Foldons, protein structural modules, and exons

Reassessing the exon-foldon correspondence using frustration analysis

Protein folding and evolution are intimately linked phenomena. Here, we revisit the concept of exons as potential protein folding modules across a set of 38 abundant and conserved protein families. Taking advantage of genomic exon-intron organization and extensive protein sequence data, we explore exon boundary conservation and assess the foldon-like behavior of exons using energy landscape theoretic measurements. We found deviations in the exon size distribution from exponential decay indicating selection in evolution. We show that when taken together there is a pronounced tendency to independent foldability for segments corresponding to the more conserved exons, supporting the idea of exon-foldon correspondence. While 45% of the families follow this general trend when analyzed individually, there are some families for which other stronger functional determinants, such as preserving frustrated active sites, may be acting. We further develop a systematic partitioning of protein domains using exon boundary hotspots, showing that minimal common exons correspond with uninterrupted alpha and/or beta elements for the majority of the families but not for all of them.

Evolutionary adaptation of the protein folding pathway for secretability

Secretory preproteins of the Sec pathway are targeted post-translationally and cross cellular membranes through translocases. During cytoplasmic transit, mature domains remain non-folded for translocase recognition/translocation. After translocation and signal peptide cleavage, mature domains fold to native states in the bacterial periplasm or traffic further. We sought the structural basis for delayed mature domain folding and how signal peptides regulate it. We compared how evolution diversified a periplasmic peptidyl-prolyl isomerase PpiA mature domain from its structural cytoplasmic PpiB twin. Global and local hydrogen-deuterium exchange mass spectrometry showed that PpiA is a slower folder. We defined at near-residue resolution hierarchical folding initiated by similar foldons in the twins, at different order and rates. PpiA folding is delayed by less hydrophobic native contacts, frustrated residues and a β-turn in the earliest foldon and by signal peptide-mediated disruption of foldon hierarchy. When selected PpiA residues and/or its signal peptide were grafted onto PpiB, they converted it into a slow folder with enhanced in vivo secretion. These structural adaptations in a secretory protein facilitate trafficking.

Localization of Energetic Frustration in Proteins

We present a detailed heuristic method to quantify the degree of local energetic frustration manifested by protein molecules. Current applications are realized in computational experiments where a protein structure is visualized highlighting the energetic conflicts or the concordance of the local interactions in that structure. Minimally frustrated linkages highlight the stable folding core of the molecule. Sites of high local frustration, in contrast, often indicate functionally relevant regions such as binding, active, or allosteric sites.

Rational Design of Protein-Specific Folding Modifiers

Protein-folding can go wrong in vivo and in vitro, with significant consequences for the living organism and the pharmaceutical industry, respectively. Here we propose a design principle for small-peptide-based protein-specific folding modifiers. The principle is based on constructing a "xenonucleus", which is a prefolded peptide that mimics the folding nucleus of a protein. Using stopped-flow kinetics, NMR spectroscopy, Förster resonance energy transfer, single-molecule force measurements, and molecular dynamics simulations, we demonstrate that a xenonucleus can make the refolding of ubiquitin faster by 33 ± 5%, while variants of the same peptide have little or no effect. Our approach provides a novel method for constructing specific, genetically encodable folding catalysts for suitable proteins that have a well-defined contiguous folding nucleus.

A coarse-grained mechanical model for folding and unfolding of tropoelastin with possible mutations

We propose a simple general framework to predict folding, native states, energy barriers, protein unfolding, as well as mutation induced diseases and other protein structural analyses. The model should not be considered as an alternative to classical approaches (Molecular Dynamics or Monte Carlo) because it neglects low scale details and rather focuses on global features of proteins and structural information. We aim at the description of phenomena that are out of the range of classical molecular modeling approaches due to the large computational cost: multimolecular interactions, cyclic behavior under variable external interactions, and similar. To demonstrate the effectiveness of the approach in a real case, we focus on the folding and unfolding behavior of tropoelastin and its mutations. Specifically, we derive a discrete mechanical model whose structure is deduced based on a coarse graining approach that allows us to group the amino acids sequence in a smaller number of `equivalent' masses. Nearest neighbor energy terms are then introduced to reproduce the interaction of such amino acid groups. Nearest and non-nearest neighbor energy terms, inter and intra functional blocks are phenomenologically added in the form of Morse potentials. As we show, the resulting system reproduces important properties of the folding-unfolding mechanical response, including the monotonic and cyclic force-elongation behavior, representing a physiologically important information for elastin. The comparison with the experimental behavior of mutated tropoelastin confirms the predictivity of the model. STATEMENT OF SIGNIFICANCE: Classical approaches to the study of phenomena at the molecular scale such as Molecular Dynamics (MD) represent an incredible tool to unveil mechanical and conformational properties of macromolecules, in particular for biological and medical applications. On the other hand, due to the computational cost, the time and spatial scales are limited. Focusing of the real case of tropoelastin, we propose a new approach based on a careful coarse graining of the system, able to describe the overall properties of the macromolecule and amenable of extension to larger scale effects (protein bundles, protein-protein interactions, cyclic loading). The comparison with tropoelastin behavior, also for mutations, is very promising.

Structure elements can be predicted using the contact volume among protein residues

Previously, the structure elements of dihydrofolate reductase (DHFR) were determined using comprehen­sive Ala-insertion mutation analysis, which is assumed to be a kind of protein “building blocks.” It is hypo­thesized that our comprehension of the structure elements could lead to understanding how an amino acid sequence dictates its tertiary structure. However, the comprehensive Ala-insertion mutation analysis is a time- and cost-consuming process and only a set of the DHFR structure elements have been reported so far. Therefore, developing a computational method to predict structure elements is an urgent necessity. We focused on intramolecular residue–residue contacts to predict the structure elements. We introduced a simple and effective parameter: the overlapped contact volume (CV) among the residues and calculated the CV along the DHFR sequence using the crystal structure. Our results indicate that the CV profile can recapitulate its precipitate ratio profile, which was used to define the structure elements in the Ala-insertion mutation analysis. The CV profile allowed us to predict structure elements like the experimentally determined structure elements. The strong correlation between the CV and precipitate ratio profiles indicates the importance of the intramolecular residue–residue contact in maintaining the tertiary structure. Additionally, the CVs between the structure elements are considerably more than those between a structure element and a linker or two linkers, indicating that the structure elements play a funda­mental role in increasing the intramolecular adhesion. Thus, we propose that the structure elements can be considered a type of “building blocks” that maintain and dictate the tertiary structures of proteins.

Glassy Dynamics and Memory Effects in an Intrinsically Disordered Protein Construct

Glassy, nonexponential relaxations in globular proteins are typically attributed to conformational behaviors that are missing from intrinsically disordered proteins. Yet, we show that single molecules of a disordered-protein construct display two signatures of glassy dynamics, logarithmic relaxations and a Kovacs memory effect, in response to changes in applied tension. We attribute this to the presence of multiple independent local structures in the chain, which we corroborate with a model that correctly predicts the force dependence of the relaxation. The mechanism established here likely applies to other disordered proteins.

Experimentally-driven protein structure modeling

Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.

Successes and challenges in simulating the folding of large proteins

Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structure-based models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.

StructureDistiller: Structural relevance scoring identifies the most informative entries of a contact map

Protein folding and structure prediction are two sides of the same coin. Contact maps and the related techniques of constraint-based structure reconstruction can be considered as unifying aspects of both processes. We present the Structural Relevance (SR) score which quantifies the information content of individual contacts and residues in the context of the whole native structure. The physical process of protein folding is commonly characterized with spatial and temporal resolution: some residues are Early Folding while others are Highly Stable with respect to unfolding events. We employ the proposed SR score to demonstrate that folding initiation and structure stabilization are subprocesses realized by distinct sets of residues. The example of cytochrome c is used to demonstrate how StructureDistiller identifies the most important contacts needed for correct protein folding. This shows that entries of a contact map are not equally relevant for structural integrity. The proposed StructureDistiller algorithm identifies contacts with the highest information content; these entries convey unique constraints not captured by other contacts. Identification of the most informative contacts effectively doubles resilience toward contacts which are not observed in the native contact map. Furthermore, this knowledge increases reconstruction fidelity on sparse contact maps significantly by 0.4 Å.

All-Atom Simulations Reveal How Single-Point Mutations Promote Serpin Misfolding

Protein misfolding is implicated in many diseases, including serpinopathies. For the canonical inhibitory serpin α₁-antitrypsin, mutations can result in protein deficiencies leading to lung disease, and misfolded mutants can accumulate in hepatocytes, leading to liver disease. Using all-atom simulations based on the recently developed bias functional algorithm, we elucidate how wild-type α₁-antitrypsin folds and how the disease-associated S (Glu264Val) and Z (Glu342Lys) mutations lead to misfolding. The deleterious Z mutation disrupts folding at an early stage, whereas the relatively benign S mutant shows late-stage minor misfolding. A number of suppressor mutations ameliorate the effects of the Z mutation, and simulations on these mutants help to elucidate the relative roles of steric clashes and electrostatic interactions in Z misfolding. These results demonstrate a striking correlation between atomistic events and disease severity and shine light on the mechanisms driving chains away from their correct folding routes.

Characterizing the relation of functional and Early Folding Residues in protein structures using the example of aminoacyl-tRNA synthetases

Proteins are chains of amino acids which adopt a three-dimensional structure and are then able to catalyze chemical reactions or propagate signals in organisms. Without external influence, many proteins fold into their native structure, and a small number of Early Folding Residues (EFR) have previously been shown to initiate the formation of secondary structure elements and guide their respective assembly. Using the two diverse superfamilies of aminoacyl-tRNA synthetases (aaRS), it is shown that the position of EFR is preserved over the course of evolution even when the corresponding sequence conservation is small. Folding initiation sites are positioned in the center of secondary structure elements, independent of aaRS class. In class I, the predicted position of EFR resembles an ancient structural packing motif present in many seemingly unrelated proteins. Furthermore, it is shown that EFR and functionally relevant residues in aaRS are almost entirely disjoint sets of residues. The Start2Fold database is used to investigate whether this separation of EFR and functional residues can be observed for other proteins. EFR are found to constitute crucial connectors of protein regions which are distant at sequence level. Especially, these residues exhibit a high number of non-covalent residue-residue contacts such as hydrogen bonds and hydrophobic interactions. This tendency also manifests as energetically stable local regions, as substantiated by a knowledge-based potential. Despite profound differences regarding how EFR and functional residues are embedded in protein structures, a strict separation of structurally and functionally relevant residues cannot be observed for a more general collection of proteins.

Atomistic simulations indicate the functional loop-to-coiled-coil transition in influenza hemagglutinin is not downhill

Influenza hemagglutinin (HA) mediates viral entry into host cells through a large-scale conformational rearrangement at low pH that leads to fusion of the viral and endosomal membranes. Crystallographic and biochemical data suggest that a loop-to-coiled-coil transition of the B-loop region of HA is important for driving this structural rearrangement. However, the microscopic picture for this proposed "spring-loaded" movement is missing. In this study, we focus on understanding the transition of the B loop and perform a set of all-atom molecular dynamics simulations of the full B-loop trimeric structure with the CHARMM36 force field. The free-energy profile constructed from our simulations describes a B loop that stably folds half of the postfusion coiled coil in tens of microseconds, but the full coiled coil is unfavorable. A buried hydrophilic residue, Thr59, is implicated in destabilizing the coiled coil. Interestingly, this conserved threonine is the only residue in the B loop that strictly differentiates between the group 1 and 2 HA molecules. Microsecond-scale constant temperature simulations revealed that kinetic traps in the structural switch of the B loop can be caused by nonnative, intramonomer, or intermonomer β-sheets. The addition of the A helix stabilized the postfusion state of the B loop, but introduced the possibility for further β-sheet structures. Overall, our results do not support a description of the B loop in group 2 HAs as a stiff spring, but, rather, it allows for more structural heterogeneity in the placement of the fusion peptides during the fusion process.

Self-organization, entropy and allostery

Allostery is a fundamental regulatory mechanism in biology. Although generally accepted that it is a dynamics-driven process, the exact molecular mechanism of allosteric signal transmission is hotly debated. We argue that allostery is as a part of a bigger picture that also includes fractal-like properties of protein interior, hierarchical protein folding and entropy-driven molecular recognition. Although so far all these phenomena were studied separately, they stem from the same common root: self-organization of polypeptide chains and, thus, has to be studied collectively. This merge will allow the cross-referencing of a broad spectrum of multi-disciplinary data facilitating progress in all these fields.

A Data-Driven Perspective on the Hierarchical Assembly of Molecular Structures

Macromolecular systems are composed of a very large number of atomic degrees of freedom. There is strong evidence suggesting that structural changes occurring in large biomolecular systems at long time scale dynamics may be captured by models coarser than atomistic, although a suitable or optimal coarse-graining is a priori unknown. Here we propose a systematic approach to learning a coarse representation of a macromolecule from microscopic simulation data. In particular, the definition of effective coarse variables is achieved by partitioning the degrees of freedom both in the structural (physical) space and in the conformational space. The identification of groups of microscopic particles forming dynamical coherent states in different metastable states leads to a multiscale description of the system, in space and time. The application of this approach to the folding dynamics of two proteins provides a revised view of the classical idea of prestructured regions (foldons) that combine during a protein-folding process and suggests a hierarchical characterization of the assembly process of folded structures.

Marginal stability drives irreversible unfolding of large multi-domain family 3 glycosylhydrolases from thermo-tolerant yeast

Protein folding is an extremely complex and fast, yet perfectly defined process, involving interplay of many intra and inter-molecular forces. In vitro, these molecular interactions are reversible for many proteins e.g., smaller and monomeric, organized into single domains. However, refolding of larger multi-domain/multimeric proteins is much more complicated, proceeds in a hierarchal way and is often irreversible. In a comparative study on two large, multi-domain and multimeric isozymes, β-glucosidase I (BGLI) and β-glucosidase II (BGLII) from Pichia etchellsii, we studied spontaneous and assisted refolding under three denaturing conditions viz. GdnHCl, alkaline pH and heat. During refolding, higher refolding yields were obtained for BGLII in case of pH induced unfolding (13.89%±0.25) than BGLI (6%±0.85) while for GdnHCl induced unfolding, refolding was marginal (BGLI=5%±0.5; BGLII=6%±0.69). Thermal unfolding was irreversible while assisted refolding also showed little structural gain for both proteins. When the apparent free energies of unfolding (ΔG_U^app) were calculated from GdnHCl unfolding data, their values were strikingly found to be lower (BGLI ΔG_U^app=3.02kcal/mol; BGLII ΔG_U^app=2.99kcal/mol) than reported for globular (ΔG_U=5-15kcal/mol)/multimeric proteins (ΔG_U=23-29kcal/mol) indicating marginal stability results in low refolding.

Protein Assembly and Building Blocks: Beyond the Limits of the LEGO Brick Metaphor

Proteins, like other biomolecules, have a modular and hierarchical structure. Various building blocks are used to construct proteins of high structural complexity and diverse functionality. In multidomain proteins, for example, domains are fused to each other in different combinations to achieve different functions. Although the LEGO brick metaphor is justified as a means of simplifying the complexity of three-dimensional protein structures, several fundamental properties (such as allostery or the induced-fit mechanism) make deviation from it necessary to respect the plasticity, softness, and cross-talk that are essential to protein function. In this work, we illustrate recently reported protein behavior in multidomain proteins that deviates from the LEGO brick analogy. While earlier studies showed that a protein domain is often unaffected by being fused to another domain or becomes more stable following the formation of a new interface between the tethered domains, destabilization due to tethering has been reported for several systems. We illustrate that tethering may sometimes result in a multidomain protein behaving as "less than the sum of its parts". We survey these cases for which structure additivity does not guarantee thermodynamic additivity. Protein destabilization due to fusion to other domains may be linked in some cases to biological function and should be taken into account when designing large assemblies.

The case for defined protein folding pathways

We consider the differences between the many-pathway protein folding model derived from theoretical energy landscape considerations and the defined-pathway model derived from experiment. A basic tenet of the energy landscape model is that proteins fold through many heterogeneous pathways by way of amino acid-level dynamics biased toward selecting native-like interactions. The many pathways imagined in the model are not observed in the structure-formation stage of folding by experiments that would have found them, but they have now been detected and characterized for one protein in the initial prenucleation stage. Analysis presented here shows that these many microscopic trajectories are not distinct in any functionally significant way, and they have neither the structural information nor the biased energetics needed to select native vs. nonnative interactions during folding. The opposed defined-pathway model stems from experimental results that show that proteins are assemblies of small cooperative units called foldons and that a number of proteins fold in a reproducible pathway one foldon unit at a time. Thus, the same foldon interactions that encode the native structure of any given protein also naturally encode its particular foldon-based folding pathway, and they collectively sum to produce the energy bias toward native interactions that is necessary for efficient folding. Available information suggests that quantized native structure and stepwise folding coevolved in ancient repeat proteins and were retained as a functional pair due to their utility for solving the difficult protein folding problem.

The LINK-A lncRNA interacts with PtdIns(3,4,5)P3 to hyperactivate AKT and confer resistance to AKT inhibitors

Phosphatidylinositol-3,4,5-trisphosphate (PIP₃) mediates signaling pathways as a second messenger in response to extracellular signals. Although primordial functions of phospholipids and RNAs have been hypothesized in the “RNA world”, physiological RNA-phospholipid interactions and their involvement in essential cellular processes has remained a mystery. We explicate the contribution of lipid-binding long non-coding RNAs (lncRNAs) in cancer cells. Among them, Long Intergenic Noncoding RNA for Kinase Activation (LINK-A) directly interacts with AKT pleckstrin homology domain and PIP₃ at the single nucleotide level, facilitating AKT-PIP₃ interaction and consequent enzymatic activation. LINK-A-dependent AKT hyperactivation leads to tumorigenesis and resistance to AKT inhibitors. Genomic deletions of the LINK-A PIP₃-binding motif dramatically sensitized breast cancer cells to AKT inhibitors. Furthermore, meta-analysis showed the correlation between LINK-A expression and incidence of a SNP (rs12095274: A>G), AKT phosphorylation status, and poor outcomes for breast and lung cancer patients. PIP₃-binding lncRNA modulates AKT activation with broad clinical implications.

On the indirect relationship between protein dynamics and enzyme activity

The behaviors of simple thermal systems have been well studied in physical chemistry and the principles obtained from such studies have been applied to complex thermal systems, such as proteins and enzymes. But the simple application of such principles is questionable and may lead to mistakes under some circumstances. In enzymology, the transition state theory of chemical reactions has been accepted as a fundamental theory, but the role of protein dynamics in enzyme catalysis is controversial in the context of transition state theory. By studying behaviors of complex thermal systems, we have revised the Arrhenius equation and transition state theory and our model is validated in enzymology. Formally speaking, the revised Arrhenius equation is apparently similar to a conventional Arrhenius equation, but the physical meanings of its parameters differ from that of traditional forms in principle. Within this model, the role of protein dynamics in enzyme catalysis is well defined and quantified.

Cooperativity and modularity in protein folding

A simple statistical mechanical model proposed by Wako and Saitô has explained the aspects of protein folding surprisingly well. This model was systematically applied to multiple proteins by Muñoz and Eaton and has since been referred to as the Wako-Saitô-Muñoz-Eaton (WSME) model. The success of the WSME model in explaining the folding of many proteins has verified the hypothesis that the folding is dominated by native interactions, which makes the energy landscape globally biased toward native conformation. Using the WSME and other related models, Saitô emphasized the importance of the hierarchical pathway in protein folding; folding starts with the creation of contiguous segments having a native-like configuration and proceeds as growth and coalescence of these segments. The Φ-values calculated for barnase with the WSME model suggested that segments contributing to the folding nucleus are similar to the structural modules defined by the pattern of native atomic contacts. The WSME model was extended to explain folding of multi-domain proteins having a complex topology, which opened the way to comprehensively understanding the folding process of multi-domain proteins. The WSME model was also extended to describe allosteric transitions, indicating that the allosteric structural movement does not occur as a deterministic sequential change between two conformations but as a stochastic diffusive motion over the dynamically changing energy landscape. Statistical mechanical viewpoint on folding, as highlighted by the WSME model, has been renovated in the context of modern methods and ideas, and will continue to provide insights on equilibrium and dynamical features of proteins.

Basic units of protein structure, folding, and function

Study of the hierarchy of domain structure with alternative sets of domains and analysis of discontinuous domains, consisting of remote segments of the polypeptide chain, raised a question about the minimal structural unit of the protein domain. The hypothesis on the decisive role of the polypeptide backbone in determining the elementary units of globular proteins have led to the discovery of closed loops. It is reviewed here how closed loops form the loop-n-lock structure of proteins, providing the foundation for stability and designability of protein folds/domain and underlying their co-translational folding. Simplified protein sequences are considered here with the aim to explore the basic principles that presumably dominated the folding and stability of proteins in the early stages of structural evolution. Elementary functional loops (EFLs), closed loops with one or few catalytic residues, are, in turn, units of the protein function. They are apparent descendants of the prebiotic ring-like peptides, which gave rise to the first functional folds/domains being fused in the beginning of the evolution of protein structure. It is also shown how evolutionary relations between protein functional superfamilies and folds delineated with the help of EFLs can contribute to establishing the rules for design of desired enzymatic functions. Generalized descriptors of the elementary functions are proposed to be used as basic units in the future computational design.

Repeat proteins challenge the concept of structural domains

Structural domains are believed to be modules within proteins that can fold and function independently. Some proteins show tandem repetitions of apparent modular structure that do not fold independently, but rather co-operate in stabilizing structural forms that comprise several repeat-units. For many natural repeat-proteins, it has been shown that weak energetic links between repeats lead to the breakdown of co-operativity and the appearance of folding sub-domains within an apparently regular repeat array. The quasi-1D architecture of repeat-proteins is crucial in detailing how the local energetic balances can modulate the folding dynamics of these proteins, which can be related to the physiological behaviour of these ubiquitous biological systems.

Protein Folding-How and Why: By Hydrogen Exchange, Fragment Separation, and Mass Spectrometry

Advanced hydrogen exchange (HX) methodology can now determine the structure of protein folding intermediates and their progression in folding pathways. Key developments over time include the HX pulse labeling method with nuclear magnetic resonance analysis, the fragment separation method, the addition to it of mass spectrometric (MS) analysis, and recent improvements in the HX MS technique and data analysis. Also, the discovery of protein foldons and their role supplies an essential interpretive link. Recent work using HX pulse labeling with MS analysis finds that a number of proteins fold by stepping through a reproducible sequence of native-like intermediates in an ordered pathway. The stepwise nature of the pathway is dictated by the cooperative foldon unit construction of the protein. The pathway order is determined by a sequential stabilization principle; prior native-like structure guides the formation of adjacent native-like structure. This view does not match the funneled energy landscape paradigm of a very large number of folding tracks, which was framed before foldons were known and is more appropriate for the unguided residue-level search to surmount an initial kinetic barrier rather than for the overall unfolded-state to native-state folding pathway.

Structural and Energetic Characterization of the Ankyrin Repeat Protein Family

Ankyrin repeat containing proteins are one of the most abundant solenoid folds. Usually implicated in specific protein-protein interactions, these proteins are readily amenable for design, with promising biotechnological and biomedical applications. Studying repeat protein families presents technical challenges due to the high sequence divergence among the repeating units. We developed and applied a systematic method to consistently identify and annotate the structural repetitions over the members of the complete Ankyrin Repeat Protein Family, with increased sensitivity over previous studies. We statistically characterized the number of repeats, the folding of the repeat-arrays, their structural variations, insertions and deletions. An energetic analysis of the local frustration patterns reveal the basic features underlying fold stability and its relation to the functional binding regions. We found a strong linear correlation between the conservation of the energetic features in the repeat arrays and their sequence variations, and discuss new insights into the organization and function of these ubiquitous proteins.

Some natural proteins are formed with repetitions of similar amino acid stretches. Ankyrin-repeat proteins constitute one of the most abundant families of this class of proteins that serve as model systems to analyze how variations in sequences exert effects in structures and biological functions. We present an in-depth analysis of the ankyrin repeat protein family, characterizing the variations in the repeating arrays both at the structural and energetic level. We introduce a consistent annotation for the repeat characteristics and describe how the structural differences are related to the sequences by their underlying energetic signatures.

Topological and sequence information predict that foldons organize a partially overlapped and hierarchical structure

It has been suggested that proteins have substructures, called foldons, which can cooperatively fold into the native structure. However, several prior investigations define foldons in various ways, citing different foldon characteristics, thereby making the concept of a foldon ambiguous. In this study, we perform a Gō model simulation and analyze the characteristics of substructures that cooperatively fold into the native-like structure. Although some results do not agree well with the experimental evidence due to the simplicity of our coarse-grained model, our results strongly suggest that cooperatively folding units sometimes organize a partially overlapped and hierarchical structure. This view makes us easy to interpret some different proposal about the foldon as a difference of the hierarchical structure. On the basis of this finding, we present a new method to assign foldons and their hierarchy, using structural and sequence information. The results show that the foldons assigned by our method correspond to the intermediate structures identified by some experimental techniques. The new method makes it easy to predict whether a protein folds sequentially into the native structure or whether some foldons fold into the native structure in parallel.

Modularity in protein structures: study on all-alpha proteins

Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.

Evolution, energy landscapes and the paradoxes of protein folding

Protein folding has been viewed as a difficult problem of molecular self-organization. The search problem involved in folding however has been simplified through the evolution of folding energy landscapes that are funneled. The funnel hypothesis can be quantified using energy landscape theory based on the minimal frustration principle. Strong quantitative predictions that follow from energy landscape theory have been widely confirmed both through laboratory folding experiments and from detailed simulations. Energy landscape ideas also have allowed successful protein structure prediction algorithms to be developed. The selection constraint of having funneled folding landscapes has left its imprint on the sequences of existing protein structural families. Quantitative analysis of co-evolution patterns allows us to infer the statistical characteristics of the folding landscape. These turn out to be consistent with what has been obtained from laboratory physicochemical folding experiments signaling a beautiful confluence of genomics and chemical physics.

Frustration in biomolecules

Biomolecules are the prime information processing elements of living matter. Most of these inanimate systems are polymers that compute their own structures and dynamics using as input seemingly random character strings of their sequence, following which they coalesce and perform integrated cellular functions. In large computational systems with finite interaction-codes, the appearance of conflicting goals is inevitable. Simple conflicting forces can lead to quite complex structures and behaviors, leading to the concept of frustration in condensed matter. We present here some basic ideas about frustration in biomolecules and how the frustration concept leads to a better appreciation of many aspects of the architecture of biomolecules, and especially how biomolecular structure connects to function by means of localized frustration. These ideas are simultaneously both seductively simple and perilously subtle to grasp completely. The energy landscape theory of protein folding provides a framework for quantifying frustration in large systems and has been implemented at many levels of description. We first review the notion of frustration from the areas of abstract logic and its uses in simple condensed matter systems. We discuss then how the frustration concept applies specifically to heteropolymers, testing folding landscape theory in computer simulations of protein models and in experimentally accessible systems. Studying the aspects of frustration averaged over many proteins provides ways to infer energy functions useful for reliable structure prediction. We discuss how frustration affects folding mechanisms. We review here how the biological functions of proteins are related to subtle local physical frustration effects and how frustration influences the appearance of metastable states, the nature of binding processes, catalysis and allosteric transitions. In this review, we also emphasize that frustration, far from being always a bad thing, is an essential feature of biomolecules that allows dynamics to be harnessed for function. In this way, we hope to illustrate how Frustration is a fundamental concept in molecular biology.

Multiple stable conformations account for reversible concentration-dependent oligomerization and autoinhibition of a metamorphic metallopeptidase

Molecular plasticity controls enzymatic activity: the native fold of a protein in a given environment is normally unique and at a global free-energy minimum. Some proteins, however, spontaneously undergo substantial fold switching to reversibly transit between defined conformers, the "metamorphic" proteins. Here, we present a minimal metamorphic, selective, and specific caseinolytic metallopeptidase, selecase, which reversibly transits between several different states of defined three-dimensional structure, which are associated with loss of enzymatic activity due to autoinhibition. The latter is triggered by sequestering the competent conformation in incompetent but structured dimers, tetramers, and octamers. This system, which is compatible with a discrete multifunnel energy landscape, affords a switch that provides a reversible mechanism of control of catalytic activity unique in nature.

Fast protein folding kinetics

Fast-folding proteins have been a major focus of computational and experimental study because they are accessible to both techniques: they are small and fast enough to be reasonably simulated with current computational power, but have dynamics slow enough to be observed with specially developed experimental techniques. This coupled study of fast-folding proteins has provided insight into the mechanisms, which allow some proteins to find their native conformation well <1 ms and has uncovered examples of theoretically predicted phenomena such as downhill folding. The study of fast folders also informs our understanding of even 'slow' folding processes: fast folders are small; relatively simple protein domains and the principles that govern their folding also govern the folding of more complex systems. This review summarizes the major theoretical and experimental techniques used to study fast-folding proteins and provides an overview of the major findings of fast-folding research. Finally, we examine the themes that have emerged from studying fast folders and briefly summarize their application to protein folding in general, as well as some work that is left to do.

Computational and theoretical methods for protein folding

A computational approach is essential whenever the complexity of the process under study is such that direct theoretical or experimental approaches are not viable. This is the case for protein folding, for which a significant amount of data are being collected. This paper reports on the essential role of in silico methods and the unprecedented interplay of computational and theoretical approaches, which is a defining point of the interdisciplinary investigations of the protein folding process. Besides giving an overview of the available computational methods and tools, we argue that computation plays not merely an ancillary role but has a more constructive function in that computational work may precede theory and experiments. More precisely, computation can provide the primary conceptual clues to inspire subsequent theoretical and experimental work even in a case where no preexisting evidence or theoretical frameworks are available. This is cogently manifested in the application of machine learning methods to come to grips with the folding dynamics. These close relationships suggested complementing the review of computational methods within the appropriate theoretical context to provide a self-contained outlook of the basic concepts that have converged into a unified description of folding and have grown in a synergic relationship with their computational counterpart. Finally, the advantages and limitations of current computational methodologies are discussed to show how the smart analysis of large amounts of data and the development of more effective algorithms can improve our understanding of protein folding.

A nanobody binding to non-amyloidogenic regions of the protein human lysozyme enhances partial unfolding but inhibits amyloid fibril formation

We report the effects of the interaction of two camelid antibody fragments, generally called nanobodies, namely cAb-HuL5 and a stabilized and more aggregation-resistant variant cAb-HuL5G obtained by protein engineering, on the properties of two amyloidogenic variants of human lysozyme, I56T and D67H, whose deposition in vital organs including the liver, kidney, and spleen is associated with a familial non-neuropathic systemic amyloidosis. Both NMR spectroscopy and X-ray crystallographic studies reveal that cAb-HuL5 binds to the α-domain, one of the two lobes of the native lysozyme structure. The binding of cAb-HuL5/cAb-HuL5G strongly inhibits fibril formation by the amyloidogenic variants; it does not, however, suppress the locally transient cooperative unfolding transitions, characteristic of these variants, in which the β-domain and the C-helix unfold and which represents key early intermediate species in the formation of amyloid fibrils. Therefore, unlike two other nanobodies previously described, cAb-HuL5/cAb-HuL5G does not inhibit fibril formation via the restoration of the global cooperativity of the native structure of the lysozyme variants to that characteristic of the wild-type protein. Instead, it inhibits a subsequent step in the assembly of the fibrils, involving the unfolding and structural reorganization of the α-domain. These results show that nanobodies can protect against the formation of pathogenic aggregates at different stages in the structural transition of a protein from the soluble native state into amyloid fibrils, illustrating their value as structural probes to study the molecular mechanisms of amyloid fibril formation. Combined with their amenability to protein engineering techniques to improve their stability and solubility, these findings support the suggestion that nanobodies can potentially be developed as therapeutics to combat protein misfolding diseases.

Detecting repetitions and periodicities in proteins by tiling the structural space

The notion of energy landscapes provides conceptual tools for understanding the complexities of protein folding and function. Energy landscape theory indicates that it is much easier to find sequences that satisfy the “Principle of Minimal Frustration” when the folded structure is symmetric (Wolynes, P. G. Symmetry and the Energy Landscapes of Biomolecules. Proc. Natl. Acad. Sci. U.S.A.1996, 93, 14249–14255). Similarly, repeats and structural mosaics may be fundamentally related to landscapes with multiple embedded funnels. Here we present analytical tools to detect and compare structural repetitions in protein molecules. By an exhaustive analysis of the distribution of structural repeats using a robust metric, we define those portions of a protein molecule that best describe the overall structure as a tessellation of basic units. The patterns produced by such tessellations provide intuitive representations of the repeating regions and their association toward higher order arrangements. We find that some protein architectures can be described as nearly periodic, while in others clear separations between repetitions exist. Since the method is independent of amino acid sequence information, we can identify structural units that can be encoded by a variety of distinct amino acid sequences.

Elements of coevolution in biological sequences

Studies of coevolution of amino acids within and between proteins have revealed two types of coevolving units: coevolving contacts, which are pairs of amino acids distant along the sequence but in contact in the three-dimensional structure, and sectors, which are larger groups of structurally connected amino acids that underlie the biochemical properties of proteins. By reconciling two approaches for analyzing correlations in multiple sequence alignments, we link these two findings together and with coevolving units of intermediate size, called "sectons," which are shown to provide additional information. By extending the analysis to the co-occurrence of orthologous genes in bacterial genomes, we also show that the methods and results are general and relevant beyond protein structures.

Mutational effects on the folding dynamics of a minimized hairpin

The fold stabilities and folding dynamics of a series of mutants of a model hairpin, KTW-NPATGK-WTE (HP7), are reported. The parent system and the corresponding DPATGK loop species display submicrosecond folding time constants. The mutational studies revealed that ultrafast folding requires both some prestructuring of the loop and a favorable interaction between the chain termini in the transition state. In the case of YY-DPETGT-WY, another submicrosecond folding species [Davis, C. M., Xiao, S., Raleigh, D. P., and Dyer, R. B. (2012) J. Am. Chem. Soc. 134, 14476-14482], a hydrophobic cluster provides the latter. In the case of HP7, the Coulombic interaction between the terminal NH3(+) and CO2(-) units provides this; a C-terminal Glu to amidated Ala mutation results in a 5-fold retardation of the folding rate. The effects of mutations within the reversing loop indicate the balance between loop flexibility (favoring fast conformational searching) and turn formation in the unfolded state is a major factor in determining the folding dynamics. The -NAAAKX- loops examined display no detectable turn formation propensity in other hairpin constructs but do result in stable analogues of HP7. Peptide KTW-NAAAKK-WTE displays the same fold stability as HP7, but both the folding and unfolding time constants are greater by a factor of 20.

C-terminal turn stability determines assembly differences between Aβ40 and Aβ42

Oligomerization of the amyloid β-protein (Aβ) is a seminal event in Alzheimer's disease. Aβ42, which is only two amino acids longer than Aβ40, is particularly pathogenic. Why this is so has not been elucidated fully. We report here results of computational and experimental studies revealing a C-terminal turn at Val36-Gly37 in Aβ42 that is not present in Aβ40. The dihedral angles of residues 36 and 37 in an Ile31-Ala42 peptide were consistent with β-turns, and a β-hairpin-like structure was indeed observed that was stabilized by hydrogen bonds and by hydrophobic interactions between residues 31-35 and residues 38-42. In contrast, Aβ(31-40) mainly existed as a statistical coil. To study the system experimentally, we chemically synthesized Aβ peptides containing amino acid substitutions designed to stabilize or destabilize the hairpin. The triple substitution Gly33Val-Val36Pro-Gly38Val ("VPV") facilitated Aβ42 hexamer and nonamer formation, while inhibiting formation of classical amyloid-type fibrils. These assemblies were as toxic as were assemblies from wild-type Aβ42. When substituted into Aβ40, the VPV substitution caused the peptide to oligomerize similarly to Aβ42. The modified Aβ40 was significantly more toxic than Aβ40. The double substitution d-Pro36-l-Pro37 abolished hexamer and dodecamer formation by Aβ42 and produced an oligomer size distribution similar to that of Aβ40. Our data suggest that the Val36-Gly37 turn could be the sine qua non of Aβ42. If true, this structure would be an exceptionally important therapeutic target.

Protein fragments: functional and structural roles of their coevolution networks

Small protein fragments, and not just residues, can be used as basic building blocks to reconstruct networks of coevolved amino acids in proteins. Fragments often enter in physical contact one with the other and play a major biological role in the protein. The nature of these interactions might be multiple and spans beyond binding specificity, allosteric regulation and folding constraints. Indeed, coevolving fragments are indicators of important information explaining folding intermediates, peptide assembly, key mutations with known roles in genetic diseases, distinguished subfamily-dependent motifs and differentiated evolutionary pressures on protein regions. Coevolution analysis detects networks of fragments interaction and highlights a high order organization of fragments demonstrating the importance of studying at a deeper level this structure. We demonstrate that it can be applied to protein families that are highly conserved or represented by few sequences, enlarging in this manner, the class of proteins where coevolution analysis can be performed and making large-scale coevolution studies a feasible goal.

Thermodynamics of protein folding using a modified Wako-Saitô-Muñoz-Eaton model

Herein, we propose a modified version of the Wako-Saitô-Muñoz-Eaton (WSME) model. The proposed model introduces an empirical temperature parameter for the hypothetical structural units (i.e., foldons) in proteins to include site-dependent thermodynamic behavior. The thermodynamics for both our proposed model and the original WSME model were investigated. For a system with beta-hairpin topology, a mathematical treatment (contact-pair treatment) to facilitate the calculation of its partition function was developed. The results show that the proposed model provides better insight into the site-dependent thermodynamic behavior of the system, compared with the original WSME model. From this site-dependent point of view, the relationship between probe-dependent experimental results and model's thermodynamic predictions can be explained. The model allows for suggesting a general principle to identify foldon behavior. We also find that the backbone hydrogen bonds may play a role of structural constraints in modulating the cooperative system. Thus, our study may contribute to the understanding of the fundamental principles for the thermodynamics of protein folding.

Selective constraint on human pre-mRNA splicing by protein structural properties

Alternative splicing (AS) is a major mechanism of increasing proteome diversity in complex organisms. Different AS transcript isoforms may be translated into peptide sequences of significantly different lengths and amino acid compositions. One important question, then, is how AS is constrained by protein structural requirements while peptide sequences may be significantly changed in AS events. Here, we address this issue by examining whether the intactness of three-dimensional protein structural units (compact units in protein structures, namely protein units [PUs]) tends to be preserved in AS events in human. We show that PUs tend to occur in constitutively spliced exons and to overlap constitutive exon boundaries. Furthermore, when PUs are located at the boundaries between two alternatively spliced exons (ASEs), these neighboring ASEs tend to co-occur in different transcript isoforms. In addition, such PU-spanned ASE pairs tend to have a higher frequency of being included in transcript isoforms. ASE regions that overlap with PUs also have lower nonsynonymous-to-synonymous substitution rate ratios than those that do not overlap with PUs, indicating stronger negative selection pressure in PU-overlapped ASE regions. Of note, we show that PUs have protein domain- and structural orderness-independent effects on messenger RNA (mRNA) splicing. Overall, our results suggest that fine-scale protein structural requirements have significant influences on the splicing patterns of human mRNAs.

Quantifying protein modularity and evolvability: a comparison of different techniques

Modularity increases evolvability by reducing constraints on adaptation and by allowing preexisting parts to function in new contexts for novel uses. Protein evolution provides an excellent context to study the causes and consequences of biological modularity. In order to address such questions, however, an index for protein modularity is necessary. This paper proposes a simple index for protein modularity-"module density"-which is the number of evolutionarily independent modules that compose a protein divided by the number of amino acids in the protein. The decomposition of proteins into constituent modules can be accomplished by either of two classes of methods. The first class of methods relies on "suppositional" criteria to assign amino acids to modules, whereas the second class of methods relies on "coevolutionary" criteria for this task. One simple and practical method from the first class consists of approximating the number of modules in a protein as the number of regular secondary structure elements (i.e., helices and sheets). Methods based on coevolutionary criteria require more elaborate data, but they have the advantage of being able to specify modules without prior assumptions about why they exist. Given the increasing availability of datasets sampling protein mutational spectra (e.g., from comparative genomics, experimental evolution, and computational prediction), methods based on coevolutionary criteria will likely become more promising in the near future. The ability to meaningfully quantify protein modularity via simple indices has the potential to aid future efforts to understand protein evolutionary rate determinants, improve molecular evolution models and engineer novel proteins.

Beta-strand interfaces of non-dimeric protein oligomers are characterized by scattered charged residue patterns

Protein oligomers are formed either permanently, transiently or even by default. The protein chains are associated through intermolecular interactions constituting the protein interface. The protein interfaces of 40 soluble protein oligomers of stœchiometries above two are investigated using a quantitative and qualitative methodology, which analyzes the x-ray structures of the protein oligomers and considers their interfaces as interaction networks. The protein oligomers of the dataset share the same geometry of interface, made by the association of two individual β-strands (β-interfaces), but are otherwise unrelated. The results show that the β-interfaces are made of two interdigitated interaction networks. One of them involves interactions between main chain atoms (backbone network) while the other involves interactions between side chain and backbone atoms or between only side chain atoms (side chain network). Each one has its own characteristics which can be associated to a distinct role. The secondary structure of the β-interfaces is implemented through the backbone networks which are enriched with the hydrophobic amino acids favored in intramolecular β-sheets (MCWIV). The intermolecular specificity is provided by the side chain networks via positioning different types of charged residues at the extremities (arginine) and in the middle (glutamic acid and histidine) of the interface. Such charge distribution helps discriminating between sequences of intermolecular β-strands, of intramolecular β-strands and of β-strands forming β-amyloid fibers. This might open new venues for drug designs and predictive tool developments. Moreover, the β-strands of the cholera toxin B subunit interface, when produced individually as synthetic peptides, are capable of inhibiting the assembly of the toxin into pentamers. Thus, their sequences contain the features necessary for a β-interface formation. Such β-strands could be considered as ‘assemblons’, independent associating units, by homology to the foldons (independent folding unit). Such property would be extremely valuable in term of assembly inhibitory drug development.

OneG: a computational tool for predicting cryptic intermediates in the unfolding kinetics of proteins under native conditions

Understanding the relationships between conformations of proteins and their stabilities is one key to address the protein folding paradigm. The free energy change (ΔG) of unfolding reactions of proteins is measured by traditional denaturation methods and native hydrogen-deuterium (H/D) exchange methods. However, the free energy of unfolding (ΔG(U)) and the free energy of exchange (ΔG(HX)) of proteins are not in good agreement, though the experimental conditions of both methods are well matching to each other. The anomaly is due to any one or combinations of the following reasons: (i) effects of cis-trans proline isomerisation under equilibrium unfolding reactions of proteins (ii) inappropriateness in accounting the baselines of melting curves (iii) presence of cryptic intermediates, which may elude the melting curve analysis and (iv) existence of higher energy metastable states in the H/D exchange reactions of proteins. Herein, we have developed a novel computational tool, OneG, which accounts the discrepancy between ΔG(U) and ΔG(HX) of proteins by systematically accounting all the four factors mentioned above. The program is fully automated and requires four inputs: three-dimensional structures of proteins, ΔG(U), ΔG(U)(*) and residue-specific ΔG(HX) determined under EX2-exchange conditions in the absence of denaturants. The robustness of the program has been validated using experimental data available for proteins such as cytochrome c and apocytochrome b(562) and the data analyses revealed that cryptic intermediates of the proteins detected by the experimental methods and the cryptic intermediates predicted by the OneG for those proteins were in good agreement. Furthermore, using OneG, we have shown possible existence of cryptic intermediates and metastable states in the unfolding pathways of cardiotoxin III and cobrotoxin, respectively, which are homologous proteins. The unique application of the program to map the unfolding pathways of proteins under native conditions have been brought into fore and the program is publicly available at http://sblab.sastra.edu/oneg.html.

Nonplanar peptide bonds in proteins are common and conserved but not biased toward active sites

The planarity of peptide bonds is an assumption that underlies decades of theoretical modeling of proteins. Peptide bonds strongly deviating from planarity are considered very rare features of protein structure that occur for functional reasons. Here, empirical analyses of atomic-resolution protein structures reveal that trans peptide groups can vary by more than 25° from planarity and that the true extent of nonplanarity is underestimated even in 1.2 Å resolution structures. Analyses as a function of the ϕ,ψ-backbone dihedral angles show that the expected value deviates by ± 8° from planar as a systematic function of conformation, but that the large majority of variation in planarity depends on tertiary effects. Furthermore, we show that those peptide bonds in proteins that are most nonplanar, deviating by over 20° from planarity, are not strongly associated with active sites. Instead, highly nonplanar peptides are simply integral components of protein structure related to local and tertiary structural features that tend to be conserved among homologs. To account for the systematic ϕ,ψ-dependent component of nonplanarity, we present a conformation-dependent library that can be used in crystallographic refinement and predictive protein modeling.

Trimming down a protein structure to its bare foldons: spatial organization of the cooperative unit

Folding of the ribosomal protein S6 is a malleable process controlled by two competing, and partly overlapping, folding nuclei. Together, these nuclei extend over most of the S6 structure, except the edge strand β2, which is consistently missing in the folding transition states; despite being part of the S6 four-stranded sheet, β2 seems not to be part of the cooperative unit of the protein. The question is then whether β2 can be removed from the S6 structure without compromising folding cooperativity or native state integrity. To investigate this, we constructed a truncated variant of S6 lacking β2, reducing the size of the protein from 96 to 76 residues (S6(Δβ2)). The new S6 variant expresses well in Escherichia coli and has a well dispersed heteronuclear single quantum correlation spectrum and a perfectly wild-type-like crystal structure, but with a smaller three-stranded β-sheet. Moreover, S6(Δβ2) displays an archetypical v-shaped chevron plot with decreased slope of the unfolding limb, as expected from a protein with maintained folding cooperativity and reduced size. The results support the notion that foldons, as defined by the structural distribution of the folding nuclei, represent a property-based level of hierarchy in the build-up of larger protein structures and suggest that the role of β2 in S6 is mainly in intermolecular binding, consistent with the position of this strand in the ribosomal assembly.