear envelopes, and review the cellular strategies at play, from co-translational assembly to the enrolment of a panel of cofactors. Remarkably, the study of NPCs can inform our perception of the biogenesis of multiprotein complexes in general - and vice versa.

Orientationally Averaged Version of the Rotne-Prager-Yamakawa Tensor Provides a Fast but Still Accurate Treatment of Hydrodynamic Interactions in Brownian Dynamics Simulations of Biological Macromolecules

The Brownian dynamics (BD) simulation technique is widely used to model the diffusive and conformational dynamics of complex systems comprising biological macromolecules. For the diffusive properties of macromolecules to be described correctly by BD simulations, it is necessary to include hydrodynamic interactions (HIs). When modeled at the Rotne-Prager-Yamakawa (RPY) level of theory, for example, the translational and rotational diffusion coefficients of isolated macromolecules can be accurately reproduced; when HIs are neglected, however, diffusion coefficients can be underestimated by an order of magnitude or more. The principal drawback to the inclusion of HIs in BD simulations is their computational expense, and several previous studies have sought to accelerate their modeling by developing fast approximations for the calculation of the correlated random displacements. Here, we explore the use of an alternative way to accelerate the calculation of HIs, i.e., by replacing the full RPY tensor with an orientationally averaged (OA) version which retains the distance dependence of the HIs but averages out their orientational dependence. We seek here to determine whether such an approximation can be justified in application to the modeling of typical proteins and RNAs. We show that the use of an OA-RPY tensor allows translational diffusion of macromolecules to be modeled with very high accuracy at the cost of rotational diffusion being underestimated by ∼25%. We show that this finding is independent of the type of macromolecule simulated and the level of structural resolution employed in the models. We also show, however, that these results are critically dependent on the inclusion of a non-zero term that describes the divergence of the diffusion tensor: when this term is omitted from simulations that use the OA-RPY model, unfolded macromolecules undergo rapid collapse. Our results indicate that the orientationally averaged RPY tensor is likely to be a useful, fast, approximate way of including HIs in BD simulations of intermediate-scale systems.

AutoRNC: an automated modeling program for building atomic models of ribosome-nascent chain complexes

The interpretation of experimental studies of co-translational protein folding often benefits from the use of computational methods that seek to model the nascent chain and its interactions with the ribosome. Ribosome-nascent chain (RNC) constructs studied experimentally can vary significantly in size and the extent to which they contain secondary and tertiary structure, and building realistic 3D models of them therefore often requires expert knowledge. To circumvent this issue, we describe here AutoRNC, an automated modeling program capable of constructing large numbers of plausible atomic models of RNCs within minutes. AutoRNC takes input from the user specifying any regions of the nascent chain that contain secondary or tertiary structure and attempts to build conformations compatible with those specifications - and with the constraints imposed by the ribosome - by sampling and progressively piecing together dipeptide conformations extracted from the RCSB. We first show that conformations of completely unfolded proteins built by AutoRNC in the absence of the ribosome have radii of gyration that match well with the corresponding experimental data. We then show that AutoRNC can build plausible conformations for a wide range of RNC constructs for which experimental data have already been reported. Since AutoRNC requires only modest computational resources, we anticipate that it will prove to be a useful hypothesis generator for experimental studies, for example, in providing indications of whether designed constructs are likely to be capable of folding, as well as providing useful starting points for downstream atomic or coarse-grained simulations of the conformational dynamics of RNCs.

Buffering of genetic dominance by allele-specific protein complex assembly

Protein complex assembly often occurs while subunits are being translated, resulting in complexes whose subunits were translated from the same mRNA in an allele-specific manner. It has thus been hypothesized that such cotranslational assembly may counter the assembly-mediated dominant-negative effect, whereby co-assembly of mutant and wild-type subunits "poisons" complex activity. Here, we show that cotranslationally assembling subunits are much less likely to be associated with autosomal dominant relative to recessive disorders, and that subunits with dominant-negative disease mutations are significantly depleted in cotranslational assembly compared to those associated with loss-of-function mutations. We also find that complexes with known dominant-negative effects tend to expose their interfaces late during translation, lessening the likelihood of cotranslational assembly. Finally, by combining complex properties with other features, we trained a computational model for predicting proteins likely to be associated with non-loss-of-function disease mechanisms, which we believe will be of considerable utility for protein variant interpretation.

An Orientationally Averaged Version of the Rotne-Prager-Yamakawa Tensor Provides A Fast But Still Accurate Treatment Of Hydrodynamic Interactions In Brownian Dynamics Simulations Of Biological Macromolecules

The Brownian dynamics (BD) simulation technique is widely used to model the diffusive and conformational dynamics of complex systems comprising biological macromolecules. For the diffusive properties of macromolecules to be described correctly by BD simulations, it is necessary to include hydrodynamic interactions (HI). When modeled at the Rotne-Prager-Yamakawa (RPY) level of theory, for example, the translational and rotational diffusion coefficients of isolated macromolecules can be accurately reproduced; when HIs are neglected, however, diffusion coefficients can be underestimated by an order of magnitude or more. The principal drawback to the inclusion of HIs in BD simulations is their computational expense, and several previous studies have sought to accelerate their modeling by developing fast approximations for the calculation of the correlated random displacements. Here we explore the use of an alternative way to accelerate calculation of HIs, i.e., by replacing the full RPY tensor with an orientationally averaged (OA) version which retains the distance dependence of the HIs but averages out their orientational dependence. We seek here to determine whether such an approximation can be justified in application to the modeling of typical proteins and RNAs. We show that the use of an OA RPY tensor allows translational diffusion of macromolecules to be modeled with very high accuracy at the cost of rotational diffusion being underestimated by ∼25%. We show that this finding is independent of the type of macromolecule simulated and the level of structural resolution employed in the models. We also show, however, that these results are critically dependent on the inclusion of a non-zero term that describes the divergence of the diffusion tensor: when this term is omitted from simulations that use the OA RPY model, unfolded macromolecules undergo rapid collapse. Our results indicate that the orientationally averaged RPY tensor is likely to be a useful, fast approximate way of including HIs in BD simulations of intermediate-scale systems.

N-terminal domain of ARF-GEF GNOM prevents heterodimerization with functionally divergent GNL1 in Arabidopsis

Evolutionary change following gene duplication can lead to functionally divergent paralogous proteins. If comprising identical subunits their random assortment would also form potentially detrimental heteromeric proteins. In Arabidopsis, the ARF GTPase guanine-nucleotide exchange factor GNOM is essential for polar recycling of auxin-efflux transporter PIN1 from endosomes to the basal plasma membrane whereas its paralog GNL1 mediates retrograde Golgi-endoplasmic reticulum traffic. Here we show that both GNOM and GNL1 form homodimers but no heterodimers. To assess the biological significance of this, we generated transgenic plants expressing engineered heterodimer-compatible GNOM variants. Those plants showed developmental defects such as the failure to produce lateral roots. To identify mechanisms underlying heterodimer prevention, we analyzed interactions of the N-terminal dimerization and cyclophilin-binding (DCB) domain. Each DCB domain interacted with the complementary fragment (ΔDCB) both of their own and of the paralogous protein. However, only DCB^GNOM interacted with itself whereas DCB^GNL1 failed to interact with itself and with DCB^GNOM . GNOM variants in which the DCB domain was removed or replaced by DCB^GNL1 revealed a role for DCB-DCB interaction in the prevention of GNOM-GNL1 heterodimers whereas DCB-ΔDCB interaction was essential for dimer formation and GNOM function. Our data suggest a model of early DCB-DCB interaction that facilitates GNOM homodimer formation, indirectly precluding formation of detrimental heterodimers.

A Short Tale of the Origin of Proteins and Ribosome Evolution

Proteins are the workhorses of the cell and have been key players throughout the evolution of all organisms, from the origin of life to the present era. How might life have originated from the prebiotic chemistry of early Earth? This is one of the most intriguing unsolved questions in biology. Currently, however, it is generally accepted that amino acids, the building blocks of proteins, were abiotically available on primitive Earth, which would have made the formation of early peptides in a similar fashion possible. Peptides are likely to have coevolved with ancestral forms of RNA. The ribosome is the most evident product of this coevolution process, a sophisticated nanomachine that performs the synthesis of proteins codified in genomes. In this general review, we explore the evolution of proteins from their peptide origins to their folding and regulation based on the example of superoxide dismutase (SOD1), a key enzyme in oxygen metabolism on modern Earth.

Large protein complex interfaces have evolved to promote cotranslational assembly

Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromeric subunits in bacterial, yeast, and human complexes. When considering all together, we observe the N-terminal interface to be larger than the C-terminal interface 54% of the time, increasing to 64% when we exclude subunits with only small interfaces, which are unlikely to cotranslationally assemble. This strongly suggests that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding.

Volumetric Strategy for Quantitatively Elucidating a Local Hydration Network around a G-Quadruplex

Hydration around nucleic acids, such as DNA and RNA, is an important factor not only for the stability of nucleic acids but also for their interaction with binding molecules. Thus, it is necessary to quantitatively elucidate the hydration properties of nucleic acids around a certain structure. In this study, volumetric changes in G-quadruplex (G4) RNA formation were investigated by systematically changing the number of G-quartet stacks under high pressure. The volumetric contribution at the level of each G4 structural unit revealed that the core G4 helix was significantly more dehydrated than the other parts, including the edges of G-quartets and loops. These findings will help in predicting the binding of G4 ligands on the surface of G4, depending on the chemical structure of the ligand and solution environment. Therefore, the preset volumetric parameter provides information that can predict molecular interactions in G4 formations during molecular crowding in cells.

Proteome-wide landscape of solubility limits in a bacterial cell

Proteins are prone to aggregate when expressed above their solubility limits. Aggregation may occur rapidly, potentially as early as proteins emerge from the ribosome, or slowly, following synthesis. However, in vivo data on aggregation rates are scarce. Here, we classified the Escherichia coli proteome into rapidly and slowly aggregating proteins using an in vivo image-based screen coupled with machine learning. We find that the majority (70%) of cytosolic proteins that become insoluble upon overexpression have relatively low rates of aggregation and are unlikely to aggregate co-translationally. Remarkably, such proteins exhibit higher folding rates compared to rapidly aggregating proteins, potentially implying that they aggregate after reaching their folded states. Furthermore, we find that a substantial fraction (~ 35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our study provides a global view of aggregation rates and hence solubility limits of proteins in a bacterial cell.

Co-translational assembly orchestrates competing biogenesis pathways

During the co-translational assembly of protein complexes, a fully synthesized subunit engages with the nascent chain of a newly synthesized interaction partner. Such events are thought to contribute to productive assembly, but their exact physiological relevance remains underexplored. Here, we examine structural motifs contained in nucleoporins for their potential to facilitate co-translational assembly. We experimentally test candidate structural motifs and identify several previously unknown co-translational interactions. We demonstrate by selective ribosome profiling that domain invasion motifs of beta-propellers, coiled-coils, and short linear motifs may act as co-translational assembly domains. Such motifs are often contained in proteins that are members of multiple complexes (moonlighters) and engage with closely related paralogs. Surprisingly, moonlighters and paralogs assemble co-translationally in only some but not all of the relevant biogenesis pathways. Our results highlight the regulatory complexity of assembly pathways.

Protein structure and aggregation: a marriage of necessity ruled by aggregation gatekeepers

Protein aggregation propensity is a pervasive and seemingly inescapable property of proteomes. Strikingly, a significant fraction of the proteome is supersaturated, meaning that, for these proteins, their native conformation is less stable than the aggregated state. Maintaining the integrity of a proteome under such conditions is precarious and requires energy-consuming proteostatic regulation. Why then is aggregation propensity maintained at such high levels over long evolutionary timescales? Here, we argue that the conformational stability of the native and aggregated states are correlated thermodynamically and that codon usage strengthens this correlation. As a result, the folding of stable proteins requires kinetic control to avoid aggregation, provided by aggregation gatekeepers. These unique residues are evolutionarily selected to kinetically favor native folding, either on their own or by coopting chaperones.

Heterodimer Formation of the Homodimeric ABC Transporter OpuA

Many proteins have a multimeric structure and are composed of two or more identical subunits. While this can be advantageous for the host organism, it can be a challenge when targeting specific residues in biochemical analyses. In vitro splitting and re-dimerization to circumvent this problem is a tedious process that requires stable proteins. We present an in vivo approach to transform homodimeric proteins into apparent heterodimers, which then can be purified using two-step affinity-tag purification. This opens the door to both practical applications such as smFRET to probe the conformational dynamics of homooligomeric proteins and fundamental research into the mechanism of protein multimerization, which is largely unexplored for membrane proteins. We show that expression conditions are key for the formation of heterodimers and that the order of the differential purification and reconstitution of the protein into nanodiscs is important for a functional ABC-transporter complex.

Solubility-Weighted Index: fast and accurate prediction of protein solubility

Motivation

Recombinant protein production is a widely used technique in the biotechnology and biomedical industries, yet only a quarter of target proteins are soluble and can therefore be purified.

Results

We have discovered that global structural flexibility, which can be modeled by normalized B-factors, accurately predicts the solubility of 12 216 recombinant proteins expressed in Escherichia coli. We have optimized these B-factors, and derived a new set of values for solubility scoring that further improves prediction accuracy. We call this new predictor the ‘Solubility-Weighted Index’ (SWI). Importantly, SWI outperforms many existing protein solubility prediction tools. Furthermore, we have developed ‘SoDoPE’ (Soluble Domain for Protein Expression), a web interface that allows users to choose a protein region of interest for predicting and maximizing both protein expression and solubility.

Availability and implementation

The SoDoPE web server and source code are freely available at https://tisigner.com/sodope and https://github.com/Gardner-BinfLab/TISIGNER-ReactJS, respectively. The code and data for reproducing our analysis can be found at https://github.com/Gardner-BinfLab/SoDoPE_paper_2020.

Supplementary information

Supplementary data are available at Bioinformatics online.

Interactions between nascent proteins translated by adjacent ribosomes drive homomer assembly

Accurate assembly of newly synthesized proteins into functional oligomers is crucial for cell activity. In this study, we investigated whether direct interaction of two nascent proteins, emerging from nearby ribosomes (co-co assembly), constitutes a general mechanism for oligomer formation. We used proteome-wide screening to detect nascent chain-connected ribosome pairs and identified hundreds of homomer subunits that co-co assemble in human cells. Interactions are mediated by five major domain classes, among which N-terminal coiled coils are the most prevalent. We were able to reconstitute co-co assembly of nuclear lamin in Escherichia coli, demonstrating that dimer formation is independent of dedicated assembly machineries. Co-co assembly may thus represent an efficient way to limit protein aggregation risks posed by diffusion-driven assembly routes and ensure isoform-specific homomer formation.

Riboexp: an interpretable reinforcement learning framework for ribosome density modeling

Translation elongation is a crucial phase during protein biosynthesis. In this study, we develop a novel deep reinforcement learning-based framework, named Riboexp, to model the determinants of the uneven distribution of ribosomes on mRNA transcripts during translation elongation. In particular, our model employs a policy network to perform a context-dependent feature selection in the setting of ribosome density prediction. Our extensive tests demonstrated that Riboexp can significantly outperform the state-of-the-art methods in predicting ribosome density by up to 5.9% in terms of per-gene Pearson correlation coefficient on the datasets from three species. In addition, Riboexp can indicate more informative sequence features for the prediction task than other commonly used attribution methods in deep learning. In-depth analyses also revealed the meaningful biological insights generated by the Riboexp framework. Moreover, the application of Riboexp in codon optimization resulted in an increase of protein production by around 31% over the previous state-of-the-art method that models ribosome density. These results have established Riboexp as a powerful and useful computational tool in the studies of translation dynamics and protein synthesis. Availability: The data and code of this study are available on GitHub: https://github.com/Liuxg16/Riboexp. Contact:  zengjy321@tsinghua.edu.cn; songsen@tsinghua.edu.cn.

Designer protein assemblies with tunable phase diagrams in living cells

Protein self-organization is a hallmark of biological systems. Although the physicochemical principles governing protein-protein interactions have long been known, the principles by which such nanoscale interactions generate diverse phenotypes of mesoscale assemblies, including phase-separated compartments, remain challenging to characterize. To illuminate such principles, we create a system of two proteins designed to interact and form mesh-like assemblies. We devise a new strategy to map high-resolution phase diagrams in living cells, which provide self-assembly signatures of this system. The structural modularity of the two protein components allows straightforward modification of their molecular properties, enabling us to characterize how interaction affinity impacts the phase diagram and material state of the assemblies in vivo. The phase diagrams and their dependence on interaction affinity were captured by theory and simulations, including out-of-equilibrium effects seen in growing cells. Finally, we find that cotranslational protein binding suffices to recruit a messenger RNA to the designed micron-scale structures.

Codon Selection Affects Recruitment of Ribosome-Associating Factors during Translation

An intriguing aspect of protein synthesis is how cotranslational events are managed inside the cell. In this study, we developed an in vivo bimolecular fluorescence complementation assay coupled to SecM stalling (BiFC-SecM) to study how codon usage influences the interactions of ribosome-associating factors that occur cotranslationally. We profiled ribosomal associations of a number of proteins, and observed differential association of chaperone proteins TF, DnaK, GroEL, and translocation factor Ffh as a result of introducing synonymous codon substitutions that change the affinity of the translating sequence to the ribosomal anti-Shine-Dalgarno (aSD) sequence. The use of pausing sequences within proteins regulates their transit within the translating ribosome. Our results indicate that the dynamics between cellular factors and the new polypeptide chain are affected by how codon composition is designed. Furthermore, associating factors may play a role in processes including protein quality control (folding and degradation) and cellular respiration.

Cotranslational folding allows misfolding-prone proteins to circumvent deep kinetic traps

Many large proteins suffer from slow or inefficient folding in vitro. It has long been known that this problem can be alleviated in vivo if proteins start folding cotranslationally. However, the molecular mechanisms underlying this improvement have not been well established. To address this question, we use an all-atom simulation-based algorithm to compute the folding properties of various large protein domains as a function of nascent chain length. We find that for certain proteins, there exists a narrow window of lengths that confers both thermodynamic stability and fast folding kinetics. Beyond these lengths, folding is drastically slowed by nonnative interactions involving C-terminal residues. Thus, cotranslational folding is predicted to be beneficial because it allows proteins to take advantage of this optimal window of lengths and thus avoid kinetic traps. Interestingly, many of these proteins' sequences contain conserved rare codons that may slow down synthesis at this optimal window, suggesting that synthesis rates may be evolutionarily tuned to optimize folding. Using kinetic modeling, we show that under certain conditions, such a slowdown indeed improves cotranslational folding efficiency by giving these nascent chains more time to fold. In contrast, other proteins are predicted not to benefit from cotranslational folding due to a lack of significant nonnative interactions, and indeed these proteins' sequences lack conserved C-terminal rare codons. Together, these results shed light on the factors that promote proper protein folding in the cell and how biomolecular self-assembly may be optimized evolutionarily.

Ligand Binding Site Structure Shapes Folding, Assembly and Degradation of Homomeric Protein Complexes

Ligand binding site structure has profound consequences for the evolution of function of protein complexes, particularly in homomers—complexes comprising multiple copies of the same protein. Previously, we have shown that homomers with multichain binding sites (MBSs) are characterized by more conserved binding sites and quaternary structure, and qualitatively different allosteric pathways than homomers with single-chain binding sites (SBSs) or monomers. Here, using computational methods, we show that the folds of single-domain MBS and SBS homomers are different, and SBS homomers are likely to be folded cotranslationally, while MBS homomers are more likely to form post-translationally and rely on more advanced folding-assistance and quality control mechanisms, which include chaperonins. In addition, our findings demonstrate that MBS homomers are qualitatively different from monomers, while SBS homomers are much less distinct, supporting the hypothesis that the evolution of quaternary structure in SBS homomers is significantly influenced by stochastic processes.

The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs

Gene duplication is a driver of the evolution of new functions. The duplication of genes encoding homomeric proteins leads to the formation of homomers and heteromers of paralogs, creating new complexes after a single duplication event. The loss of these heteromers may be required for the two paralogs to evolve independent functions. Using yeast as a model, we find that heteromerization is frequent among duplicated homomers and correlates with functional similarity between paralogs. Using in silico evolution, we show that for homomers and heteromers sharing binding interfaces, mutations in one paralog can have structural pleiotropic effects on both interactions, resulting in highly correlated responses of the complexes to selection. Therefore, heteromerization could be preserved indirectly due to selection for the maintenance of homomers, thus slowing down functional divergence between paralogs. We suggest that paralogs can overcome the obstacle of structural pleiotropy by regulatory evolution at the transcriptional and post-translational levels.

Mechanisms of Cotranslational Maturation of Newly Synthesized Proteins

The timely production of functional proteins is of critical importance for the biological activity of cells. To reach the functional state, newly synthesized polypeptides have to become enzymatically processed, folded, and assembled into oligomeric complexes and, for noncytosolic proteins, translocated across membranes. Key activities of these processes occur cotranslationally, assisted by a network of machineries that transiently engage nascent polypeptides at distinct phases of translation. The sequence of events is tuned by intrinsic features of the nascent polypeptides and timely association of factors with the translating ribosome. Considering the dynamics of translation, the heterogeneity of cellular proteins, and the diversity of interaction partners, it is a major cellular achievement that these processes are temporally and spatially so precisely coordinated, minimizing the generation of damaged proteins. This review summarizes the current progress we have made toward a comprehensive understanding of the cotranslational interactions of nascent chains, which pave the way to their functional state.

Evolution of interface binding strengths in simplified model of protein quaternary structure

The self-assembly of proteins into protein quaternary structures is of fundamental importance to many biological processes, and protein misassembly is responsible for a wide range of proteopathic diseases. In recent years, abstract lattice models of protein self-assembly have been used to simulate the evolution and assembly of protein quaternary structure, and to provide a tractable way to study the genotype-phenotype map of such systems. Here we generalize these models by representing the interfaces as mutable binary strings. This simple change enables us to model the evolution of interface strengths, interface symmetry, and deterministic assembly pathways. Using the generalized model we are able to reproduce two important results established for real protein complexes: The first is that protein assembly pathways are under evolutionary selection to minimize misassembly. The second is that the assembly pathway of a complex mirrors its evolutionary history, and that both can be derived from the relative strengths of interfaces. These results demonstrate that the generalized lattice model offers a powerful new idealized framework to facilitate the study of protein self-assembly processes and their evolution.