Contact order revisited: influence of protein size on the folding rate

Enzyme miniaturization: Revolutionizing future biocatalysts

Enzyme miniaturization offers a transformative approach to overcome limitations posed by the large size of conventional enzymes in industrial, therapeutic, and diagnostic applications. However, the evolutionary optimization of enzymes for activity has not inherently favored compact structures, creating challenges for modern applications requiring smaller catalysts. In this review, we surveyed the advantages of miniature enzymes, including enhanced expressivity, folding efficiency, thermostability, and resistance to proteolysis. We described the applications of miniature enzymes as industrial catalysts, therapeutic agents, and diagnostic elements. We highlighted strategies such as genome mining, rational design, random deletion, and de novo design for achieving enzyme miniaturization, integrating both computational and experimental techniques. By investigating these approaches, we aim to provide a framework for advancing enzyme engineering, emphasizing the unique potential of miniature enzymes to revolutionize biocatalysis, gene therapy, and biosensing technologies.

Studying the Protein Thermostabilities and Folding Rates by the Interaction Energy Network in Solvent

Residue interaction networks determine various characteristics of proteins, such as the folding rate, thermostability, and allosteric process. The interactions between residues can be described by distances or energies. The former is simple but less rigorous. The latter is complicated but more precise, especially when considering the solvent effect. In this work, we apply an existing energy decomposition method based on the Poisson-Boltzmann equation solver. The calculation is especially accelerated on GPU for higher performance. In four formal applications, the constructed interaction energy (IE) network shows good results. First, it is found that the protein folding rate has a stronger correlation with the energy-based contact order than the distance-based contact order. The Pearson correlation coefficient (PCC) is 0.839 versus 0.784 on a dataset of non-two-state proteins. Second, we find that most thermophilic proteins have lower IEs than mesophilic proteins. The IE in solvent acts as an indicator to evaluate the thermostabilities of proteins. Third, we use the IE network to predict the key residues in the formation of the insulin dimer. Most key residues are in agreement with the findings in previous alanine-scanning experiments. Lastly, we propose a novel method (called APFN) to predict the allosteric pathway based on the IE network. The method gives the same allosteric pathway for CheY protein as in previous nuclear magnetic resonance spectroscopy experiments. On the whole, the IE network in the solvent has been demonstrated to be reliable in describing the characteristics embedded in protein structures.

Solvation enhances folding cooperativity and the topology dependence of folding rates in a lattice protein model

The aqueous solvent profoundly influences protein folding, yet its effects are relatively poorly understood. In this study, we investigate the impact of solvation on the folding of lattice proteins by using Monte Carlo simulations. The proteins are modeled as self-avoiding 27-mer chains on a cubic lattice, with compact native states and structure-based Gō potentials. Each residue that makes no contact with other residues in a given protein conformation is assigned a solvation energy ɛs, representing its full exposure to the solvent. We find that a negative ɛs, indicating a favorable solvation, increases the cooperativity of the folding transition by lowering the free energy of the unfolded state, increasing the folding free energy barrier, and narrowing the folding routes. This favorable solvation also significantly improves the correlation between folding rates and the native topology, measured by the relative contact order. Our results suggest that the Gō model may overestimate the importance of native interactions, and a solvation potential countering the native bias can play a significant role. The solvation energy in our model can be related to the polar interaction between water and peptide groups in the protein backbone. It is, therefore, suggested that the solvation of peptide groups may significantly contribute to the exceptional folding cooperativity and the pronounced topology-dependence of folding rates observed in two-state proteins.

On the free energy of protein folding in optical tweezers experiments

Free energy is a critical parameter in understanding the equilibrium in chemical reactions. It enables us to determine the equilibrium proportion between the different species in the reaction and to predict in which direction the reaction will proceed if a change is performed in the system. Historically, to calculate this value, bulk experiments were performed where a parameter was altered at a gradual rate to change the population until a new equilibrium was established. In protein folding studies, it is common to vary the temperature or chaotropic agents in order to change the population and then to extrapolate to physiological conditions. Such experiments were time-consuming due to the necessity of ensuring equilibrium and reversibility. Techniques of single-molecule manipulation, such as optical/magnetic tweezers and atomic force microscopy, permit the direct measurement of the work performed by a protein undergoing unfolding/refolding at particular forces. Also, with the development of non-equilibrium free energy theorems (Jarzynski equality, Crooks fluctuation theorem, Bennett acceptance ratio, and overlapping method), it is possible to obtain free energy values in experiments far from equilibrium. This review compares different methodologies and their application in optical tweezers. Interestingly, in many proteins, discrepancies in free energy values obtained through different methods suggest additional complexities in the folding pathway, possibly involving intermediate states such as the molten globule. Further studies are needed to confirm their presence and significance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-025-01310-0.

Importance of Inter-residue Contacts for Understanding Protein Folding and Unfolding Rates, Remote Homology, and Drug Design

Inter-residue interactions in protein structures provide valuable insights into protein folding and stability. Understanding these interactions can be helpful in many crucial applications, including rational design of therapeutic small molecules and biologics, locating functional protein sites, and predicting protein-protein and protein-ligand interactions. The process of developing machine learning models incorporating inter-residue interactions has been improved recently. This review highlights the theoretical models incorporating inter-residue interactions in predicting folding and unfolding rates of proteins. Utilizing contact maps to depict inter-residue interactions aids researchers in developing computer models for detecting remote homologs and interface residues within protein-protein complexes which, in turn, enhances our knowledge of the relationship between sequence and structure of proteins. Further, the application of contact maps derived from inter-residue interactions is highlighted in the field of drug discovery. Overall, this review presents an extensive assessment of the significant models that use inter-residue interactions to investigate folding rates, unfolding rates, remote homology, and drug development, providing potential future advancements in constructing efficient computational models in structural biology.

How proteins manage to fold and how chaperones manage to assist the folding

This review presents the current understanding of (i) spontaneous self-organization of spatial structures of protein molecules, and (ii) possible ways of chaperones' assistance to this process. Specifically, we overview the most important features of spontaneous folding of proteins (mostly, of the single-domain water-soluble globular proteins): the choice of the unique protein structure among zillions of alternatives, the nucleation of the folding process, and phase transitions within protein molecules. We consider the main experimental facts on protein folding, both in vivo and in vitro, of both kinetic and thermodynamic nature. We discuss the famous Levinthal's paradox of protein folding and its solution, theoretical models of protein folding and unfolding, and the dependence of the rates of these processes on the protein chain length. Special attention is paid to relatively small, single-domain, and water-soluble globular proteins whose structure and folding are much better studied and understood than those of large proteins, especially membrane or fibrous proteins. Lastly, we describe the chaperone-assisted protein folding with an emphasis on the chaperones' ability to prevent proteins from their irreversible aggregation. Since the possible assistance mechanisms connected with chaperones are still debatable, experimental data useful in selecting the most likely mechanisms of chaperone-assisted protein folding are presented.

Co-translational protein aggregation and ribosome stalling as a broad-spectrum antibacterial mechanism

Drug-resistant bacteria pose an urgent global health threat, necessitating the development of antibacterial compounds with novel modes of action. Protein biosynthesis accounts for up to half of the energy expenditure of bacterial cells, and consequently inhibiting the efficiency or fidelity of the bacterial ribosome is a major target of existing antibiotics. Here, we describe an alternative mode of action that affects the same process: allowing translation to proceed but causing co-translational aggregation of the nascent peptidic chain. We show that treatment with an aggregation-prone peptide induces formation of polar inclusion bodies and activates the SsrA ribosome rescue pathway in bacteria. The inclusion bodies contain ribosomal proteins and ribosome hibernation factors, as well as mRNAs and cognate nascent chains of many proteins in amyloid-like structures, with a bias for membrane proteins with a fold rich in long-range beta-sheet interactions. The peptide is bactericidal against a wide range of pathogenic bacteria in planktonic growth and in biofilms, and reduces bacterial loads in mouse models of Escherichia coli and Acinetobacter baumannii infections. Our results indicate that disrupting protein homeostasis via co-translational aggregation constitutes a promising strategy for development of broad-spectrum antibacterials.

Structural determinants of co-translational protein complex assembly

Protein assembly into functional complexes is critical to life's processes. While complex assembly is classically described as occurring between fully synthesized proteins, recent work showed that co-translational assembly is prevalent in human cells. However, the biological basis for the existence of this process and the identity of protein pairs that assemble co-translationally remain unknown. We show that co-translational assembly is governed by structural characteristics of complexes and involves mutually stabilized subunits. Accordingly, co-translationally assembling subunits are unstable in isolation and exhibit synchronized proteostasis with their partner. By leveraging structural signatures and AlphaFold2-based predictions, we accurately predicted co-translational assembly, including pair identities, at proteome scale and across species. We validated our predictions by ribosome profiling, stoichiometry perturbations, and single-molecule RNA-fluorescence in situ hybridization (smFISH) experiments that revealed co-localized mRNAs. This work establishes a fundamental connection between protein structure and the translation process, highlighting the overarching impact of three-dimensional structure on gene expression, mRNA localization, and proteostasis.

Folds from fold: Exploring topological isoforms of a single-domain protein

Expanding the protein fold space beyond linear chains is of fundamental significance, yet remains largely unexplored. Herein, we report the creation of seven topological isoforms (i.e., linear, cyclic, knot, lasso, pseudorotaxane, and catenane) from a single protein fold precursor by rewiring the connectivity of secondary structure elements of the SpyTag-SpyCatcher complex and mutating the reactive residue on SpyTag to abolish the isopeptide bonding. These topological isoforms can be directly expressed in cells. Their topologies were confirmed by combined techniques of proteolytic digestion, fluorescence correlation spectroscopy (FCS), size-exclusion chromatography (SEC), and topological transformation. To study the effects of topology on their structures and properties, their biophysical properties were characterized by differential scanning calorimetry (DSC), heteronuclear single quantum coherence nuclear magnetic resonance spectroscopy (HSQC-NMR), and circular dichroism (CD) spectroscopy. Molecular dynamics (MD) simulations were further performed to reveal the atomic details of structural changes upon unfolding. Both experimental and simulation results suggest that they share a similar, well-folded hydrophobic core but exhibit distinct folding/unfolding dynamic behaviors. These results shed light onto the folding landscape of topological isoforms derived from the same protein fold. As a model system, this work improves our understanding of protein structure and dynamics beyond linear chains and suggests that protein folds are highly amenable to topological variation.

On the role of native contact cooperativity in protein folding

The consistency of energy landscape theory predictions with available experimental data, as well as direct evidence from molecular simulations, have shown that protein folding mechanisms are largely determined by the contacts present in the native structure. As expected, native contacts are generally energetically favorable. However, there are usually at least as many energetically favorable nonnative pairs owing to the greater number of possible nonnative interactions. This apparent frustration must therefore be reduced by the greater cooperativity of native interactions. In this work, we analyze the statistics of contacts in the unbiased all-atom folding trajectories obtained by Shaw and coworkers, focusing on the unfolded state. By computing mutual cooperativities between contacts formed in the unfolded state, we show that native contacts form the most cooperative pairs, while cooperativities among nonnative or between native and nonnative contacts are typically much less favorable or even anticooperative. Furthermore, we show that the largest network of cooperative interactions observed in the unfolded state consists mainly of native contacts, suggesting that this set of mutually reinforcing interactions has evolved to stabilize the native state.

Biophysical characterization of the CXC chemokine receptor 2 ligands

The chemokines of the immune system act as first responders by operating as chemoattractants, directing immune cells to specific locations of inflamed tissues. This promiscuous network is comprised of 50 ligands and 18 receptors where the ligands may interact with the receptors in various oligomeric states i.e., monomers, homodimers, and heterodimers. Chemokine receptors are G-protein coupled receptors (GPCRs) present in the membrane of immune cells. The migration of immune cells occurs in response to a concentration gradient of the ligands. Chemotaxis of neutrophils is directed by CXC-ligand (CXCL) activation of the membrane bound CXC chemokine receptor 2 (CXCR2). CXCR2 plays an important role in human health and is linked to disorders such as autoimmune disorders, inflammation, and cancer. Yet, despite their important role, little is known about the biophysical characteristics controlling ligand:ligand and ligand:receptor interaction essential for biological activity. In this work, we study the homodimers of three of the CXCR2 cognate ligands, CXCL1, CXCL5, and CXCL8. The ligands share high structural integrity but a low sequence identity. We show that the sequence diversity has evolved different binding affinities and stabilities for the CXC-ligands resulting in diverse agonist/antagonist behavior. Furthermore, CXC-ligands fold through a three-state mechanism, populating a folded monomeric state before associating into an active dimer.

The dynamic-process characterization and prediction of synthetic gene circuits by dynamic delay model

Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.

VeloPro: A pipeline integrating Ribo-seq and AlphaFold deciphers association patterns between translation velocity and protein structure features

VeloPro integrates Ribo-seq data and AlphaFold2-predicted 3D protein structure information for characterization of the association patterns between translation velocity and many protein structure features in prokaryotic and eukaryotic organisms across different taxonomical clades such as bacteria, fungi, protozoa, nematode, plants, insect, and mammals. We illustrated that association patterns between translation velocity and protein structure features differ across organisms, partially reflecting their taxonomical relationship.

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.

Unveiling Metastable Ensembles of GRB2 and the Relevance of Interdomain Communication during Folding

The folding process of multidomain proteins is a highly intricate phenomenon involving the assembly of distinct domains into a functional three-dimensional structure. During this process, each domain may fold independently while interacting with others. The folding of multidomain proteins can be influenced by various factors, including their composition, the structure of each domain, or the presence of disordered regions, as well as the surrounding environment. Misfolding of multidomain proteins can lead to the formation of nonfunctional structures associated with a range of diseases, including cancers or neurodegenerative disorders. Understanding this process is an important step for many biophysical analyses such as stability, interaction, malfunctioning, and rational drug design. One such multidomain protein is growth factor receptor-bound protein 2 (GRB2), an adaptor protein that is essential in regulating cell survival. GRB2 consists of one central Src homology 2 (SH2) domain flanked by two Src homology 3 (SH3) domains. The SH2 domain interacts with phosphotyrosine regions in other proteins, while the SH3 domains recognize proline-rich regions on protein partners during cell signaling. Here, we combined computational and experimental techniques to investigate the folding process of GRB2. Through computational simulations, we sampled the conformational space and mapped the mechanisms involved by the free energy profiles, which may indicate possible intermediate states. From the molecular dynamics trajectories, we used the energy landscape visualization method (ELViM), which allowed us to visualize a three-dimensional (3D) representation of the overall energy surface. We identified two possible parallel folding routes that cannot be seen in a one-dimensional analysis, with one occurring more frequently during folding. Supporting these results, we used differential scanning calorimetry (DSC) and fluorescence spectroscopy techniques to confirm these intermediate states in vitro. Finally, we analyzed the deletion of domains to compare our model outputs to previously published results, supporting the presence of interdomain modulation. Overall, our study highlights the significance of interdomain communication within the GRB2 protein and its impact on the formation, stability, and structural plasticity of the protein, which are crucial for its interaction with other proteins in key signaling pathways.

Appraisal of blob-Based Approaches in the Prediction of Protein Folding Times

A series of reports published in the last 3 years has illustrated that a blob-based model (BBM) can predict the folding time of proteins from their primary amino acid (aa) sequence based on three simple rules established to characterize the long-range backbone dynamics (LRBD) of racemic polypeptides. The sole use of LRBD to predict protein folding times with the BBM represents a radical departure from all other prediction methods currently applied to determine protein folding times, which rely instead on parameters such as the structure content, folding kinetics, chain length, amino acid properties, or contact topography of proteins. Furthermore, the built-in modularity of the BBM enables the parametrization and inclusion of new phenomena affecting the LRBD of polypeptides, while its conceptual simplicity makes it an interesting new mathematical tool for studying protein folding. However, its novelty implies that its relationship with many other methods used to predict protein folding times has not been well researched. Consequently, the purpose of this report is to uncover the physical phenomena encountered during protein folding that are best described by the BBM through the identification of parameters that have been recognized over the years as being strong predictors for protein folding, such as protein size, topology, structural class, and folding kinetics. This was accomplished by determining the parameters most strongly correlated with the folding times predicted by the BBM. While the BBM in its present form appears to be a good indicator of the folding times of the vast majority of the 195 proteins considered so far, this report finds that it excels for moderately large proteins that are primarily composed of locally formed structural motifs such as α-helices or for proteins that fold in multiple steps. Altogether, these observations based on the use of the BBM support the notion that proteins fold the way they do because the LRBD of polypeptides is mostly driven by the local interactions experienced between aa's within reach of one another.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

FungiProteomeDB: a database for the molecular weight and isoelectric points of the fungal proteomes

Proteins' molecular weight (MW) and isoelectric point (pI) are crucial for their subcellular localization and subsequent function. These are also useful in 2D gel electrophoresis, liquid chromatography-mass spectrometry and X-ray protein crystallography. Moreover, visualizations like a virtual 2D proteome map of pI vs. MW are worthwhile to discuss the proteome diversity among different species. Although the genome sequence data of the fungi kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the MW and pI of the fungi proteins and reported them in, FungiProteomeDB, an online database (DB) https://vision4research.com/fungidb/. We analyzed the proteome of 685 fungal species that contain 7 127 141 protein sequences. The DB provides an easy-to-use and efficient interface for various search options, summary statistics and virtual 2D proteome map visualizations. The MW and pI of a protein can be obtained by searching the name of a protein, a keyword or a list of accession numbers. It also allows querying protein sequences. The DB will be helpful in hypothesis formulation and in various biotechnological applications. Database URL https://vision4research.com/fungidb/.

Computational prediction of protein folding rate using structural parameters and network centrality measures

Protein folding is a complex physicochemical process whereby a polymer of amino acids samples numerous conformations in its unfolded state before settling on an essentially unique native three-dimensional (3D) structure. To understand this process, several theoretical studies have used a set of 3D structures, identified different structural parameters, and analyzed their relationships using the natural logarithmic protein folding rate (ln(k_f)). Unfortunately, these structural parameters are specific to a small set of proteins that are not capable of accurately predicting ln(k_f) for both two-state (TS) and non-two-state (NTS) proteins. To overcome the limitations of the statistical approach, a few machine learning (ML)-based models have been proposed using limited training data. However, none of these methods can explain plausible folding mechanisms. In this study, we evaluated the predictive capabilities of ten different ML algorithms using eight different structural parameters and five different network centrality measures based on newly constructed datasets. In comparison to the other nine regressors, support vector machine was found to be the most appropriate for predicting ln(k_f) with mean absolute differences of 1.856, 1.55, and 1.745 for the TS, NTS, and combined datasets, respectively. Furthermore, combining structural parameters and network centrality measures improves the prediction performance compared to individual parameters, indicating that multiple factors are involved in the folding process.

Charge reversal mutations in mesophilic-thermophilic orthologous protein pairs and their role in enhancing coulombic interaction energy

Proteins from thermophilic organisms are a matter of immense interest for decades because of its application in fields like de-novo protein design, thermostable variants of biocatalysts etc. Previous studies have found several sequence and structural adaptations related to thermal stability, while charge reversal study remains ignored. Here we address whether charge reversal mutations naturally occur in mesophilic-thermophilic/hyperthermophilic orthologous proteins. Do they contribute to thermal stability? Our systematic study on 1550 mesophilic-thermophilic/hyperthermophilic orthologous protein pairs with remarkable structural and topological similarity, shows gain in coulombic interaction energy in thermophilic/hyperthermophilic proteins at short range associated with partially exposed and buried charge reversal mutations, which may enhance thermostability. Our findings call forth its application in future protein engineering studies. Communicated by Ramaswamy H. Sarma.

Synergetic Effects of Alanine and Glycine in Blob-Based Methods for Predicting Protein Folding Times

The polypeptide PGlyAlaGlu was prepared with 20 mol % glycine (Gly), 36 mol % d,l-alanine (Ala), and 44 mol % d,l-glutamic acid (Glu) and labeled with the dye 1-pyrenemethylamine to yield a series of Py-PGlyAlaGlu samples. The fluorescence decays of the Py-PGlyAlaGlu samples were analyzed according to the fluorescence blob model (FBM) to obtain the number N_blob^exp of amino acids (aa's) encompassed inside the subvolume V_blob of the polypeptide probed by an excited pyrene. An N_blob^exp value of 29 (±2) was retrieved for Py-PGlyAlaGlu, which was much larger than for any of the copolypeptide PGlyGlu or PAlaGlu prepared with either Gly and Glu or Ala and Glu, respectively. The continuous increase in N_blob^exp with decreasing side chain size (SCS) from 10 aa's for PGlu to 16 aa's for PAlaGlu and 22 aa's for PGlyGlu was used earlier to define the reach of an aa and determine the groups of aa's that could interact with each other along a polypeptide backbone according to their SCS. These groups of aa's, referred to as blobs, led to the implementation of blob-based models (BBM) to predict the folding time τ_F^theo,BBM of 145 proteins, which was found to match their experimental folding time τ_F^exp with a relatively high 0.71 correlation coefficient. Nevertheless, the much higher N_blob^exp value found for Py-PGlyAlaGlu compared to all other pyrene-labeled polypeptides studied to date indicates that the reach of aa's along a polypeptide sequence is affected not only by SCS but also by synergetic effects between different aa's. Following this new insight, a revised BBM was implemented to predict τ_F^theo,BBM for 195 proteins assuming the existence or absence of synergies to control the interactions between aa's along a polypeptide sequence. Similarly good correlation coefficients of 0.71 and 0.74 were obtained for a direct 1:1 comparison of τ_F^exp and τ_F^theo,BBM for the 195 proteins without and with synergies, respectively. This result suggests that synergetic effects between different aa's have little effect on τ_F^theo,BBM predicted from BBM underlying the robustness of this methodology.

Engineering the kinetic stability of a β-trefoil protein by tuning its topological complexity

Kinetic stability, defined as the rate of protein unfolding, is central to determining the functional lifetime of proteins, both in nature and in wide-ranging medical and biotechnological applications. Further, high kinetic stability is generally correlated with high resistance against chemical and thermal denaturation, as well as proteolytic degradation. Despite its significance, specific mechanisms governing kinetic stability remain largely unknown, and few studies address the rational design of kinetic stability. Here, we describe a method for designing protein kinetic stability that uses protein long-range order, absolute contact order, and simulated free energy barriers of unfolding to quantitatively analyze and predict unfolding kinetics. We analyze two β-trefoil proteins: hisactophilin, a quasi-three-fold symmetric natural protein with moderate stability, and ThreeFoil, a designed three-fold symmetric protein with extremely high kinetic stability. The quantitative analysis identifies marked differences in long-range interactions across the protein hydrophobic cores that partially account for the differences in kinetic stability. Swapping the core interactions of ThreeFoil into hisactophilin increases kinetic stability with close agreement between predicted and experimentally measured unfolding rates. These results demonstrate the predictive power of readily applied measures of protein topology for altering kinetic stability and recommend core engineering as a tractable target for rationally designing kinetic stability that may be widely applicable.

Potential Self-Peptide Inhibitors of the SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro) plays an essential role in viral replication, cleaving viral polyproteins into functional proteins. This makes Mpro an important drug target. Mpro consists of an N-terminal catalytic domain and a C-terminal α-helical domain (MproC). Previous studies have shown that peptides derived from a given protein sequence (self-peptides) can affect the folding and, in turn, the function of that protein. Since the SARS-CoV-1 MproC is known to stabilize its Mpro and regulate its function, we hypothesized that SARS-CoV-2 MproC-derived self-peptides may modulate the folding and the function of SARS-CoV-2 Mpro. To test this, we studied the folding of MproC in the presence of various self-peptides using coarse-grained structure-based models and molecular dynamics simulations. In these simulations of MproC and one self-peptide, we found that two self-peptides, the α1-helix and the loop between α4 and α5 (loop4), could replace the equivalent native sequences in the MproC structure. Replacement of either sequence in full-length Mpro should, in principle, be able to perturb Mpro function albeit through different mechanisms. Some general principles for the rational design of self-peptide inhibitors emerge: The simulations show that prefolded self-peptides are more likely to replace native sequences than those which do not possess structure. Additionally, the α1-helix self-peptide is kinetically stable and once inserted rarely exchanges with the native α1-helix, while the loop4 self-peptide is easily replaced by the native loop4, making it less useful for modulating function. In summary, a prefolded α1-derived peptide should be able to inhibit SARS-CoV-2 Mpro function.

Protein folding problem: enigma, paradox, solution

The ability of protein chains to spontaneously form their three-dimensional structures is a long-standing mystery in molecular biology. The most conceptual aspect of this mystery is how the protein chain can find its native, "working" spatial structure (which, for not too big protein chains, corresponds to the global free energy minimum) in a biologically reasonable time, without exhaustive enumeration of all possible conformations, which would take billions of years. This is the so-called "Levinthal's paradox." In this review, we discuss the key ideas and discoveries leading to the current understanding of protein folding kinetics, including folding landscapes and funnels, free energy barriers at the folding/unfolding pathways, and the solution of Levinthal's paradox. A special role here is played by the "all-or-none" phase transition occurring at protein folding and unfolding and by the point of thermodynamic (and kinetic) equilibrium between the "native" and the "unfolded" phases of the protein chain (where the theory obtains the simplest form). The modern theory provides an understanding of key features of protein folding and, in good agreement with experiments, it (i) outlines the chain length-dependent range of protein folding times, (ii) predicts the observed maximal size of "foldable" proteins and domains. Besides, it predicts the maximal size of proteins and domains that fold under solely thermodynamic (rather than kinetic) control. Complementarily, a theoretical analysis of the number of possible protein folding patterns, performed at the level of formation and assembly of secondary structures, correctly outlines the upper limit of protein folding times.

Effects of Residual Composition and Distribution on the Structural Characteristics of the Protein

The effect of ratio and consecutive number of hydrophobic residues in the repeating unit of protein chains was investigated by MD simulation. The modified off-lattice HNP model was applied in this study. The protein chains constituted by different HNP ratios or different numbers of consecutively hydrophobic residues with the same chain length were simulated under a broad temperature range. We concluded that the proteins with higher ratio or larger number of sequentially hydrophobic residues present more orientated and compact structure under a certain low temperature. It is attributed to the lower non-bonded potential energy between H-H residual pairs, especially more hydrophobic residues in a procession among the protein chain. Considering the microscopic structure of the protein, more residue contacts are achieved with the proteins with higher ratios and sequential H residues under the low temperature. Meanwhile, with the ratio and consecutive number of H residues increasing, the distribution of stem length showed a transition from exponential decline to unimodal and even multiple peaks, indicating the specific ordered structure formed. These results provide an insight into 3D structural properties of proteins from their residue sequences, which has a primary structure at molecular level and, ultimately, a practical possibility of applying in biotechnological applications.

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.

The Molten Globule State of a Globular Protein in a Cell Is More or Less Frequent Case Rather than an Exception

Quite a long time ago, Oleg B. Ptitsyn put forward a hypothesis about the possible functional significance of the molten globule (MG) state for the functioning of proteins. MG is an intermediate between the unfolded and the native state of a protein. Its experimental detection and investigation in a cell are extremely difficult. In the last decades, intensive studies have demonstrated that the MG-like state of some globular proteins arises from either their modifications or interactions with protein partners or other cell components. This review summarizes such reports. In many cases, MG was evidenced to be functionally important. Thus, the MG state is quite common for functional cellular proteins. This supports Ptitsyn’s hypothesis that some globular proteins may switch between two active states, rigid (N) and soft (MG), to work in solution or interact with partners.

Ribosome profiling reveals multiple roles of SecA in cotranslational protein export

SecA, an ATPase known to posttranslationally translocate secretory proteins across the bacterial plasma membrane, also binds ribosomes, but the role of SecA’s ribosome interaction has been unclear. Here, we used a combination of ribosome profiling methods to investigate the cotranslational actions of SecA. Our data reveal the widespread accumulation of large periplasmic loops of inner membrane proteins in the cytoplasm during their cotranslational translocation, which are specifically recognized and resolved by SecA in coordination with the proton motive force (PMF). Furthermore, SecA associates with 25% of secretory proteins with highly hydrophobic signal sequences at an early stage of translation and mediates their cotranslational transport. In contrast, the chaperone trigger factor (TF) delays SecA engagement on secretory proteins with weakly hydrophobic signal sequences, thus enforcing a posttranslational mode of their translocation. Our results elucidate the principles of SecA-driven cotranslational protein translocation and reveal a hierarchical network of protein export pathways in bacteria.

Using a combination of ribosome profiling methods, Zhu et al. investigate the principles governing the cotranslational interaction of SecA with nascent proteins and reveal a hierarchical organization of protein export pathways in bacteria.

A topological refactoring design strategy yields highly stable granulopoietic proteins

Protein therapeutics frequently face major challenges, including complicated production, instability, poor solubility, and aggregation. De novo protein design can readily address these challenges. Here, we demonstrate the utility of a topological refactoring strategy to design novel granulopoietic proteins starting from the granulocyte-colony stimulating factor (G-CSF) structure. We change a protein fold by rearranging the sequence and optimising it towards the new fold. Testing four designs, we obtain two that possess nanomolar activity, the most active of which is highly thermostable and protease-resistant, and matches its designed structure to atomic accuracy. While the designs possess starkly different sequence and structure from the native G-CSF, they show specific activity in differentiating primary human haematopoietic stem cells into mature neutrophils. The designs also show significant and specific activity in vivo. Our topological refactoring approach is largely independent of sequence or structural context, and is therefore applicable to a wide range of protein targets.

Skokowa et al. reconstruct the fold of a granulopoietic cytokine, resulting in de novo, hyperstable, highly active proteins with therapeutic potential for treating several neutropenia disorders.

Combining High-Pressure NMR and Geometrical Sampling to Obtain a Full Topological Description of Protein Folding Landscapes: Application to the Folding of Two MAX Effectors from Magnaporthe oryzae

Despite advances in experimental and computational methods, the mechanisms by which an unstructured polypeptide chain regains its unique three-dimensional structure remains one of the main puzzling questions in biology. Single-molecule techniques, ultra-fast perturbation and detection approaches and improvement in all-atom and coarse-grained simulation methods have greatly deepened our understanding of protein folding and the effects of environmental factors on folding landscape. However, a major challenge remains the detailed characterization of the protein folding landscape. Here, we used high hydrostatic pressure 2D NMR spectroscopy to obtain high-resolution experimental structural information in a site-specific manner across the polypeptide sequence and along the folding reaction coordinate. We used this residue-specific information to constrain Cyana3 calculations, in order to obtain a topological description of the entire folding landscape. This approach was used to describe the conformers populating the folding landscape of two small globular proteins, AVR-Pia and AVR-Pib, that belong to the structurally conserved but sequence-unrelated MAX effectors superfamily. Comparing the two folding landscapes, we found that, in spite of their divergent sequences, the folding pathway of these two proteins involves a similar, inescapable, folding intermediate, even if, statistically, the routes used are different.

PlantMWpIDB: a database for the molecular weight and isoelectric points of the plant proteomes

The molecular weight and isoelectric point of the proteins are very important parameters that control their subcellular localization and subsequent function. Although the genome sequence data of the plant kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the molecular weight and isoelectric point of the plant proteins and reported them in this database. A database, PlantMWpIDB, containing protein data from 342 plant proteomes was created to provide information on plant proteomes for hypothesis formulation in basic research and for biotechnological applications. The Molecular weight and isoelectric point (pI) are important molecular parameters of proteins that are useful when conducting protein studies involving 2D gel electrophoresis, liquid chromatography-mass spectrometry, and X-ray protein crystallography. PlantMWpIDB provides an easy-to-use and efficient interface for search options and generates a summary of basic protein parameters. The database represents a virtual 2D proteome map of plants, and the molecular weight and pI of a protein can be obtained by searching on the name of a protein, a keyword, or by a list of accession numbers. The PlantMWpIDB database also allows one to query protein sequences. The database can be found in the following link https://plantmwpidb.com/ . The individual 2D virtual proteome map of the plant kingdom will enable us to understand the proteome diversity between different species. Further, the molecular weight and isoelectric point of individual proteins can enable us to understand their functional significance in different species.

Residual Structure in the Denatured State of the Fast-Folding UBA(1) Domain from the Human DNA Excision Repair Protein HHR23A

The structure of the first ubiquitin-associated domain from HHR23A, UBA(1), was determined by X-ray crystallography at a 1.60 Å resolution, and its stability, folding kinetics, and residual structure under denaturing conditions have been investigated. The concentration dependence of thermal denaturation and size-exclusion chromatography indicate that UBA(1) is monomeric. Guanidine hydrochloride (GdnHCl) denaturation experiments reveal that the unfolding free energy, ΔGu°'(H2O), of UBA(1) is 2.4 kcal mol-1. Stopped-flow folding kinetics indicates sub-millisecond folding with only proline isomerization phases detectable at 25 °C. The full folding kinetics are observable at 4 °C, yielding a folding rate constant, kf, in the absence of a denaturant of 13,000 s-1 and a Tanford β-value of 0.80, consistent with a compact transition state. Evaluation of the secondary structure via circular dichroism shows that the residual helical structure in the denatured state is replaced by polyproline II structure as the GdnHCl concentration increases. Analysis of NMR secondary chemical shifts for backbone 15NH, 13CO, and 13Cα atoms between 4 and 7 M GdnHCl shows three islands of residual helical secondary structure that align in sequence with the three native-state helices. Extrapolation of the NMR data to 0 M GdnHCl demonstrates that helical structure would populate to 17-33% in the denatured state under folding conditions. Comparison with NMR data for a peptide corresponding to helix 1 indicates that this helix is stabilized by transient tertiary interactions in the denatured state of UBA(1). The high helical content in the denatured state, which is enhanced by transient tertiary interactions, suggests a diffusion-collision folding mechanism.

De novo protein folding on computers. Benefits and challenges

There has been recent success in prediction of the three-dimensional folded native structures of proteins, most famously by the AlphaFold Algorithm running on Google's/Alphabet's DeepMind computer. However, this largely involves machine learning of protein structures and is not a de novo protein structure prediction method for predicting three-dimensional structures from amino acid residue sequences. A de novo approach would be based almost entirely on general principles of energy and entropy that govern protein folding energetics, and importantly do so without the use of the amino acid sequences and structural features of other proteins. Most consider that problem as still unsolved even though it has occupied leading scientists for decades. Many consider that it remains one of the major outstanding issues in modern science. There is crucial continuing help from experimental findings on protein unfolding and refolding in the laboratory, but only to a limited extent because many researchers consider that the speed by which real proteins folds themselves, often from milliseconds to minutes, is itself still not fully understood. This is unfortunate, because a practical solution to the problem would probably have a major effect on personalized medicine, the pharmaceutical industry, biotechnology, and nanotechnology, including for example "smaller" tasks such as better modeling of flexible "unfolded" regions of the SARS-COV-2 spike glycoprotein when interacting with its cell receptor, antibodies, and therapeutic agents. Some important ideas from earlier studies are given before moving on to lessons from periodic and aperiodic crystals, and a possible role for quantum phenomena. The conclusion is that better computation of entropy should be the priority, though that is presented guardedly.

Pyrene Excimer Formation (PEF) and Its Application to the Study of Polypeptide Dynamics

This Perspective describes how the fluorescence blob model (FBM) has been developed and applied over the past 30 years to characterize the long-range backbone dynamics (LRBD) of polymers in solution. In these experiments, the polymers are randomly labeled with the dye pyrene, which forms an excimer upon the encounter between an excited and a ground-state pyrenyl label inside a finite subvolume of the polymer coil referred to as a blob representing the volume probed by the excited pyrene. By compartmentalizing the polymer coil into a cluster of identical blobs, FBM analysis of the fluorescence decays acquired with the polymers yields the number N_blob of structural units inside a blob. Since a flexible or rigid backbone will result in an N_blob that is either large or small, N_blob can be used as a measure of the flexibility of a given polymer. After having established that these experiments based on pyrene excimer formation (PEF) yielded quantitative information about the LRBD of a variety of polymers in solution, control experiments were carried out to characterize the effects that different molecular variables, such as the side-chain size (SCS) of a structural unit or the length of the linker connecting pyrene to the polymeric backbone, had on the parameters retrieved with the FBM. At this point, the FBM was applied to study the LRBD of polypeptides prepared from racemic mixtures of amino acids (aa's). These studies led to the establishment of simple rules that could be developed into mathematical equations to describe the LRBD of polypeptides. The N_blob values retrieved from the FBM analysis of the fluorescence decays acquired with the pyrene-labeled polypeptides could then be employed to predict the total conformational search time (τ_tcs) of any polypeptide based on their sequence. Strong correlations were found between the predicted τ_tcs and the experimental folding times of 145 proteins. The good quality of these correlations suggests that the blob-based approach described in this report might represent an interesting mathematical means for studying protein folding.

Accelerating therapeutic protein design

Protein structures provide for defined microenvironments that can support complex pharmacological functions, otherwise unachievable by small molecules. The advent of therapeutic proteins has thus greatly broadened the range of manageable disorders. Leveraging the knowledge and recent advances in de novo protein design methods has the prospect of revolutionizing how protein drugs are discovered and developed. This review lays out the main challenges facing therapeutic proteins discovery and development, and how present and future advancements of protein design can accelerate the protein drug pipelines.

Effects of ionic strength on the folding and stability of SAMP1, a ubiquitin-like halophilic protein

Our knowledge of the folding behavior of proteins from extremophiles is limited at this time. These proteins may more closely resemble the primordial proteins selected in early evolution under extreme conditions. The small archaeal modifier protein 1 (SAMP1) studied in this report is an 87-residue protein with a β-grasp fold found in the halophile Haloferax volcanii from the Dead Sea. To gain insight into the effects of salt on the stability and folding mechanism of SAMP1, we conducted equilibrium and kinetic folding experiments as a function of sodium chloride concentration. The results revealed that increasing ionic strength accelerates refolding and slows down unfolding of SAMP1, giving rise to a pronounced salt-induced stabilization. With increasing NaCl concentration, the rate of folding observed via a combination of continuous-flow (0.1-2 ms time range) and stopped-flow measurements (>2 ms) exhibited a >100-fold increase between 0.1 and 1.5 M NaCl and leveled off at higher concentrations. Using the Linderström-Lang smeared charge formalism to model electrostatic interactions in ground and transition states encountered during folding, we showed that the observed salt dependence is dominated by Debye-Hückel screening of electrostatic repulsion among numerous negatively charged residues. Comparisons are also drawn with three well-studied mesophilic members of the β-grasp superfamily: protein G, protein L, and ubiquitin. Interestingly, the folding rate of SAMP1 in 3 M sodium chloride is comparable to that of protein G, ubiquitin, and protein L at lower ionic strength. The results indicate the important role of electrostatic interactions in protein folding and imply that proteins have evolved to minimize unfavorable charge-charge interactions under their specific native conditions.

Prediction of Folding and Unfolding Rates of Proteins with Simple Models

Large differences exist between the experimentally measured folding and unfolding rates in single-domain proteins, which range from seconds to microseconds. Considerable effort has been dedicated to develop methods for the prediction of these rates using a simple set of rules. Much of this work has focused in identifying structural metrics derived from experimentally resolved protein structures that serve as good predictors of folding rates. An alternative to this ad-hoc methodology is the use of phenomenological free energy models, parametrized with empirical parameters. This alternative approach has become very useful to obtain estimates of folding and, importantly, also unfolding rates with only the information of protein size and secondary structure. Here we present the fundamentals of this type of approach and introduce a recent implementation of this predictive method.

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.

Topological principles of protein folding

What is the topology of a protein and what governs protein folding to a specific topology? This is a fundamental question in biology. The protein folding reaction is a critically important cellular process, which is failing in many prevalent diseases. Understanding protein folding is also key to the design of new proteins for applications. However, our ability to predict the folding of a protein chain is quite limited and much is still unknown about the topological principles of folding. Current predictors of folding kinetics, including the contact order and size, present a limited predictive power, suggesting that these models are fundamentally incomplete. Here, we use a newly developed mathematical framework to define and extract the topology of a native protein conformation beyond knot theory, and investigate the relationship between native topology and folding kinetics in experimentally characterized proteins. We show that not only the folding rate, but also the mechanistic insight into folding mechanisms can be inferred from topological parameters. We identify basic topological features that speed up or slow down the folding process. The approach enabled the decomposition of protein 3D conformation into topologically independent elementary folding units, called circuits. The number of circuits correlates significantly with the folding rate, offering not only an efficient kinetic predictor, but also a tool for a deeper understanding of theoretical folding models. This study contributes to recent work that reveals the critical relevance of topology to protein folding with a new, contact-based, mathematically rigorous perspective. We show that topology can predict folding kinetics when geometry-based predictors like contact order and size fail.

First-passage times in protein folding: exploring the native-like states vs. overcoming the free energy barrier

Using a model β-hairpin protein as a representative example of simple two-state folders whose kinetics are uncomplicated by the presence of on- and off-pathway intermediates, it is studied how the search for the protein's native state among native-like states affects the folding kinetics. It is revealed that the first-passage time (FPT) distributions are essentially single-exponential not only for the times to overcome the free energy barrier between the unfolded and native-like states but also for the times to find the native state among the native-like ones. The FPT distributions of this type are observed through all studied two-state-like regimes of protein folding, varying from a regime close to two-state folding to a regime close to downhill folding. If the protein explores native-like states for a time much longer than the time to overcome the free energy barrier, which is characteristic of high temperatures, the resulting FPT distribution to reach the native state remains close to exponential but the mean FPT (MFPT) is determined not by the height of the free energy barrier but by the time to explore native-like states. In particular, the mean time to overcome the free energy barrier is in reasonable agreement with the Kramers rate formula and generally far shorter than the overall MFPT to reach the native state. The observed increase of the overall MFPT, as a result of longer exploration of native-like states, may lead to an overestimate of the height of the free energy barrier between the unfolded and folded states when it is calculated from the overall MFPT.

A molecular dynamics study of protein denaturation induced by sulfonate-based surfactants

Microsecond timescale explicit-solvent atomistic simulations were carried out to investigate how anionic surfactants modulate protein structure and dynamics. We found that lysozyme undergoes near-complete denaturation at the high concentration (> 0.1 M) of sodium pentadecyl sulfonate (SPDS), while only partial denaturation occurs at the concentration slightly below 0.1 M. In large part, protein denaturation is structurally manifested by disappearance of helical segments and loss of tertiary interactions. The computational prediction of the extent of burial of cysteine residues was experimentally validated by measuring the accessibility of the respective sulfhydryl groups. Overall, our work indicates an interesting synergy between electrostatic and hydrophobic contributions to lysozyme's denaturation process by anionic surfactants. In fact, first disulfide bridges and hydrogen bonds from protein surface to SPDS head groups loosen the protein globule followed by fuller denaturation via insertion of the surfactant's hydrophobic tails into the protein core.

The Right-Handed Parallel β-Helix Topology of Erwinia chrysanthemi Pectin Methylesterase Is Intimately Associated with Both Sequential Folding and Resistance to High Pressure

The complex topologies of large multi-domain globular proteins make the study of their folding and assembly particularly demanding. It is often characterized by complex kinetics and undesired side reactions, such as aggregation. The structural simplicity of tandem-repeat proteins, which are characterized by the repetition of a basic structural motif and are stabilized exclusively by sequentially localized contacts, has provided opportunities for dissecting their folding landscapes. In this study, we focus on the Erwinia chrysanthemi pectin methylesterase (342 residues), an all-β pectinolytic enzyme with a right-handed parallel β-helix structure. Chemicals and pressure were chosen as denaturants and a variety of optical techniques were used in conjunction with stopped-flow equipment to investigate the folding mechanism of the enzyme at 25 °C. Under equilibrium conditions, both chemical- and pressure-induced unfolding show two-state transitions, with average conformational stability (ΔG° = 35 ± 5 kJ·mol⁻¹) but exceptionally high resistance to pressure (P_m = 800 ± 7 MPa). Stopped-flow kinetic experiments revealed a very rapid (τ < 1 ms) hydrophobic collapse accompanied by the formation of an extended secondary structure but did not reveal stable tertiary contacts. This is followed by three distinct cooperative phases and the significant population of two intermediate species. The kinetics followed by intrinsic fluorescence shows a lag phase, strongly indicating that these intermediates are productive species on a sequential folding pathway, for which we propose a plausible model. These combined data demonstrate that even a large repeat protein can fold in a highly cooperative manner.

Folding and Stability of Ankyrin Repeats Control Biological Protein Function

Ankyrin repeat proteins are found in all three kingdoms of life. Fundamentally, these proteins are involved in protein-protein interaction in order to activate or suppress biological processes. The basic architecture of these proteins comprises repeating modules forming elongated structures. Due to the lack of long-range interactions, a graded stability among the repeats is the generic properties of this protein family determining both protein folding and biological function. Protein folding intermediates were frequently found to be key for the biological functions of repeat proteins. In this review, we discuss most recent findings addressing this close relation for ankyrin repeat proteins including DARPins, Notch receptor ankyrin repeat domain, IκBα inhibitor of NFκB, and CDK inhibitor p19^INK4d. The role of local folding and unfolding and gradual stability of individual repeats will be discussed during protein folding, protein-protein interactions, and post-translational modifications. The conformational changes of these repeats function as molecular switches for biological regulation, a versatile property for modern drug discovery.

An Effective Cumulative Torsion Angles Model for Prediction of Protein Folding Rates

BACKGROUND

Protein folding rate is mainly determined by the size of the conformational space to search, which in turn is dictated by factors such as size, structure and amino-acid sequence in a protein. It is important to integrate these factors effectively to form a more precisely description of conformation space. But there is no general paradigm to answer this question except some intuitions and empirical rules. Therefore, at the present stage, predictions of the folding rate can be improved through finding new factors, and some insights are given to the above question.

OBJECTIVE

Its purpose is to propose a new parameter that can describe the size of the conformational space to improve the prediction accuracy of protein folding rate.

METHODS

Based on the optimal set of amino acids in a protein, an effective cumulative backbone torsion angles (CBTAeff) was proposed to describe the size of the conformational space. Linear regression model was used to predict protein folding rate with CBTAeff as a parameter. The degree of correlation was described by the coefficient of determination and the mean absolute error MAE between the predicted folding rates and experimental observations.

RESULTS

It achieved a high correlation (with the coefficient of determination of 0.70 and MAE of 1.88) between the logarithm of folding rates and the (CBTAeff)0.5 with experimental over 112 twoand multi-state folding proteins.

CONCLUSION

The remarkable performance of our simplistic model demonstrates that CBTA based on optimal set was the major determinants of the conformation space of natural proteins.

Effect of Protein Structure on Evolution of Cotranslational Folding

Cotranslational folding depends on the folding speed and stability of the nascent protein. It remains difficult, however, to predict which proteins cotranslationally fold. Here, we simulate evolution of model proteins to investigate how native structure influences evolution of cotranslational folding. We developed a model that connects protein folding during and after translation to cellular fitness. Model proteins evolved improved folding speed and stability, with proteins adopting one of two strategies for folding quickly. Low contact order proteins evolve to fold cotranslationally. Such proteins adopt native conformations early on during the translation process, with each subsequently translated residue establishing additional native contacts. On the other hand, high contact order proteins tend not to be stable in their native conformations until the full chain is nearly extruded. We also simulated evolution of slowly translating codons, finding that slower translation speeds at certain positions enhances cotranslational folding. Finally, we investigated real protein structures using a previously published data set that identified evolutionarily conserved rare codons in Escherichia coli genes and associated such codons with cotranslational folding intermediates. We found that protein substructures preceding conserved rare codons tend to have lower contact orders, in line with our finding that lower contact order proteins are more likely to fold cotranslationally. Our work shows how evolutionary selection pressure can cause proteins with local contact topologies to evolve cotranslational folding.

Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications

Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.

Design of novel protein building modules and modular architectures

Nature uses only a limited number of protein topologies and while several folds have evolved independently over time, there are clearly many possible topologies that have not been explored by evolution. With recent advances of protein design concepts, computational modeling tools, high resolution and high-throughput experimental methods it is now possible to design new protein architectures. The collection of building blocks and design principles widened both in size and complexity, offering an expanded toolset for building new modular folds and functional protein structures. Here we review and discuss recent achievements of protein design, focusing in particular on the use and prospects of modular approaches for assembling new protein folds.

The Molten Globule, and Two-State vs. Non-Two-State Folding of Globular Proteins

From experimental studies of protein folding, it is now clear that there are two types of folding behavior, i.e., two-state folding and non-two-state folding, and understanding the relationships between these apparently different folding behaviors is essential for fully elucidating the molecular mechanisms of protein folding. This article describes how the presence of the two types of folding behavior has been confirmed experimentally, and discusses the relationships between the two-state and the non-two-state folding reactions, on the basis of available data on the correlations of the folding rate constant with various structure-based properties, which are determined primarily by the backbone topology of proteins. Finally, a two-stage hierarchical model is proposed as a general mechanism of protein folding. In this model, protein folding occurs in a hierarchical manner, reflecting the hierarchy of the native three-dimensional structure, as embodied in the case of non-two-state folding with an accumulation of the molten globule state as a folding intermediate. The two-state folding is thus merely a simplified version of the hierarchical folding caused either by an alteration in the rate-limiting step of folding or by destabilization of the intermediate.