Nature and Regulation of Protein Folding on the Ribosome

Hsp90, a team player in protein quality control and the stress response in bacteria

SUMMARYHeat shock protein 90 (Hsp90) participates in proteostasis by facilitating protein folding, activation, disaggregation, prevention of aggregation, degradation, and protection against degradation of various cellular proteins. It is highly conserved from bacteria to humans. In bacteria, protein remodeling by Hsp90 involves collaboration with the Hsp70 molecular chaperone and Hsp70 cochaperones. In eukaryotes, protein folding by Hsp90 is more complex and involves collaboration with many Hsp90 cochaperones as well as Hsp70 and Hsp70 cochaperones. This review focuses primarily on bacterial Hsp90 and highlights similarities and differences between bacterial and eukaryotic Hsp90. Seminal research findings that elucidate the structure and the mechanisms of protein folding, disaggregation, and reactivation promoted by Hsp90 are discussed. Understanding the mechanisms of bacterial Hsp90 will provide fundamental insight into the more complex eukaryotic chaperone systems.

Unraveling the genetic and molecular basis of heat stress in cotton

Human activities and climate change have resulted in frequent and intense weather fluctuations, leading to diverse abiotic stresses on crops which hampers greatly their metabolic activities. Heat stress, a prevalent abiotic factor, significantly influences cotton plant biological activities resulting in reducing yield and production. We must deepen our understanding of how plants respond to heat stress across various dimensions, encompassing genes, RNAs, proteins, metabolites for effective cotton breeding. Multi-omics methods, primarily genomics, transcriptomics, proteomics, metabolomics, and phenomics, proves instrumental in studying cotton's responses to abiotic stresses. Integrating genomics, transcriptomics, proteomics, and metabolomic is imperative for our better understanding regarding genetics and molecular basis of heat tolerance in cotton. The current review explores fundamental omics techniques, covering genomics, transcriptomics, proteomics, and metabolomics, to highlight the progress made in cotton omics research.

Navigating the complexities of multi-domain protein folding

Proteome complexity has expanded tremendously over evolutionary time, enabling biological diversification. Much of this complexity is achieved by combining a limited set of structural units into long polypeptides. This widely used evolutionary strategy poses challenges for folding of the resulting multi-domain proteins. As a consequence, their folding differs from that of small single-domain proteins, which generally fold quickly and reversibly. Co-translational processes and chaperone interactions are important aspects of multi-domain protein folding. In this review, we discuss some of the recent experimental progress toward understanding these processes.

GNN Codon Adjacency Tunes Protein Translation

The central dogma treats the ribosome as a molecular machine that reads one mRNA codon at a time as it adds each amino acid to its growing peptide chain. However, this and previous studies suggest that ribosomes actually perceive pairs of adjacent codons as they take three-nucleotide steps along the mRNA. We examined GNN codons, which we find are surprisingly overrepresented in eukaryote protein-coding open reading frames (ORFs), especially immediately after NNU codons. Ribosome profiling experiments in yeast revealed that ribosomes with NNU at their aminoacyl (A) site have particularly elevated densities when NNU is immediately followed (3') by a GNN codon, indicating slower mRNA threading of the NNU codon from the ribosome's A to peptidyl (P) sites. Moreover, if the assessment was limited to ribosomes that have only recently arrived at the next codon, by examining 21-nucleotide ribosome footprints (21-nt RFPs), elevated densities were observed for multiple codon classes when followed by GNN. This striking translation slowdown at adjacent 5'-NNN GNN codon pairs is likely mediated, in part, by the ribosome's CAR surface, which acts as an extension of the A-site tRNA anticodon during ribosome translocation and interacts through hydrogen bonding and pi stacking with the GNN codon. The functional consequences of 5'-NNN GNN codon adjacency are expected to influence the evolution of protein coding sequences.

Nascent chains derived from a foldable protein sequence interact with specific ribosomal surface sites near the exit tunnel

In order to become bioactive, proteins must be translated and protected from aggregation during biosynthesis. The ribosome and molecular chaperones play a key role in this process. Ribosome-bound nascent chains (RNCs) of intrinsically disordered proteins and RNCs bearing a signal/arrest sequence are known to interact with ribosomal proteins. However, in the case of RNCs bearing foldable protein sequences, not much information is available on these interactions. Here, via a combination of chemical crosslinking and time-resolved fluorescence-anisotropy, we find that nascent chains of the foldable globin apoHmp1-140 interact with ribosomal protein L23 and have a freely-tumbling non-interacting N-terminal compact region comprising 63-94 residues. Longer RNCs (apoHmp1-189) also interact with an additional yet unidentified ribosomal protein, as well as with chaperones. Surprisingly, the apparent strength of RNC/r-protein interactions does not depend on nascent-chain sequence. Overall, foldable nascent chains establish and expand interactions with selected ribosomal proteins and chaperones, as they get longer. These data are significant because they reveal the interplay between independent conformational sampling and nascent-protein interactions with the ribosomal surface.

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.

Roles of Nucleic Acids in Protein Folding, Aggregation, and Disease

The role of nucleic acids in protein folding and aggregation is an area of continued research, with relevance to understanding both basic biological processes and disease. In this review, we provide an overview of the trajectory of research on both nucleic acids as chaperones and their roles in several protein misfolding diseases. We highlight key questions that remain on the biophysical and biochemical specifics of how nucleic acids have large effects on multiple proteins' folding and aggregation behavior and how this pertains to multiple protein misfolding diseases.

Morphological features and types of aggregated structures

In vivo, protein aggregation arises due to incorrect folding or misfolding. The aggregation of proteins into amyloid fibrils is the characteristic feature of various misfolding diseases known as amyloidosis, such as Alzheimer's and Parkinson's disease. The heterogeneous nature of these fibrils restricts the extent to which their structure may be characterized. Advancements in techniques, such as X-ray diffraction, cryo-electron microscopy, and solid-state NMR have yielded intricate insights into structures of different amyloid fibrils. These studies have unveiled a diverse range of polymorphic structures that typically conform to the cross-β amyloid pattern. This chapter provides a concise overview of the information acquired in the field of protein aggregation, with particular focus on amyloids.

Amyloid-induced neurodegeneration: A comprehensive review through aggregomics perception of proteins in health and pathology

Amyloidosis of protein caused by fibrillation and aggregation are some of the most exciting new edges not only in protein sciences but also in molecular medicines. The present review discusses recent advancements in the field of neurodegenerative diseases and therapeutic applications with ongoing clinical trials, featuring new areas of protein misfolding resulting in aggregation. The endogenous accretion of protein fibrils having fibrillar morphology symbolizes the beginning of neuro-disorders. Prognostic amyloidosis is prominent in numerous degenerative infections such as Alzheimer's and Parkinson's disease, Amyotrophic lateral sclerosis (ALS), etc. However, the molecular basis determining the intracellular or extracellular evidence of aggregates, playing a significant role as a causative factor in neurodegeneration is still unclear. Structural conversions and protein self-assembly resulting in the formation of amyloid oligomers and fibrils are important events in the pathophysiology of the disease. This comprehensive review sheds light on the evolving landscape of potential treatment modalities, highlighting the ongoing clinical trials and the potential socio-economic impact of novel therapeutic interventions in the realm of neurodegenerative diseases. Furthermore, many drugs are undergoing different levels of clinical trials that would certainly help in treating these disorders and will surely improve the socio-impact of human life.

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.

Exploring the potential of amyloids in biomedical applications: A review

Amyloid is defined as a fibrous quaternary structure formed by assembling protein or peptide monomers into intermolecularly hydrogen linked β-sheets. There is a prevalent issue with protein aggregation and the buildup of amyloid molecules, which results in human neurological illnesses including Alzheimer's and Parkinson's. But it is now evident that many organisms, like bacteria, fungi as well as humans, use the same fibrillar structure to carry out a variety of biological functions, such as structure and protection supporting interface transitions and cell-cell recognition, protein control and storage, epigenetic inheritance, and memory. Recent discoveries of self-assembling amyloidogenic peptides and proteins, based on the amyloid core structure, give rise to interesting biomaterials with potential uses in numerous industries. These functions dramatically diverge from the initial conception of amyloid fibrils as intrinsically diseased entities. Apart from the natural ability of amyloids to spontaneously arrange themselves and their exceptional material characteristics, this aspect has prompted extensive research into engineering artificial amyloids for generating various nanostructures, molecular substances, and combined materials. Here, we discuss significant developments in the artificial design of useful amyloids as well as how amyloid materials serve as examples of how function emerges from protein self-assembly at various length scales.

Folding kinetics of an entangled protein

The possibility of the protein backbone adopting lasso-like entangled motifs has attracted increasing attention. After discovering the surprising abundance of natively entangled protein domain structures, it was shown that misfolded entangled subpopulations might become thermosensitive or escape the homeostasis network just after translation. To investigate the role of entanglement in shaping folding kinetics, we introduce a novel indicator and analyze simulations of a coarse-grained, structure-based model for two small single-domain proteins. The model recapitulates the well-known two-state folding mechanism of a non-entangled SH3 domain. However, despite its small size, a natively entangled antifreeze RD1 protein displays a rich refolding behavior, populating two distinct kinetic intermediates: a short-lived, entangled, near-unfolded state and a longer-lived, non-entangled, near-native state. The former directs refolding along a fast pathway, whereas the latter is a kinetic trap, consistently with known experimental evidence of two different characteristic times. Upon trapping, the natively entangled loop folds without being threaded by the N-terminal residues. After trapping, the native entangled structure emerges by either backtracking to the unfolded state or threading through the already formed but not yet entangled loop. Along the fast pathway, trapping does not occur because the native contacts at the closure of the lasso-like loop fold after those involved in the N-terminal thread, confirming previous predictions. Despite this, entanglement may appear already in unfolded configurations. Remarkably, a longer-lived, near-native intermediate, with non-native entanglement properties, recalls what was observed in cotranslational folding.

Control of mRNA fate by its encoded nascent polypeptide

Cells tightly regulate mRNA processing, localization, and stability to ensure accurate gene expression in diverse cellular states and conditions. Most of these regulatory steps have traditionally been thought to occur before translation by the action of RNA-binding proteins. Several recent discoveries highlight multiple co-translational mechanisms that modulate mRNA translation, localization, processing, and stability. These mechanisms operate by recognition of the nascent protein, which is necessarily coupled to its encoding mRNA during translation. Hence, the distinctive sequence or structure of a particular nascent chain can recruit recognition factors with privileged access to the corresponding mRNA in an otherwise crowded cellular environment. Here, we draw on both well-established and recent examples to provide a conceptual framework for how cells exploit nascent protein recognition to direct mRNA fate. These mechanisms allow cells to dynamically and specifically regulate their transcriptomes in response to changes in cellular states to maintain protein homeostasis.

Improving the soluble expression of difficult-to-express proteins in prokaryotic expression system via protein engineering and synthetic biology strategies

Solubility and folding stability are key concerns for difficult-to-express proteins (DEPs) restricted by amino acid sequences and superarchitecture, resolved by the precise distribution of amino acids and molecular interactions as well as the assistance of the expression system. Therefore, an increasing number of tools are available to achieve efficient expression of DEPs, including directed evolution, solubilization partners, chaperones, and affluent expression hosts, among others. Furthermore, genome editing tools, such as transposons and CRISPR Cas9/dCas9, have been developed and expanded to construct engineered expression hosts capable of efficient expression ability of soluble proteins. Accounting for the accumulated knowledge of the pivotal factors in the solubility and folding stability of proteins, this review focuses on advanced technologies and tools of protein engineering, protein quality control systems, and the redesign of expression platforms in prokaryotic expression systems, as well as advances of the cell-free expression technologies for membrane proteins production.

Dissecting the brain with spatially resolved multi-omics

Recent studies have highlighted spatially resolved multi-omics technologies, including spatial genomics, transcriptomics, proteomics, and metabolomics, as powerful tools to decipher the spatial heterogeneity of the brain. Here, we focus on two major approaches in spatial transcriptomics (next-generation sequencing-based technologies and image-based technologies), and mass spectrometry imaging technologies used in spatial proteomics and spatial metabolomics. Furthermore, we discuss their applications in neuroscience, including building the brain atlas, uncovering gene expression patterns of neurons for special behaviors, deciphering the molecular basis of neuronal communication, and providing a more comprehensive explanation of the molecular mechanisms underlying central nervous system disorders. However, further efforts are still needed toward the integrative application of multi-omics technologies, including the real-time spatial multi-omics analysis in living cells, the detailed gene profile in a whole-brain view, and the combination of functional verification.

The central role of translation elongation in response to stress

Protein synthesis is essential to support homeostasis, and thus, must be highly regulated during cellular response to harmful environments. All stages of translation are susceptible to regulation under stress, however, the mechanisms involved in translation regulation beyond initiation have only begun to be elucidated. Methodological advances enabled critical discoveries on the control of translation elongation, highlighting its important role in translation repression and the synthesis of stress-response proteins. In this article, we discuss recent findings on mechanisms of elongation control mediated by ribosome pausing and collisions and the availability of tRNAs and elongation factors. We also discuss how elongation intersects with distinct modes of translation control, further supporting cellular viability and gene expression reprogramming. Finally, we highlight how several of these pathways are reversibly regulated, emphasizing the dynamics of translation control during stress-response progression. A comprehensive understanding of translation regulation under stress will produce fundamental knowledge of protein dynamics while opening new avenues and strategies to overcome dysregulated protein production and cellular sensitivity to stress.

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.

Entangled Motifs in Membrane Protein Structures

Entangled motifs are found in one-third of protein domain structures, a reference set that contains mostly globular proteins. Their properties suggest a connection with co-translational folding. Here, we wish to investigate the presence and properties of entangled motifs in membrane protein structures. From existing databases, we build a non-redundant data set of membrane protein domains, annotated with the monotopic/transmembrane and peripheral/integral labels. We evaluate the presence of entangled motifs using the Gaussian entanglement indicator. We find that entangled motifs appear in one-fifth of transmembrane and one-fourth of monotopic proteins. Surprisingly, the main features of the distribution of the values of the entanglement indicator are similar to the reference case of general proteins. The distribution is conserved across different organisms. Differences with respect to the reference set emerge when considering the chirality of entangled motifs. Although the same chirality bias is found for single-winding motifs in both membrane and reference proteins, the bias is reversed, strikingly, for double-winding motifs only in the reference set. We speculate that these observations can be rationalized in terms of the constraints exerted on the nascent chain by the co-translational bio-genesis machinery, which is different for membrane and globular proteins.

Functional advantages of building nanosystems using multiple molecular components

Over half of all the natural nanomachines in living organisms are multimeric and likely exploit the self-assembly of their components to provide functional benefits. However, the advantages and disadvantages of building nanosystems using multiple molecular components remain relatively unexplored at the thermodynamic, kinetic and functional levels. In this study we used theory and a simple DNA-based model that forms the same nanostructures with different numbers of components to advance our knowledge in this area. Despite its lower assembly rate, we found that a system built with three components may undergo a more cooperative assembly transition from less preorganized components, which facilitates the emergence of functionalities. Using simple variations of its components, we also found that trimeric nanosystems display a much higher level of programmability than their dimeric counterparts because they can assemble with various levels of cooperativity, self-inhibition and time-dependent properties. We show here how two simple strategies (for example, cutting and adding components) can be employed to efficiently programme the regulatory function of a more complex, artificially selected, RNA-cleaving catalytic nanosystem.

Profiling the Hsp70 Chaperone Network in Heat-Induced Proteotoxic Stress Models of Human Neurons

Heat stroke is among the most hazardous hyperthermia-related illnesses and an emerging threat to humans from climate change. Acute brain injury and long-lasting brain damage are the hallmarks of this condition. Hyperthermic neurological manifestations are remarkable for their damage correlation with stress amplitude and long-term persistence. Hyperthermia-induced protein unfolding, and nonspecific aggregation accumulation have neurotoxic effects and contribute to the pathogenesis of brain damage in heat stroke. Therefore, we generated heat-induced, dose-responsive extreme and mild proteotoxic stress models in medulloblastoma [Daoy] and neuroblastoma [SH-SY5Y] and differentiated SH-SY5Y neuronal cells. We show that heat-induced protein aggregation is associated with reduced cell proliferation and viability. Higher protein aggregation in differentiated neurons than in neuroblastoma precursors suggests a differential neuronal vulnerability to heat. We characterized the neuronal heat shock response through RT-PCR array analysis of eighty-four genes involved in protein folding and protein quality control (PQC). We identify seventeen significantly expressed genes, five of which are Hsp70 chaperones, and four of their known complementing function proteins. Protein expression analysis determined the individual differential contribution of the five Hsp70 chaperones to the proteotoxic stress response and the significance of only two members under mild conditions. The co-expression analysis reveals significantly high co-expression between the Hsp70 chaperones and their interacting partners. The findings of this study lend support to the hypothesis that hyperthermia-induced proteotoxicity may underlie the brain injury of heat stroke. Additionally, this study presents a comprehensive map of the Hsp70 network in these models with potential clinical and translational implications.

Stress-Mediated Attenuation of Translation Undermines T-cell Activity in Cancer

Protein synthesis supports robust immune responses. Nutrient competition and global cell stressors in the tumor microenvironment (TME) may impact protein translation in T cells and antitumor immunity. Using human and mouse tumors, we demonstrated here that protein translation in T cells is repressed in solid tumors. Reduced glucose availability to T cells in the TME led to activation of the unfolded protein response (UPR) element eIF2α (eukaryotic translation initiation factor 2 alpha). Genetic mouse models revealed that translation attenuation mediated by activated p-eIF2α undermines the ability of T cells to suppress tumor growth. Reprograming T-cell metabolism was able to alleviate p-eIF2α accumulation and translational attenuation in the TME, allowing for sustained protein translation. Metabolic and pharmacological approaches showed that proteasome activity mitigates induction of p-eIF2α to support optimal antitumor T-cell function, protecting from translation attenuation and enabling prolonged cytokine synthesis in solid tumors. Together, these data identify a new therapeutic avenue to fuel the efficacy of tumor immunotherapy.

SIGNIFICANCE

Proteasome function is a necessary cellular component for endowing T cells with tumor killing capacity by mitigating translation attenuation resulting from the unfolded protein response induced by stress in the tumor microenvironment.

Modulating co-translational protein folding by rational design and ribosome engineering

Co-translational folding is a fundamental process for the efficient biosynthesis of nascent polypeptides that emerge through the ribosome exit tunnel. To understand how this process is modulated by the shape and surface of the narrow tunnel, we have rationally engineered three exit tunnel protein loops (uL22, uL23 and uL24) of the 70S ribosome by CRISPR/Cas9 gene editing, and studied the co-translational folding of an immunoglobulin-like filamin domain (FLN5). Our thermodynamics measurements employing ¹⁹F/¹⁵N/methyl-TROSY NMR spectroscopy together with cryo-EM and molecular dynamics simulations reveal how the variations in the lengths of the loops present across species exert their distinct effects on the free energy of FLN5 folding. A concerted interplay of the uL23 and uL24 loops is sufficient to alter co-translational folding energetics, which we highlight by the opposite folding outcomes resulting from their extensions. These subtle modulations occur through a combination of the steric effects relating to the shape of the tunnel, the dynamic interactions between the ribosome surface and the unfolded nascent chain, and its altered exit pathway within the vestibule. These results illustrate the role of the exit tunnel structure in co-translational folding, and provide principles for how to remodel it to elicit a desired folding outcome.

The narrow exit tunnel of the ribosome is important for cotranslational protein folding. Here, authors show that their rationally designed and engineered exit tunnel protein loops modulate the free energy of nascent chain dynamics and folding.

Heat-Induced Proteotoxic Stress Response in Placenta-Derived Stem Cells (PDSCs) Is Mediated through HSPA1A and HSPA1B with a Potential Higher Role for HSPA1B

Placenta-derived stem cells (PDSCs), due to unique traits such as mesenchymal and embryonic characteristics and the absence of ethical constraints, are in a clinically and therapeutically advantageous position. To aid in stemness maintenance, counter pathophysiological stresses, and withstand post-differentiation challenges, stem cells require elevated protein synthesis and consequently augmented proteostasis. Stem cells exhibit source-specific proteostasis traits, making it imperative to study them individually from different sources. These studies have implications for understanding stem cell biology and exploitation in the augmentation of therapeutic applications. Here, we aim to identify the primary determinants of proteotoxic stress response in PDSCs. We generated heat-induced dose-responsive proteotoxic stress models of three stem cell types: placental origin cells, the placenta-derived mesenchymal stem cells (pMSCs), maternal origin cells, the decidua parietalis mesenchymal stem cells (DPMSCs), and the maternal–fetal interface cells, decidua basalis mesenchymal stem cells (DBMSCs), and measured stress induction through biochemical and cell proliferation assays. RT-PCR array analysis of 84 genes involved in protein folding and protein quality control led to the identification of Hsp70 members HSPA1A and HSPA1B as the prominent ones among 17 significantly expressed genes and with further analysis at the protein level through Western blotting. A kinetic analysis of HSPA1A and HSPA1B gene and protein expression allowed a time series evaluation of stress response. As identified by protein expression, an active stress response is in play even at 24 h. More prominent differences in expression between the two homologs are detected at the translational level, alluding to a potential higher requirement for HSPA1B during proteotoxic stress response in PDSCs.

The ribosome stabilizes partially folded intermediates of a nascent multi-domain protein

Co-translational folding is crucial to ensure the production of biologically active proteins. The ribosome can alter the folding pathways of nascent polypeptide chains, yet a structural understanding remains largely inaccessible experimentally. We have developed site-specific labelling of nascent chains to detect and measure, using ¹⁹F nuclear magnetic resonance (NMR) spectroscopy, multiple states accessed by an immunoglobulin-like domain within a tandem repeat protein during biosynthesis. By examining ribosomes arrested at different stages during translation of this common structural motif, we observe highly broadened NMR resonances attributable to two previously unidentified intermediates, which are stably populated across a wide folding transition. Using molecular dynamics simulations and corroborated by cryo-electron microscopy, we obtain models of these partially folded states, enabling experimental verification of a ribosome-binding site that contributes to their high stabilities. We thus demonstrate a mechanism by which the ribosome could thermodynamically regulate folding and other co-translational processes.

Most proteins must fold co-translationally on the ribosome to adopt biologically active conformations, yet structural, mechanistic descriptions are lacking. Using ¹⁹F NMR spectroscopy to study a nascent multi-domain protein has now enabled the identification of two co-translational folding intermediates that are significantly more stable than intermediates formed off the ribosome, suggesting that the ribosome may thermodynamically regulate folding.

Mechanical regulation of talin through binding and history-dependent unfolding

Talin is a force-sensing multidomain protein and a major player in cellular mechanotransduction. Here, we use single-molecule magnetic tweezers to investigate the mechanical response of the R8 rod domain of talin. We find that under various force cycles, the R8 domain of talin can display a memory-dependent behavior: At the same low force (<10 pN), the same protein molecule shows vastly different unfolding kinetics. This history-dependent behavior indicates the evolution of a unique force-induced native state. We measure through mechanical unfolding that talin R8 domain binds one of its ligands, DLC1, with much higher affinity than previously reported. This strong interaction can explain the antitumor response of DLC1 by regulating inside-out activation of integrins. Together, our results paint a complex picture for the mechanical unfolding of talin in the physiological range and a new mechanism of function of DLC1 to regulate inside-out activation of integrins.

How does RNA fold dynamically?

Recent advances in interrogating RNA folding dynamics have shown the classical model of RNA folding to be incomplete. Here, we pose three prominent questions for the field that are at the forefront of our understanding of the importance of RNA folding dynamics for RNA function. The first centers on the most appropriate biophysical framework to describe changes to the RNA folding energy landscape that a growing RNA chain encounters during transcriptional elongation. The second focuses on the potential ubiquity of strand displacement - a process by which RNA can rapidly change conformations - and how this process may be generally present in broad classes of seemingly different RNAs. The third raises questions about the potential importance and roles of cellular protein factors in RNA conformational switching. Answers to these questions will greatly improve our fundamental knowledge of RNA folding and function, drive biotechnological advances that utilize engineered RNAs, and potentially point to new areas of biology yet to be discovered.

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Background

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.

Results

Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.

Conclusions

Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08635-0).

Folding and Evolution of a Repeat Protein on the Ribosome

Life on earth is the result of the work of proteins, the cellular nanomachines that fold into elaborated 3D structures to perform their functions. The ribosome synthesizes all the proteins of the biosphere, and many of them begin to fold during translation in a process known as cotranslational folding. In this work we discuss current advances of this field and provide computational and experimental data that highlight the role of ribosome in the evolution of protein structures. First, we used the sequence of the Ankyrin domain from the Drosophila Notch receptor to launch a deep sequence-based search. With this strategy, we found a conserved 33-residue motif shared by different protein folds. Then, to see how the vectorial addition of the motif would generate a full structure we measured the folding on the ribosome of the Ankyrin repeat protein. Not only the on-ribosome folding data is in full agreement with classical in vitro biophysical measurements but also it provides experimental evidence on how folded proteins could have evolved by duplication and fusion of smaller fragments in the RNA world. Overall, we discuss how the ribosomal exit tunnel could be conceptualized as an active site that is under evolutionary pressure to influence protein folding.

Ribosome Profiling Reveals Genome-Wide Cellular Translational Regulation in Lacticaseibacillus rhamnosus ATCC 53103 under Acid Stress

During fermentation and food processing, Lacticaseibacillus rhamnosus ATCC 53103 can encounter many adverse conditions, and acid stress is one of them. The purpose of the present study was to investigate the influence of acid stress on the global translational and transcriptional regulation of Lacticaseibacillus rhamnosus ATCC 53103. Two pH values (pH 6.0 vs. pH 5.0) were applied, the effects of which were studied via ribosome profiling and RNA sequencing assay. Under acid stress, many genes showed differential changes at the translational and transcriptional levels. A total of 10 genes showed different expression trends at the two levels. The expression of 337 genes—which mainly participated in the ABC transporters, amino acid metabolism, and ribosome functional group assembly pathways—was shown to be regulated only at the translational level. The translational efficiency of a few genes participating in the pyrimidine and amino acid metabolism pathways were upregulated. Ribosome occupancy data suggested that ribosomes accumulated remarkably in the elongation region of open reading frame regions under acid stress. This study provides new insights into Lacticaseibacillus rhamnosus ATCC 53103 gene expression under acid stress, and demonstrates that the bacterium can respond to acid stress with synergistic translational and transcriptional regulation mechanisms, improving the vitality of cells.

Biosynthetic Protein Folding and Molecular Chaperons

The problem of linear polypeptide chain folding into a unique tertiary structure is one of the fundamental scientific challenges. The process of folding cannot be fully understood without its biological context, especially for big multidomain and multisubunit proteins. The principal features of biosynthetic folding are co-translational folding of growing nascent polypeptide chains and involvement of molecular chaperones in the process. The review summarizes available data on the early events of nascent chain folding, as well as on later advanced steps, including formation of elements of native structure. The relationship between the non-uniformity of translation rate and folding of the growing polypeptide is discussed. The results of studies on the effect of biosynthetic folding features on the parameters of folding as a physical process, its kinetics and mechanisms, are presented. Current understanding and hypotheses on the relationship of biosynthetic folding with the fundamental physical parameters and current views on polypeptide folding in the context of energy landscapes are discussed.

LM-GVP: an extensible sequence and structure informed deep learning framework for protein property prediction

Proteins perform many essential functions in biological systems and can be successfully developed as bio-therapeutics. It is invaluable to be able to predict their properties based on a proposed sequence and structure. In this study, we developed a novel generalizable deep learning framework, LM-GVP, composed of a protein Language Model (LM) and Graph Neural Network (GNN) to leverage information from both 1D amino acid sequences and 3D structures of proteins. Our approach outperformed the state-of-the-art protein LMs on a variety of property prediction tasks including fluorescence, protease stability, and protein functions from Gene Ontology (GO). We also illustrated insights into how a GNN prediction head can inform the fine-tuning of protein LMs to better leverage structural information. We envision that our deep learning framework will be generalizable to many protein property prediction problems to greatly accelerate protein engineering and drug development.

Biomolecular and Biological Applications of Solid-State NMR with Dynamic Nuclear Polarization Enhancement

Solid-state NMR spectroscopy (ssNMR) with magic-angle spinning (MAS) enables the investigation of biological systems within their native context, such as lipid membranes, viral capsid assemblies, and cells. However, such ambitious investigations often suffer from low sensitivity due to the presence of significant amounts of other molecular species, which reduces the effective concentration of the biomolecule or interaction of interest. Certain investigations requiring the detection of very low concentration species remain unfeasible even with increasing experimental time for signal averaging. By applying dynamic nuclear polarization (DNP) to overcome the sensitivity challenge, the experimental time required can be reduced by orders of magnitude, broadening the feasible scope of applications for biological solid-state NMR. In this review, we outline strategies commonly adopted for biological applications of DNP, indicate ongoing challenges, and present a comprehensive overview of biological investigations where MAS-DNP has led to unique insights.

Thermodynamics of co-translational folding and ribosome-nascent chain interactions

Proteins can begin the conformational search for their native structure in parallel with biosynthesis on the ribosome, in a process termed co-translational folding. In contrast to the reversible folding of isolated domains, as a nascent chain emerges from the ribosome exit tunnel during translation the free energy landscape it explores also evolves as a function of chain length. While this presents a substantially more complex measurement problem, this review will outline the progress that has been made recently in understanding, quantitatively, the process by which a nascent chain attains its full native stability, as well as the mechanisms through which interactions with the nearby ribosome surface can perturb or modulate this process.

Protein folding in vitro and in the cell: From a solitary journey to a team effort

Correct protein folding is essential for the health and function of living organisms. Yet, it is not well understood how unfolded proteins reach their native state and avoid aggregation, especially within the cellular milieu. Some proteins, especially small, single-domain and apparent two-state folders, successfully attain their native state upon dilution from denaturant. Yet, many more proteins undergo misfolding and aggregation during this process, in a concentration-dependent fashion. Once formed, native and aggregated states are often kinetically trapped relative to each other. Hence, the early stages of protein life are absolutely critical for proper kinetic channeling to the folded state and for long-term solubility and function. This review summarizes current knowledge on protein folding/aggregation mechanisms in buffered solution and within the bacterial cell, highlighting early stages. Remarkably, teamwork between nascent chain, ribosome, trigger factor and Hsp70 molecular chaperones enables all proteins to overcome aggregation propensities and reach a long-lived bioactive state.

When light meets biology - how the specimen affects quantitative microscopy

Fluorescence microscopy images should not be treated as perfect representations of biology. Many factors within the biospecimen itself can drastically affect quantitative microscopy data. Whereas some sample-specific considerations, such as photobleaching and autofluorescence, are more commonly discussed, a holistic discussion of sample-related issues (which includes less-routine topics such as quenching, scattering and biological anisotropy) is required to appropriately guide life scientists through the subtleties inherent to bioimaging. Here, we consider how the interplay between light and a sample can cause common experimental pitfalls and unanticipated errors when drawing biological conclusions. Although some of these discrepancies can be minimized or controlled for, others require more pragmatic considerations when interpreting image data. Ultimately, the power lies in the hands of the experimenter. The goal of this Review is therefore to survey how biological samples can skew quantification and interpretation of microscopy data. Furthermore, we offer a perspective on how to manage many of these potential pitfalls.

Peptide Model of the Mutant Proinsulin Syndrome. I. Design and Clinical Correlation

The mutant proinsulin syndrome is a monogenic cause of diabetes mellitus due to toxic misfolding of insulin's biosynthetic precursor. Also designated mutant INS-gene induced diabetes of the young (MIDY), this syndrome defines molecular determinants of foldability in the endoplasmic reticulum (ER) of β-cells. Here, we describe a peptide model of a key proinsulin folding intermediate and variants containing representative clinical mutations; the latter perturb invariant core sites in native proinsulin (LeuB15→Pro, LeuA16→Pro, and PheB24→Ser). The studies exploited a 49-residue single-chain synthetic precursor (designated DesDi), previously shown to optimize in vitro efficiency of disulfide pairing. Parent and variant peptides contain a single disulfide bridge (cystine B19-A20) to provide a model of proinsulin's first oxidative folding intermediate. The peptides were characterized by circular dichroism and redox stability in relation to effects of the mutations on (a) in vitro foldability of the corresponding insulin analogs and (b) ER stress induced in cell culture on expression of the corresponding variant proinsulins. Striking correlations were observed between peptide biophysical properties, degree of ER stress and age of diabetes onset (neonatal or adolescent). Our findings suggest that age of onset reflects the extent to which nascent structure is destabilized in proinsulin's putative folding nucleus. We envisage that such peptide models will enable high-resolution structural studies of key folding determinants and in turn permit molecular dissection of phenotype-genotype relationships in this monogenic diabetes syndrome. Our companion study (next article in this issue) employs two-dimensional heteronuclear NMR spectroscopy to define site-specific perturbations in the variant peptides.

Ribosome-nascent chain interaction regulates N-terminal protein modification

Numerous proteins initiate their folding, localization, and modifications early during translation, and emerging data show that the ribosome actively participates in diverse protein biogenesis pathways. Here we show that the ribosome imposes an additional layer of substrate selection during N-terminal methionine excision (NME), an essential protein modification in bacteria. Biochemical analyses show that cotranslational NME is exquisitely sensitive to a hydrophobic signal sequence or transmembrane domain near the N terminus of the nascent polypeptide. The ability of the nascent chain to access the active site of NME enzymes dictates NME efficiency, which is inhibited by confinement of the nascent chain on the ribosome surface and exacerbated by signal recognition particle. In vivo measurements corroborate the inhibition of NME by an N-terminal hydrophobic sequence, suggesting the retention of formylmethionine on a substantial fraction of the secretory and membrane proteome. Our work demonstrates how molecular features of a protein regulate its cotranslational modification and highlights the active participation of the ribosome in protein biogenesis pathways via interactions of the ribosome surface with the nascent protein.

A Ribosomal Perspective on Neuronal Local Protein Synthesis

Continued mRNA translation and protein production are critical for various neuronal functions. In addition to the precise sorting of proteins from cell soma to distant locations, protein synthesis allows a dynamic remodeling of the local proteome in a spatially variable manner. This spatial heterogeneity of protein synthesis is shaped by several factors such as injury, guidance cues, developmental cues, neuromodulators, and synaptic activity. In matured neurons, thousands of synapses are non-uniformly distributed throughout the dendritic arbor. At any given moment, the activity of individual synapses varies over a wide range, giving rise to the variability in protein synthesis. While past studies have primarily focused on the translation factors or the identity of translated mRNAs to explain the source of this variation, the role of ribosomes in this regard continues to remain unclear. Here, we discuss how several stochastic mechanisms modulate ribosomal functions, contributing to the variability in neuronal protein expression. Also, we point out several underexplored factors such as local ion concentration, availability of tRNA or ATP during translation, and molecular composition and organization of a compartment that can influence protein synthesis and its variability in neurons.

A small molecule high throughput screening platform to profile conformational properties of nascent, ribosome-bound proteins

Genetic mutations cause a wide spectrum of human disease by disrupting protein folding, both during and after synthesis. Transient de-novo folding intermediates therefore represent potential drug targets for pharmacological correction of protein folding disorders. Here we develop a FRET-based high-throughput screening (HTS) assay in 1,536-well format capable of identifying small molecules that interact with nascent polypeptides and correct genetic, cotranslational folding defects. Ribosome nascent chain complexes (RNCs) containing donor and acceptor fluorophores were isolated from cell free translation reactions, immobilized on Nickel-NTA/IDA beads, and imaged by high-content microscopy. Quantitative FRET measurements obtained from as little as 0.4 attomole of protein/bead enabled rapid assessment of conformational changes with a high degree of reproducibility. Using this assay, we performed a pilot screen of ~ 50,000 small molecules to identify compounds that interact with RNCs containing the first nucleotide-binding domain (NBD1) of the cystic fibrosis transmembrane conductance regulator (CFTR) harboring a disease-causing mutation (A455E). Screen results yielded 133 primary hits and 1 validated hit that normalized FRET values of the mutant nascent peptide. This system provides a scalable, tractable, structure-based discovery platform for screening small molecules that bind to or impact the folding of protein substrates that are not amenable to traditional biochemical analyses.

Role of cotranslational folding for β-sheet-enriched proteins: A perspective from molecular dynamics simulations

The formations of correct three-dimensional structures of proteins are essential to their functions. Cotranslational folding is vital for proteins to form correct structures in vivo. Although some experiments have shown that cotranslational folding can improve the efficiency of folding, its microscopic mechanism is not yet clear. Previously, we built a model of the ribosomal exit tunnel and investigated the cotranslational folding of a three-helix protein by using all-atom molecular dynamics simulations. Here we study the cotranslational folding of three β-sheet-enriched proteins using the same method. The results show that cotranslational folding can enhance the helical population in most cases and reduce non-native long-range contacts before emerging from the ribosomal exit tunnel. After exiting the tunnel, all proteins fall into local minimal states and the structural ensembles of cotranslational folding show more helical conformations than those of free folding. In particular, for one of the three proteins, the GTT WW domain, we find that one local minimum state of the cotranslational folding is the known folding intermediate, which is not found in free folding. This result suggests that the cotranslational folding may increase the folding efficiency by accelerating the sampling more than by avoiding the misfolded state, which is presently a mainstream viewpoint.

Is Protein Folding a Thermodynamically Unfavorable, Active, Energy-Dependent Process?

The prevailing current view of protein folding is the thermodynamic hypothesis, under which the native folded conformation of a protein corresponds to the global minimum of Gibbs free energy G. We question this concept and show that the empirical evidence behind the thermodynamic hypothesis of folding is far from strong. Furthermore, physical theory-based approaches to the prediction of protein folds and their folding pathways so far have invariably failed except for some very small proteins, despite decades of intensive theory development and the enormous increase of computer power. The recent spectacular successes in protein structure prediction owe to evolutionary modeling of amino acid sequence substitutions enhanced by deep learning methods, but even these breakthroughs provide no information on the protein folding mechanisms and pathways. We discuss an alternative view of protein folding, under which the native state of most proteins does not occupy the global free energy minimum, but rather, a local minimum on a fluctuating free energy landscape. We further argue that ΔG of folding is likely to be positive for the majority of proteins, which therefore fold into their native conformations only through interactions with the energy-dependent molecular machinery of living cells, in particular, the translation system and chaperones. Accordingly, protein folding should be modeled as it occurs in vivo, that is, as a non-equilibrium, active, energy-dependent process.

Cell-Free Synthesis Strategies to Probe Co-translational Folding of Proteins Within Lipid Membranes

In order to comprehend the molecular basis of transmembrane protein biogenesis, methods are required that are capable of investigating the co-translational folding of these hydrophobic proteins. Equally, in artificial cell studies, controllable methods are desirable for in situ synthesis of membrane proteins that then direct reactions in the synthetic cell membrane. Here we describe a method that exploits cell-free expression systems and tunable membrane mimetics to facilitate co-translational studies. Alteration of the lipid bilayer composition improves the efficiency of the folding system. The approach also enables membrane transport proteins to be made and inserted into artificial cell platforms such as droplet interface bilayers. Importantly, this gives a new facet to the droplet networks by enabling specific transport of molecules across the synthetic bilayer against a concentration gradient. This method also includes a protocol to pause and restart translation of membrane proteins at specified positions during their co-translational folding. This stop-start strategy provides an avenue to investigate whether the proteins fold in sequence order, or if the correct fold of N-terminal regions is reliant on the synthesis of downstream residues.

Common sequence motifs of nascent chains engage the ribosome surface and trigger factor

Proteins are produced by ribosomes in the cell, and during this process, can begin to adopt their biologically active forms assisted by molecular chaperones such as trigger factor. This fundamental cellular mechanism is crucial to maintaining a functional proteome and avoiding deleterious misfolding. Here, we study how disordered nascent chains emerge from the ribosome exit tunnel, and find that interactions with the ribosome surface dominate their dynamics in vitro and in vivo. Moreover, we show that the types of amino acids that mediate such interactions are also those that recruit trigger factor. This lays the foundation to describe how nascent chains are handed over from the ribosome surface to chaperones during biosynthesis within the crowded cytosol.

In the cell, the conformations of nascent polypeptide chains during translation are modulated by both the ribosome and its associated molecular chaperone, trigger factor. The specific interactions that underlie these modulations, however, are still not known in detail. Here, we combine protein engineering, in-cell and in vitro NMR spectroscopy, and molecular dynamics simulations to explore how proteins interact with the ribosome during their biosynthesis before folding occurs. Our observations of α-synuclein nascent chains in living Escherichia coli cells reveal that ribosome surface interactions dictate the dynamics of emerging disordered polypeptides in the crowded cytosol. We show that specific basic and aromatic motifs drive such interactions and directly compete with trigger factor binding while biasing the direction of the nascent chain during its exit out of the tunnel. These results reveal a structural basis for the functional role of the ribosome as a scaffold with holdase characteristics and explain how handover of the nascent chain to specific auxiliary proteins occurs among a host of other factors in the cytosol.

Slowest-first protein translation scheme: Structural asymmetry and co-translational folding

Proteins are translated from the N to the C terminus, raising the basic question of how this innate directionality affects their evolution. To explore this question, we analyze 16,200 structures from the Protein Data Bank (PDB). We find remarkable enrichment of α helices at the C terminus and β strands at the N terminus. Furthermore, this α-β asymmetry correlates with sequence length and contact order, both determinants of folding rate, hinting at possible links to co-translational folding (CTF). Hence, we propose the "slowest-first" scheme, whereby protein sequences evolved structural asymmetry to accelerate CTF: the slowest of the cooperatively folding segments are positioned near the N terminus so they have more time to fold during translation. A phenomenological model predicts that CTF can be accelerated by asymmetry in folding rate, up to double the rate, when folding time is commensurate with translation time; analysis of the PDB predicts that structural asymmetry is indeed maximal in this regime. This correspondence is greater in prokaryotes, which generally require faster protein production. Altogether, this indicates that accelerating CTF is a substantial evolutionary force whose interplay with stability and functionality is encoded in secondary structure asymmetry.

Engineering of the Recombinant Expression and PEGylation Efficiency of the Therapeutic Enzyme Human Thymidine Phosphorylase

Human thymidine phosphorylase (HsTP) is an enzyme with important implications in the field of rare metabolic diseases. Defective mutations of HsTP lead to mitochondrial neurogastrointestinal encephalomyopathy (MNGIE), a disease with a high unmet medical need that is associated with severe neurological and gastrointestinal complications. Current efforts focus on the development of an enzyme replacement therapy (ERT) using the Escherichia coli ortholog (EcTP). However, bacterial enzymes are counter-indicated for human therapeutic applications because they are recognized as foreign by the human immune system, thereby eliciting adverse immune responses and raising significant safety and efficacy risks. Thus, it is critical to utilize the HsTP enzyme as starting scaffold for pre-clinical drug development, thus de-risking the safety concerns associated with the use of bacterial enzymes. However, HsTP expresses very poorly in E. coli, whereas its PEGylation, a crucial chemical modification for achieving long serum persistence of therapeutic enzymes, is highly inefficient and negatively affects its catalytic activity. Here we focused on the engineering of the recombinant expression profile of HsTP in E. coli cells, as well as on the optimization of its PEGylation efficiency aiming at the development of an alternative therapeutic approach for MNGIE. We show that phylogenetic and structural analysis of proteins can provide important insights for the rational design of N’-terminus-truncation constructs which exhibit significantly improved recombinant expression levels. In addition, we developed and implemented a criteria-driven rational surface engineering strategy for the substitution of arginine-to-lysine and lysine-to-arginine residues to achieve more efficient, homogeneous and reproducible PEGylation without negatively affecting the enzymatic catalytic activity upon PEGylation. Collectively, our proposed strategies provide an effective way to optimize enzyme PEGylation and E. coli recombinant expression and are likely applicable for other proteins and enzymes.

Interactions of perfluorooctanoic acid with acyl-CoA thioesterase 1 (Acot1)

Perfluorooctanoic acid (PFOA), a typical representative of per- and polyfluoroalkyl substances (PFASs), is a widely utilized persistent organic pollutant (POP) known to induce liver toxicity in laboratory animals and wildlife. Evidence suggests that PFOA interacts with Acyl-CoA thioesterase 1 (Acot1) to modulate levels of β-oxidation. Specifically, PFOA accelerates β-oxidation, while Acot1 is inhibitory. Few studies have investigated the specific relationship between PFOA and Acot1 and the mechanism of their interaction remains unclear. In the following study, purified rat Acot1 protein was synthesized via bacterial recombination and the structural features that facilitate its binding to PFOA were assessed via molecular docking technology. Additionally, through use of circular dichroism spectroscopy (CD) and isothermal titration calorimetry (ITC) we demonstrate that PFOA binds to WT-Acot1 through electrostatic attraction and low strength non-covalent hydrogen bonding at a molar ratio of 1:1. Furthermore, we identify N326 and H373 amino acid residues as key regulators of the binding process. Together, these findings clarify the interaction pattern of PFOA and Acot1 proteins and provide insight into the specific molecular mechanisms that induce PFOA toxicity in humans and animals.

FSATOOL 2.0: An integrated molecular dynamics simulation and trajectory data analysis program

Molecular dynamics simulation is important in the computational study of the biomolecules. In this paper, we upgrade our previous FSATOOL to version 2.0. It is no longer a plugin as before. Besides the existed enhanced sampling and Markov state model analysis module, FSATOOL 2.0 has three new features now. First, it contains a molecular dynamics simulation engine on both CPU and GPU device. The engine works with an embedded enhanced sampling module. Second, it can do the free energy calculation by various practical methods, including the weighted histogram analysis method and Gaussian mixture model. Third, it has many subroutines to process the trajectory data, such as principal component analysis, time-structure based independent component analysis, contact analysis, and Φ-value analysis. Most importantly, all these calculations are integrated into one package. The trajectory data format is compatible with all the modules. With a proper input parameter file, users can do the molecular dynamics simulation and data analysis work by only a few simplified commands. The capabilities and theoretical backgrounds of FSATOOL 2.0 are introduced in the paper.

Nascent chains can form co-translational folding intermediates that promote post-translational folding outcomes in a disease-causing protein

During biosynthesis, proteins can begin folding co-translationally to acquire their biologically-active structures. Folding, however, is an imperfect process and in many cases misfolding results in disease. Less is understood of how misfolding begins during biosynthesis. The human protein, alpha-1-antitrypsin (AAT) folds under kinetic control via a folding intermediate; its pathological variants readily form self-associated polymers at the site of synthesis, leading to alpha-1-antitrypsin deficiency. We observe that AAT nascent polypeptides stall during their biosynthesis, resulting in full-length nascent chains that remain bound to ribosome, forming a persistent ribosome-nascent chain complex (RNC) prior to release. We analyse the structure of these RNCs, which reveals compacted, partially-folded co-translational folding intermediates possessing molten-globule characteristics. We find that the highly-polymerogenic mutant, Z AAT, forms a distinct co-translational folding intermediate relative to wild-type. Its very modest structural differences suggests that the ribosome uniquely tempers the impact of deleterious mutations during nascent chain emergence. Following nascent chain release however, these co-translational folding intermediates guide post-translational folding outcomes thus suggesting that Z's misfolding is initiated from co-translational structure. Our findings demonstrate that co-translational folding intermediates drive how some proteins fold under kinetic control, and may thus also serve as tractable therapeutic targets for human disease.