There and back again: Two views on the protein folding puzzle

Why does a cell function? New arguments in favor of quantum effects

In this study, the complexities of intracellular processes have been analyzed, including DNA folding, alternative splicing, mitochondrial function, and enzyme transport in lysosomes. Based on a previously proposed hypothesis (Levinthal's generalized paradox), a conclusion is made that all abovementioned processes cannot be realized with sufficient accuracy and in a realistic timeframe within the framework of classical physics. It is unclear why the cell functions at all. For the cell to function, its internal environment must be highly structured. In this regard, the cell shares similarities with computational devices (computers). In this study, quantum models of interactions between biologically important molecules were constructed, taking into account the long-range effects. One significant aspect of these models is the special role of the phase of the wavefunction, which serves as a controlling parameter. Experiments have been proposed that may confirm or refute these models.

Plant protein solubility: A challenge or insurmountable obstacle

Currently, there is an increasing focus on comprehending the solubility of plant-based proteins, driven by the rising demand for animal-free food formulations. The solubility of proteins plays a crucial role in impacting other functional properties of proteins and food processing. Consequently, understanding protein solubility in a deeper sense may allow a better usage of plant proteins. Herein, we discussed the definition of protein solubility from both thermodynamic and colloidal perspectives. A range of factors affecting solubility of plant proteins are generalized, including intrinsic factors (amino acids composition, hydrophobicity), and extrinsic factors (pH, ionic strength, extraction and drying methods). Current methods to enhance solubility are outlined, including microwave, high intensity ultrasound, hydrostatic pressure, glycation, pH-shifting, enzymatic hydrolysis, enzymatic cross-linking, complexation and modulation of amino acids. We base the discussion on diverse modified methods of nitrogen solubility index available to determine and analyze protein solubility followed by addressing how other indigenous components affect the solubility of plant proteins. Some nonproteinaceous constituents in proteins such as carbohydrates and polyphenols may exert positive or negative impact on protein solubility. Appropriate protein extraction and modification methods that meet consumer and manufacturers requirements concerning nutritious and eco-friendly foods with lower cost should be investigated and further explored.

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.

Mapping Protein Structural Evolution upon Unfolding

In the past, many intensive attempts failed to capture or underestimated the copopulated intermediate conformers from the protein folding/unfolding reaction. We report a promising approach to kinetically trap, resolve, and quantify protein conformers that evolve during unfolding in solution. We conducted acid-induced unfolding of three model proteins (cytochrome c, myoglobin, and lysozyme), and the corresponding reaction aliquots upon decreasing the pH were electrosprayed for high field asymmetric waveform ion mobility spectrometry (FAIMS) measurements. The copopulated conformers were resolved, visualized, and quantified by a two-dimensional mapping of the FAIMS output. Contrary to expectations, all the above proteins appeared metamorphic (multiple-folded conformations) at the physiological pH, and cytochrome c exhibited an unusual "conformational shuttling" before forming the molten globule state. Thus, in contrast to many previous studies, a wide variety of thermodynamically stable intermediate conformers, including compact, molten globule, and partially unfolded forms, was trapped from solution, probing the unfolding mechanism in detail.

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.

Expanding the toolbox for predictive parameters describing antibody stability considering thermodynamic and kinetic determinants

PURPOSE

Introduction of the activation energy (E_a) as a kinetic parameter to describe and discriminate monoclonal antibody (mAb) stability.

METHODS

E_a is derived from intrinsic fluorescence (IF) unfolding thermograms. An apparent irreversible three-state fit model based on the Arrhenius integral is developed to determine E_a of respective unfolding transitions. These activation energies are compared to the thermodynamic parameter of van´t Hoff enthalpies (∆H_vh). Using a set of 34 mAbs formulated in four different formulations, both the apparent thermodynamic and kinetic parameters together with apparent melting temperatures are correlated collectively with each other to storage stabilities to evaluate its predictive power with respect to long-term effects potentially reflected in shelf-life.

RESULTS

E_a allows for the discrimination of (i) different parent mAbs, (ii) different variants that originate from parent mAbs, and (iii) different formulations. Interestingly, we observed that the E_a of the CH₂ unfolding transition shows strongest correlations with monomer and aggregate content after storage at accelerated and stress conditions when collectively compared to ∆H_vh and T_m of the CH₂ transition. Moreover, the predictive parameters determined for the CH₂ domain show generally stronger correlations with monomer and aggregate content than those derived for the Fab. Qualitative assessment by ranking E_a of the Fab domain showed good agreement with monomer content in storage stabilities of individual mAb sub-sets.

CONCLUSION

E_a from IF unfolding transitions can be used in addition to other commonly used thermodynamic predictive parameters to discriminate and characterize thermal stability of different mAbs in different formulations. Hence, it shows great potential for antibody engineering and formulation scientists.

Residue Folding Degree-Relationship to Secondary Structure Categories and Use as Collective Variable

Recently, we have shown that the residue folding degree, a network-based measure of folded content in proteins, is able to capture backbone conformational transitions related to the formation of secondary structures in molecular dynamics (MD) simulations. In this work, we focus primarily on developing a collective variable (CV) for MD based on this residue-bound parameter to be able to trace the evolution of secondary structure in segments of the protein. We show that this CV can do just that and that the related energy profiles (potentials of mean force, PMF) and transition barriers are comparable to those found by others for particular events in the folding process of the model mini protein Trp-cage. Hence, we conclude that the relative segment folding degree (the newly proposed CV) is a computationally viable option to gain insight into the formation of secondary structures in protein dynamics. We also show that this CV can be directly used as a measure of the amount of α-helical content in a selected segment.

Two energy barriers and a transient intermediate state determine the unfolding and folding dynamics of cold shock protein

Cold shock protein (Csp) is a typical two-state folding model protein which has been widely studied by biochemistry and single molecule techniques. Recently two-state property of Csp was confirmed by atomic force microscopy (AFM) through direct pulling measurement, while several long-lifetime intermediate states were found by force-clamp AFM. We systematically studied force-dependent folding and unfolding dynamics of Csp using magnetic tweezers with intrinsic constant force capability. Here we report that Csp mostly folds and unfolds with a single step over force range from 5 pN to 50 pN, and the unfolding rates show different force sensitivities at forces below and above ~8 pN, which determines a free energy landscape with two barriers and a transient intermediate state between them along one transition pathway. Our results provide a new insight on protein folding mechanism of two-state proteins.

Towards kinetic control of coordination self-assembly: a case study of a Pd3L6 double-walled triangle to predict the outcomes by a reaction network model

Numerical analysis of self-assembly process (NASAP) was performed for a [Pd3L6]6+ double-walled triangle (DWT) complex. With a chemical reaction network and a parameter set of the reaction rate constants obtained from a numerical search in an eighteen-dimensional parameter space to obtain a good fit to the data from the experimental counterpart (quantitative analysis of self-assembly process, QASAP), a refined calculation resulted in a detailed time evolution of each molecular species. Analysis based on those clues revealed dominant self-assembly pathways and a balance between inter- and intramolecular reactions, and enabled prediction of the reaction outcomes depending on the initial stoichiometric ratio under kinetic control.

Protein Dynamics and the Folding Degree

The analysis of folding trajectories for proteins is an open challenge. One of the problems is how to describe the amount of folded secondary structure in a protein. We extend the use of Estradas' folding degree (Bioinformatics 2002, 18, 697) for the analysis of the evolution of the folding stage during molecular dynamics (MD) simulation. It is shown that residue contribution to the total folding degree is a predominantly local property, well-defined by the backbone dihedral angles at the given residue, without significant contribution from the backbone conformation of other residues. Moreover, the magnitude of this residue contribution can be quite easily associated with characteristic motifs of secondary protein structures such as the α-helix, β-sheet (hairpin), and so on by means of a Ramachandran-like plot as a function of backbone dihedral angles φ,ψ. Additionally, the understanding of the free energy profile associated with the folding process becomes much simpler. Often a 1D profile is sufficient to locate global minima and the corresponding structure for short peptides.

Solution of Levinthal's Paradox and a Physical Theory of Protein Folding Times

“How do proteins fold?” Researchers have been studying different aspects of this question for more than 50 years. The most conceptual aspect of the problem is how protein can find the global free energy minimum in a biologically reasonable time, without exhaustive enumeration of all possible conformations, the so-called “Levinthal’s paradox.” Less conceptual but still critical are aspects about factors defining folding times of particular proteins and about perspectives of machine learning for their prediction. We will discuss in this review the key ideas and discoveries leading to the current understanding of folding kinetics, including the solution of Levinthal’s paradox, as well as the current state of the art in the prediction of protein folding times.

Degradation of proteins by PROTACs and other strategies

Blocking the biological functions of scaffold proteins and aggregated proteins is a challenging goal. PROTAC proteolysis-targeting chimaera (PROTAC) technology may be the solution, considering its ability to selectively degrade target proteins. Recent progress in the PROTAC strategy include identification of the structure of the first ternary eutectic complex, extra-terminal domain-4-PROTAC-Von-Hippel-Lindau (BRD4-PROTAC-VHL), and PROTAC ARV-110 has entered clinical trials for the treatment of prostate cancer in 2019. These discoveries strongly proved the value of the PROTAC strategy. In this perspective, we summarized recent meaningful research of PROTAC, including the types of degradation proteins, preliminary biological data in vitro and in vivo, and new E3 ubiquitin ligases. Importantly, the molecular design, optimization strategy and clinical application of candidate molecules are highlighted in detail. Future perspectives for development of advanced PROTAC in medical fields have also been discussed systematically.

Life in Phases: Intra- and Inter- Molecular Phase Transitions in Protein Solutions

Proteins, these evolutionarily-edited biological polymers, are able to undergo intramolecular and intermolecular phase transitions. Spontaneous intramolecular phase transitions define the folding of globular proteins, whereas binding-induced, intra- and inter- molecular phase transitions play a crucial role in the functionality of many intrinsically-disordered proteins. On the other hand, intermolecular phase transitions are the behind-the-scenes players in a diverse set of macrosystemic phenomena taking place in protein solutions, such as new phase nucleation in bulk, on the interface, and on the impurities, protein crystallization, protein aggregation, the formation of amyloid fibrils, and intermolecular liquid-liquid or liquid-gel phase transitions associated with the biogenesis of membraneless organelles in the cells. This review is dedicated to the systematic analysis of the phase behavior of protein molecules and their ensembles, and provides a description of the major physical principles governing intramolecular and intermolecular phase transitions in protein solutions.

Protein misfolding, aggregation and mechanism of amyloid cytotoxicity: An overview and therapeutic strategies to inhibit aggregation

Protein and peptides are converted from their soluble forms into highly ordered fibrillar aggregates under various conditions inside the cell. Such transitions confer diverse neurodegenerative diseases including Alzheimer's disease, Huntington's disease Prion's disease, Parkinson's disease, polyQ and share abnormal folding of potentially cytotoxic protein species linked with degeneration and death of precise neuronal populations. Presently, major advances are made to understand and get detailed insight into the structural basis and mechanism of amyloid formation, cytotoxicity and therapeutic approaches to combat them. Here we highlight classifies and summarizes the detailed overview of protein misfolding and aggregation at their molecular level including the factors that promote protein aggregation under in vivo and in vitro conditions. In addition, we describe the recent technologies that aid the characterization of amyloid aggregates along with several models that might be responsible for amyloid induced cytotoxicity to cells. Overview on the inhibition of amyloidosis by targeting different small molecules (both natural and synthetic origin) have been also discussed, that provides important approaches to identify novel targets and develop specific therapeutic strategies to combat protein aggregation related neurodegenerative diseases.

The Role of Hydrogen Bonding in the Folding/Unfolding Process of Hydrated Lysozyme: A Review of Recent NMR and FTIR Results

The biological activity of proteins depends on their three-dimensional structure, known as the native state. The main force driving the correct folding mechanism is the hydrophobic effect and when this folding kinetics is altered, aggregation phenomena intervene causing the occurrence of illnesses such as Alzheimer and Parkinson’s diseases. The other important effect is performed by water molecules and by their ability to form a complex network of hydrogen bonds whose dynamics influence the mobility of protein amino acids. In this work, we review the recent results obtained by means of spectroscopic techniques, such as Fourier Transform Infrared (FTIR) and Nuclear Magnetic Resonance (NMR) spectroscopies, on hydrated lysozyme. In particular, we explore the Energy Landscape from the thermal region of configurational stability up to that of the irreversible denaturation. The importance of the coupling between the solute and the solvent will be highlighted as well as the different behaviors of hydrophilic and hydrophobic moieties of protein amino acid residues.

From Levinthal's Paradox to the Effects of Cell Environmental Perturbation on Protein Folding

BACKGROUND

The rapidly increasing number of known protein sequences calls for more efficient methods to predict the Three-Dimensional (3D) structures of proteins, thus providing basic knowledge for rational drug design. Understanding the folding mechanism of proteins is valuable for predicting their 3D structures and for designing proteins with new functions and medicinal applications. Levinthal's paradox is that although the astronomical number of conformations possible even for proteins as small as 100 residues cannot be fully sampled, proteins in nature normally fold into the native state within timescales ranging from microseconds to hours. These conflicting results reveal that there are factors in organisms that can assist in protein folding.

METHODS

In this paper, we selected a crowded cell-like environment and temperature, and the top three Posttranslational Modifications (PTMs) as examples to show that Levinthal's paradox does not reflect the folding mechanism of proteins. We then revealed the effects of these factors on protein folding.

RESULTS

The results summarized in this review indicate that a crowded cell-like environment, temperature, and the top three PTMs reshape the Free Energy Landscapes (FELs) of proteins, thereby regulating the folding process. The balance between entropy and enthalpy is the key to understanding the effect of the crowded cell-like environment and PTMs on protein folding. In addition, the stability/flexibility of proteins is regulated by temperature.

CONCLUSION

This paper concludes that the cellular environment could directly intervene in protein folding. The long-term interactions of the cellular environment and sequence evolution may enable proteins to fold efficiently. Therefore, to correctly understand the folding mechanism of proteins, the effect of the cellular environment on protein folding should be considered.

Combined approaches from physics, statistics, and computer science for ab initio protein structure prediction: ex unitate vires (unity is strength)?

Connecting the dots among the amino acid sequence of a protein, its structure, and its function remains a central theme in molecular biology, as it would have many applications in the treatment of illnesses related to misfolding or protein instability. As a result of high-throughput sequencing methods, biologists currently live in a protein sequence-rich world. However, our knowledge of protein structure based on experimental data remains comparatively limited. As a consequence, protein structure prediction has established itself as a very active field of research to fill in this gap. This field, once thought to be reserved for theoretical biophysicists, is constantly reinventing itself, borrowing ideas informed by an ever-increasing assembly of scientific domains, from biology, chemistry, (statistical) physics, mathematics, computer science, statistics, bioinformatics, and more recently data sciences. We review the recent progress arising from this integration of knowledge, from the development of specific computer architecture to allow for longer timescales in physics-based simulations of protein folding to the recent advances in predicting contacts in proteins based on detection of coevolution using very large data sets of aligned protein sequences.

Modeling protein folding in vivo

A half century of studying protein folding in vitro and modeling it in silico has not provided us with a reliable computational method to predict the native conformations of proteins de novo, let alone identify the intermediates on their folding pathways. In this Opinion article, we suggest that the reason for this impasse is the over-reliance on current physical models of protein folding that are based on the assumption that proteins are able to fold spontaneously without assistance. These models arose from studies conducted in vitro on a biased sample of smaller, easier-to-isolate proteins, whose native structures appear to be thermodynamically stable. Meanwhile, the vast empirical data on the majority of larger proteins suggests that once these proteins are completely denatured in vitro, they cannot fold into native conformations without assistance. Moreover, they tend to lose their native conformations spontaneously and irreversibly in vitro, and therefore such conformations must be metastable. We propose a model of protein folding that is based on the notion that the folding of all proteins in the cell is mediated by the actions of the "protein folding machine" that includes the ribosome, various chaperones, and other components involved in co-translational or post-translational formation, maintenance and repair of protein native conformations in vivo. The most important and universal component of the protein folding machine consists of the ribosome in complex with the welcoming committee chaperones. The concerted actions of molecular machinery in the ribosome peptidyl transferase center, in the exit tunnel, and at the surface of the ribosome result in the application of mechanical and other forces to the nascent peptide, reducing its conformational entropy and possibly creating strain in the peptide backbone. The resulting high-energy conformation of the nascent peptide allows it to fold very fast and to overcome high kinetic barriers along the folding pathway. The early folding intermediates in vivo are stabilized by interactions with the ribosome and welcoming committee chaperones and would not be able to exist in vitro in the absence of such cellular components. In vitro experiments that unfold proteins by heat or chemical treatment produce denaturation ensembles that are very different from folding intermediates in vivo and therefore have very limited use in reconstructing the in vivo folding pathways. We conclude that computational modeling of protein folding should deemphasize the notion of unassisted thermodynamically controlled folding, and should focus instead on the step-by-step reverse engineering of the folding process as it actually occurs in vivo.

REVIEWERS

This article was reviewed by Eugene Koonin and Frank Eisenhaber.

Coarse-Grained Modeling of the Interplay between Secondary Structure Propensities and Protein Fold Assembly

We recently developed a new coarse-grained model of protein structure and dynamics [ Dawid et al. J. Chem. Theory Comput. 2017 , 13 ( 11 ), 5766 - 5779 ]. The model assumed a single bead representation of amino acid residues, where positions of such united residues were defined by centers of mass of four amino acid fragments. Replica exchange Monte Carlo sampling of the model chains provided good pictures of modeled structures and their dynamics. In its generic form the statistical knowledge-based force field of the model has been dedicated for single-domain globular proteins. Sequence-specific interactions are defined by three-letter secondary structure data. In the present work we demonstrate that different assignments and/or predictions of secondary structures are usually sufficient for enforcing cooperative formation of native-like folds of SURPASS chains for the majority of single-domain globular proteins. Simulations of native-like structure assembly for a representative set of globular proteins have shown that the accuracy of secondary structure data is usually not crucial for model performance, although some specific errors can strongly distort the obtained three-dimensional structures.