Building Blocks,Hinge-Bending Motions and Protein Topology

Abstract

Here we show that the locations of molecular hinges in protein structures fall between building block elements. Building blocks are fragments of the protein chain which constitute local minima. These elements fold first. In the next step they associate through a combinatorial assembly process. While chain-linked building blocks may be expected to trial-associate first, if unstable, alternate more stable associations will take place. Hence, we would expect that molecular hinges will be at such inter-building block locations, or at the less stable, ‘unassigned’ regions.

On the other hand, hinge-bending motions are well known to be critical for protein function. Hence, protein folding and protein function are evolutionarily related. Further, the pathways through which proteins attain their three dimensional folds are determined by protein topology. However, at the same time the locations of the hinges, and hinge-bending motions are also an outcome of protein topology. Thus, protein folding and function appear coupled, and relate to protein topology. Here we provide some results illustrating such a relationship.     

Hierarchical protein folding pathways: a computational study of protein fragments

We have previously presented a building block folding model. The model postulates that protein folding is a hierarchical top-down process. The basic unit from which a fold is constructed, referred to as a hydrophobic folding unit, is the outcome of combinatorial assembly of a set of "building blocks." Results obtained by the computational cutting procedure yield fragments that are in agreement with those obtained experimentally by limited proteolysis. Here we show that as expected, proteins from the same family give very similar building blocks. However, different proteins can also give building blocks that are similar in structure. In such cases the building blocks differ in sequence, stability, contacts with other building blocks, and in their 3D locations in the protein structure. This result, which we have repeatedly observed in many cases, leads us to conclude that while a building block is influenced by its environment, nevertheless, it can be viewed as a stand-alone unit. For small-sized building blocks existing in multiple conformations, interactions with sister building blocks in the protein will increase the population time of the native conformer. With this conclusion in hand, it is possible to develop an algorithm that predicts the building block assignment of a protein sequence whose structure is unknown. Toward this goal, we have created sequentially nonredundant databases of building block sequences. A protein sequence can be aligned against these, in order to be matched to a set of potential building blocks.     

Binding and folding: in search of intramolecular chaperone-like building block fragments

We propose an intramolecular chaperone which catalyzes folding and neither dissociates nor is cleaved. This uncleaved foldase is an intramolecular chain-linked chaperone, which constitutes a critical building block of the structure. Macroscopically, all molecular chaperones facilitate folding reactions and manifest similar energy landscapes. However, microscopically they differ. While intermolecular chaperones catalyze folding by unfolding misfolded conformations or prevent misfolding, the chain-linked cleaved (proregion) and uncleaved intramolecular chaperone-like building blocks suggested here, catalyze folding by binding to, stabilizing and increasing the populations of native conformations of adjacent building block fragments. In both, the more stable the intramolecular chaperone fragment region, the faster is the folding rate. Hence, mechanistically, intramolecular chaperones and chaperone-like segments are similar. Both play a dual role, in folding and in protein function. However, while the functional role of the proregions is inhibitory, necessitating their cleavage, the function of the uncleaved intramolecular chaperone-like building blocks does not require their subsequent removal. On the contrary, it requires that they remain in the structure. This may lead to the difference in the type of control they are under: proteins folding with the assistance of the proregion have been shown to be under kinetic control. It has been suggested that kinetically controlled folding reactions, with the proregion catalyst removed, lend longevity under harsh conditions. On the other hand, proteins with uncleaved intramolecular chaperone-like building blocks, with their 'foldases' still attached, are largely under thermodynamic control, consistent with the control observed in most protein folding reactions. We propose that an uncleaved intramolecular chaperone-like fragment occurs frequently in proteins. We further propose that such proteins would be prone to changing conditions and in particular, to mutations in this critical building block region. We describe the features qualifying it for its proposed chaperone-like role, compare it with inter- and intramolecular chaperones and review current literature in this light. We further propose a mechanism showing how it lowers the barrier heights, leading to faster folding reaction rates. Since these fragments constitute an intergal part of the protein structure, we call these critical building blocks intramolecular, chaperone-like fragments, to clarify, distinguish and adhere to the definition of the transiently associating chaperones. The new mechanism presented here differs from the concept of 'folding nuclei'. While the concept of folding nuclei focuses on a non-sequential distribution of the folding information along the entire protein chain, the chaperone-like building block fragments proposition focuses on a segmental distribution of the folding information. This segmental distribution controls the distributions of the populations throughout the hierarchical folding processes.     

Protein folding and function: the N-terminal fragment in adenylate kinase

Three-dimensional protein folds range from simple to highly complex architectures. In complex folds, some building block fragments are more important for correct protein folding than others. Such fragments are typically buried in the protein core and mediate interactions between other fragments. Here we present an automated, surface area-based algorithm that is able to indicate which, among all local elements of the structure, is critical for the formation of the native fold, and apply it to structurally well-characterized proteins. In particular, we focus on adenylate kinase. The fragment containing the phosphate binding, P-loop (the "giant anion hole") flanked by a beta-strand and an alpha-helix near the N-terminus, is identified as a critical building block. This building block shows a high degree of sequence and structural conservation in all adenylate kinases. The results of our molecular dynamics simulations are consistent with this identification. In its absence, the protein flips to a stable, non-native state. In this misfolded conformation, the other local elements of the structure are in their native-like conformations; however, their association is non-native. Furthermore, this element is critically important for the function of the enzyme, coupling folding, and function.     

Potential folding-function interrelationship in proteins

The possibility is addressed that protein folding and function may be related via regions that are critical for both folding and function. This approach is based on the building blocks folding model that describes protein folding as binding events of conformationally fluctuating building blocks. Within these, we identify building block fragments that are critical for achieving the native fold. A library of such critical building blocks (CBBs) is constructed. Then, it is asked whether the functionally important residues fall in these CBB fragments. We find that for over two-thirds of the proteins in our library with available functional information, the catalytic or binding site residues lie within the CBB regions. From the evolutionary standpoint, a folding-function relationship is advantageous, since the need to guard against mutations is limited to one region. Furthermore, conformationally similar CBBs are found in globally unrelated proteins with different functions. Hence, substituting CBBs may lead to designed proteins with altered functions. We further find that the CBBs in our library are conformationally unstable.     

The building block folding model and the kinetics of protein folding.

Here we show that qualitatively, the building blocks folding model accounts for three-state versus the two-state protein folding. Additionally, it is consistent with the faster versus slower folding rates of the two-state proteins. Specifically, we illustrate that the building blocks size, their mode of associations in the native structure, the number of ways they can combinatorially assemble, their population times and the way they are split in the iterative, step-by-step structural dissection which yields the anatomy trees, explain a broad range of folding rates. We further show that proteins with similar general topologies may have different folding pathways, and hence different folding rates. On the other hand, the effect of mutations resembles that of changes in conditions, shifting the population times and hence the energy landscapes. Hence, together with the secondary structure type and the extent of local versus non-local interactions, a coherent, consistent rationale for folding kinetics can be outlined, in agreement with experimental results. Given the native structure of a protein, these guidelines enable a qualitative prediction of the folding kinetics. We further describe these in the context of the protein folding energy landscape. Quantitatively, in principle, the diffusion-collision model for the building block association can be used. However, the folding rates of the building blocks and traps in their formation and association, need to be considered.     

Flexible docking allowing induced fit in proteins: Insights from an open to closed conformational isomers

Here we dock a ligand onto a receptor surface allowing hinge-bending domain/substructural movements. Our approach mimics and manifests induced fit in molecular recognition. All angular rotations are allowed on the one hand, while a conformational space search is avoided on the other. Rather than dock each of the molecular parts separately with subsequent reconstruction of the consistently docked molecules, all parts are docked simultaneously while still utilizing the position of the hinge from the start. Like pliers closing on a screw, the receptor automatically closes on its ligand in the best surface-matching way. Movements are allowed either in the ligand or in the larger receptor, hence reproducing induced molecular fit. Hinge bending movements are frequently observed when molecules associate. There are numerous examples of open versus closed conformations taking place upon binding. Such movements are observed when the substrate binds to its respective enzyme. In particular, such movements are of interest in allosteric enzymes. The movements can involve entire domains, subdomains, loops, (other) secondary structure elements, or between any groups of atoms connected by flexible joints. We have implemented the hinges at points and at bonds. By allowing 3-dimensional (3-D) rotation at the hinge, several rotations about (consecutive or nearby) bonds are implicitly taken into account. Alternatively, if required, the point rotation can be restricted to bond rotation. Here we illustrate this hinge-bending docking approach and the insight into flexibility it provides on a complex of the calmodulin with its M13 ligand, positioning the hinges either in the ligand or in the larger receptor. This automated and efficient method is adapted from computer vision and robotics. It enables utilizing entire molecular surfaces rather than focusing a priori on active sites. Hence, allows attaining the overall optimally matching surfaces, the extent and type of motions which are involved. Here we do not treat the conformational flexibility of side-chains or of very small pieces of the molecules. Therefore, currently available methods addressing these issues and the method presented here, are complementary to each other, expanding the repertoire of computational docking tools foreseen to aid in studies of recognition, conformational flexibility and drug design. Proteins 32:159–174, 1998. © 1998 Wiley-Liss, Inc.     

Folding funnels and conformational transitions via hinge-bending motions

In this article we focus on presenting a broad range of examples illustrating low-energy transitions via hinge-bending motions. The examples are divided according to the type of hinge-bending involved; namely, motions involving fragments of the protein chains, hinge-bending motions involving protein domains, and hinge-bending motions between the covalently unconnected subunits. We further make a distinction between allosterically and nonallosterically regulated proteins. These transitions are discussed within the general framework of folding and binding funnels. We propose that the conformers manifesting such swiveling motions are not the outcome of “induced fit” binding mechanism; instead, molecules exist in an ensemble of conformations that are in equilibrium in solution. These ensembles, which populate the bottoms of the funnels,a priori contain both the “open” and the “closed” conformational isomers. Furthermore, we argue that there are no fundamental differences among the physical principles behind the folding and binding funnels. Hence, there is no basic difference between funnels depicting ensembles of conformers of single molecules with fragment, or domain motions, as compared to subunits in multimeric quaternary structures, also showing such conformational transitions. The difference relates only to the size and complexity of the system. The larger the system, the more complex its corresponding fused funnel(s). In particular, funnels associated with allosterically regulated proteins are expected to be more complicated, because allostery is frequently involved with movements between subunits, and consequently is often observed in multichain and multimolecular complexes. This review centers on the critical role played by flexibility and conformational fluctuations in enzyme activity. Internal motions that extend over different time scales and with different amplitudes are known to be essential for the catalytic cycle. The conformational change observed in enzyme-substrate complexes as compared to the unbound enzyme state, and in particular the hinge-bending motions observed in enzymes with two domains, have a substantial effect on the enzymatic catalytic activity. The examples we review span the lipolytic enzymes that are particularly interesting, owing to their activation at the water-oil interface; an allosterically controlled dehydrogenase (lactate dehydrogenase); a DNA methyltransferase, with a covalently-bound intermediate; large-scale flexible loop motions in a glycolytic enzyme (TIM); domain motion in PGK, an enzyme which is essential in most cells, both for ATP generation in aerobes and for fermentation in anaerobes; adenylate kinase, showing large conformational changes, owing to their need to shield their catalytic centers from water; a calcium-binding protein (calmodulin), involved in a wide range of cellular calcium-dependent signaling; diphtheria toxin, whose large domain motion has been shown to yield “domain swapping” the hexameric glutamate dehydrogenase, which has been studied both in a thermophile and in a mesophile; an allosteric enzyme, showing subunit motion between the R and the T states (aspartate transcarbamoylase), and the historically well-studied lac represoor. Nonallosteric subunit transitions are also addressed with some examples (aspartate receptor andBamHI endonuclease). Hence, using this enzyme-catalysis-centered discussion, we address energy funnel landscapes of large-scale conformational transitions, rather than the faster, quasi-harmonic, thermal fluctuations.     

hdANM: a new comprehensive dynamics model for protein hinges

Hinge motions are essential for many protein functions, and their dynamics are important to understand underlying biological mechanisms. The ways that these motions are represented by various computational methods differ significantly. By focusing on a specific class of motion, we have developed a new hinge-domain anisotropic network model (hdANM) that is based on the prior identification of flexible hinges and rigid domains in the protein structure and the subsequent generation of global hinge motions. This yields a set of motions in which the relative translations and rotations of the rigid domains are modulated and controlled by the deformation of the flexible hinges, leading to a more restricted, specific view of these motions. hdANM is the first model, to our knowledge, that combines information about protein hinges and domains to model the characteristic hinge motions of a protein. The motions predicted with this new elastic network model provide important conceptual advantages for understanding the underlying biological mechanisms. As a matter of fact, the generated hinge movements are found to resemble the expected mechanisms required for the biological functions of diverse proteins. Another advantage of this model is that the domain-level coarse graining makes it significantly more computationally efficient, enabling the generation of hinge motions within even the largest molecular assemblies, such as those from cryo-electron microscopy. hdANM is also comprehensive as it can perform in the same way as the well-known protein dynamics models (anisotropic network model, rotations-translations of blocks, and nonlinear rigid block normal mode analysis), depending on the definition of flexible and rigid parts in the protein structure and on whether the motions are extrapolated in a linear or nonlinear fashion. Furthermore, our results indicate that hdANM produces more realistic motions as compared to the anisotropic network model. hdANM is an open-source software, freely available, and hosted on a user-friendly website.     

Transient, highly populated, building blocks folding model

Protein folding is a hierarchical event, in which transiently formed local structural elements assemble to yield the native conformation. In principle, multiple paths glide down the energy landscape, but, in practice, only a few of the paths are highly traveled. Here, the literature is reviewed in this light, and, particularly, a hierarchical, building block protein-folding model is presented, putting it in the context of a broad range of experimental and theoretical results published over the past few years. The model is based on two premises: First, although the local building block elements may be unstable, they nevertheless have higher population times than all alternate conformations; and, second, protein folding progresses through a combinatorial assembly of these elements. Through the binding of the most favorable building block conformers, there is a redistribution of the conformers in solution, propagating the protein-folding reaction. We describe the algorithm, and illustrate its usefulness, then we focus on its utility in assigning simple vs complex folding pathways, on chaperonin-assisted folding, on its relevance to domain-swapping processes, and on its relevance and relationship to disconnectivity graphs and tree diagrams. Considering protein folding as initiating from local transient structural elements is consistent with available experimental and theoretical results. Here, we have shown that, early in the folding process, sequential interactions are likely to take place, even if the final native fold is a complex, nonsequential one. Such a route is favorable kinetically and entropically. Through the construction of anatomy trees, the model enables derivation of the major folding pathways and their bumps, and qualitatively explains the kinetics of protein folding.     

In silico protein design by combinatorial assembly of protein building blocks

Utilizing concepts of protein building blocks, we propose a de novo computational algorithm that is similar to combinatorial shuffling experiments. Our goal is to engineer new naturally occurring folds with low homology to existing proteins. A selected protein is first partitioned into its building blocks based on their compactness, degree of isolation from the rest of the structure, and hydrophobicity. Next, the protein building blocks are substituted by fragments taken from other proteins with overall low sequence identity, but with a similar hydrophobic/hydrophilic pattern and a high structural similarity. These criteria ensure that the designed protein has a similar fold, low sequence identity, and a good hydrophobic core compared with its native counterpart. Here, we have selected two proteins for engineering, protein G B1 domain and ubiquitin. The two engineered proteins share approximately 20% and approximately 25% amino acid sequence identities with their native counterparts, respectively. The stabilities of the engineered proteins are tested by explicit water molecular dynamics simulations. The algorithm implements a strategy of designing a protein using relatively stable fragments, with a high population time. Here, we have selected the fragments by searching for local minima along the polypeptide chain using the protein building block model. Such an approach provides a new method for engineering new proteins with similar folds and low homology.     

Network analysis of protein dynamics

The network paradigm is increasingly used to describe the topology and dynamics of complex systems. Here, we review the results of the topological analysis of protein structures as molecular networks describing their small-world character, and the role of hubs and central network elements in governing enzyme activity, allosteric regulation, protein motor function, signal transduction and protein stability. We summarize available data how central network elements are enriched in active centers and ligand binding sites directing the dynamics of the entire protein. We assess the feasibility of conformational and energy networks to simplify the vast complexity of rugged energy landscapes and to predict protein folding and dynamics. Finally, we suggest that modular analysis, novel centrality measures, hierarchical representation of networks and the analysis of network dynamics will soon lead to an expansion of this field.     

Protein folding: binding of conformationally fluctuating building blocks via population selection.

Here we review different aspects of the protein folding literature. We present a broad range of observations, showing them to be consistent with a general hierarchical protein folding model. In such a model, local relatively stable, conformationally fluctuating building blocks bind through population selection, to yield the native state. The model includes several components: (1) the fluctuating building blocks that constitute local minima along the polypeptide chain, which even if unstable still possess higher population times than all alternate conformations; (2) the landscape around the bottom of the funnels; (3) the consideration that protein folding involves intramolecular recognition; (4) similar landscapes are observed for folding and for binding, and that (5) the landscape is dynamic, changing with the conditions. The model considers protein folding to be guided by native interactions. The reviewed literature includes the effects of changing the conditions, intermediates and kinetic traps, mutations, similar topologies, fragment complementation experiments, fragments and pathways, focusing on one specific well-studied example, that of the dihydrofolate reductase, chaperones, and chaperonines, in vivo vs. in vitro folding, still using the dihydrofolate example, amyloid formation, and molecular "disorder". These are consistent with the view that binding and folding are similar events, with the differences stemming from different stabilities and hence population times.     

Mechanical unfoldons as building blocks of maltose-binding protein

Identifying independently folding cores or substructures is important for understanding and assaying the structure, function and assembly of large proteins. Here, we suggest mechanical stability as a criterion to identify building blocks of the 366 amino acid maltose-binding protein (MBP). We find that MBP, when pulled at its termini, unfolds via three (meta-) stable unfolding intermediates. Consequently, the MBP structure consists of four structural blocks (unfoldons) that detach sequentially from the folded structure upon force application. We used cysteine cross-link mutations to characterize the four unfoldons structurally. We showed that many MBP constructs composed of those building blocks indeed form stably folded structures in solution. Mechanical unfoldons may provide a new tool for a systematic search for stable substructures of large proteins.     

Reducing the computational complexity of protein folding via fragment folding and assembly

Understanding, and ultimately predicting, how a 1-D protein chain reaches its native 3-D fold has been one of the most challenging problems during the last few decades. Data increasingly indicate that protein folding is a hierarchical process. Hence, the question arises as to whether we can use the hierarchical concept to reduce the practically intractable computational times. For such a scheme to work, the first step is to cut the protein sequence into fragments that form local minima on the polypeptide chain. The conformations of such fragments in solution are likely to be similar to those when the fragments are embedded in the native fold, although alternate conformations may be favored during the mutual stabilization in the combinatorial assembly process. Two elements are needed for such cutting: (1) a library of (clustered) fragments derived from known protein structures and (2) an assignment algorithm that selects optimal combinations to "cover" the protein sequence. The next two steps in hierarchical folding schemes, not addressed here, are the combinatorial assembly of the fragments and finally, optimization of the obtained conformations. Here, we address the first step in a hierarchical protein-folding scheme. The input is a target protein sequence and a library of fragments created by clustering building blocks that were generated by cutting all protein structures. The output is a set of cutout fragments. We briefly outline a graph theoretic algorithm that automatically assigns building blocks to the target sequence, and we describe a sample of the results we have obtained.     

Proline-induced hinges in transmembrane helices: possible roles in ion channel gating

A number of ion channels contain transmembrane (TM) alpha-helices that contain proline-induced molecular hinges. These TM helices include the channel-forming peptide alamethicin (Alm), the S6 helix from voltage-gated potassium (Kv) channels, and the D5 helix from voltage-gated chloride (CLC) channels. For both Alm and KvS6, experimental data implicate hinge-bending motions of the helix in an aspect of channel gating. We have compared the hinge-bending motions of these TM helices in bilayer-like environments by multi-nanosecond MD simulations in an attempt to describe motions of these helices that may underlie possible modes of channel gating. Alm is an alpha-helical channel-forming peptide, which contains a central kink associated with a Gly-x-x-Pro motif in its sequence. Simulations of Alm in a TM orientation for 10 ns in an octane slab indicate that the Gly-x-x-Pro motif acts as a molecular hinge. The S6 helix from Shaker Kv channels contains a Pro-Val-Pro motif. Modeling studies and recent experimental data suggest that the KvS6 helix may be kinked in the vicinity of this motif. Simulations (10 ns) of an isolated KvS6 helix in an octane slab and in a POPC bilayer reveal hinge-bending motions. A pattern-matching approach was used to search for possible hinge-bending motifs in the TM helices of other ion channel proteins. This uncovered a conserved Gly-x-Pro motif in TM helix D5 of CLC channels. MD simulations of a model of hCLC1-D5 spanning an octane slab suggest that this channel also contains a TM helix that undergoes hinge-bending motion. In conclusion, our simulations suggest a model in which hinge-bending motions of TM helices may play a functional role in the gating mechanisms of several different families of ion channels.     

The blind search for the closed states of hinge-bending proteins

The hinge-bending proteins provide the most pronounced example of the large-amplitude slow motions in a number of proteins, which are critical for their functioning. They are often used as the test ground for developing novel approaches to the simulation of slow protein dynamics. In the present study, we present the algorithm, which allows physically-consistent simulations of slow protein dynamics in globular proteins. Our algorithm is based on the hierarchical clustering of the correlation patterns (HCCP) technique of domain identification, which allows subdividing the protein into the hierarchy of the rigid-body-like clusters. The clusters are allowed to rotate relative to one another on the automatically identified hinges. The clusters are found in the course of automated, objective and well-tested procedure. In the present communication, our technique is applied to 10 hinge-bending proteins. For each of the proteins, we performed the blind search for the closed conformation, staring from the open one. Resulting closed conformations are compared with the closed states observed in crystallographic structures. It is shown that our technique produces realistic closed conformations for 8 out of 10 studied proteins. This demonstrates that HCCP technique can be used for finding alternative protein conformations and for sampling the slow motions in proteins.     

Distinguishing between sequential and nonsequentially folded proteins: implications for folding and misfolding.

We describe here an algorithm for distinguishing sequential from nonsequentially folding proteins. Several experiments have recently suggested that most of the proteins that are synthesized in the eukaryotic cell may fold sequentially. This proposed folding mechanism in vivo is particularly advantageous to the organism. In the absence of chaperones, the probability that a sequentially folding protein will misfold is reduced significantly. The problem we address here is devising a procedure that would differentiate between the two types of folding patterns. Footprints of sequential folding may be found in structures where consecutive fragments of the chain interact with each other. In such cases, the folding complexity may be viewed as being lower. On the other hand, higher folding complexity suggests that at least a portion of the polypeptide backbone folds back upon itself to form three-dimensional (3D) interactions with noncontiguous portion(s) of the chain. Hence, we look at the mechanism of folding of the molecule via analysis of its complexity, that is, through the 3D interactions formed by contiguous segments on the polypeptide chain. To computationally splice the structure into consecutively interacting fragments, we either cut it into compact hydrophobic folding units or into a set of hypothetical, transient, highly populated, contiguous fragments ("building blocks" of the structure). In sequential folding, successive building blocks interact with each other from the amino to the carboxy terminus of the polypeptide chain. Consequently, the results of the parsing differentiate between sequentially vs. nonsequentially folded chains. The automated assessment of the folding complexity provides insight into both the likelihood of misfolding and the kinetic folding rate of the given protein. In terms of the funnel free energy landscape theory, a protein that truly follows the mechanism of sequential folding, in principle, encounters smoother free energy barriers. A simple sequentially folded protein should, therefore, be less error prone and fold faster than a protein with a complex folding pattern.     

Effective protein folding in simple random search

Here I show the following facts using a simple random search model without including any sophisticated energy term. As the size of elements exponentially affects the efficiency of folding, it can be remarkably enhanced by dividing the elements into small blocks. As the folding of the blocks is completely independent, the total folding time can be reduced to the folding time of the single hardest block. This result gives the simplest and most straightforward answer to the Levinthal paradox.     

StoneHinge: Hinge prediction by network analysis of individual protein structures

Hinge motions are important for molecular recognition, and knowledge of their location can guide the sampling of protein conformations for docking. Predicting domains and intervening hinges is also important for identifying structurally self‐determinate units and anticipating the influence of mutations on protein flexibility and stability. Here we present StoneHinge, a novel approach for predicting hinges between domains using input from two complementary analyses of noncovalent bond networks: StoneHingeP, which identifies domain‐hinge‐domain signatures in ProFlex constraint counting results, and StoneHingeD, which does the same for DomDecomp Gaussian network analyses. Predictions for the two methods are compared to hinges defined in the literature and by visual inspection of interpolated motions between conformations in a series of proteins. For StoneHingeP, all the predicted hinges agree with hinge sites reported in the literature or observed visually, although some predictions include extra residues. Furthermore, no hinges are predicted in six hinge‐free proteins. On the other hand, StoneHingeD tends to overpredict the number of hinges, while accurately pinpointing hinge locations. By determining the consensus of their results, StoneHinge improves the specificity, predicting 11 of 13 hinges found both visually and in the literature for nine different open protein structures, and making no false‐positive predictions. By comparison, a popular hinge detection method that requires knowledge of both the open and closed conformations finds 10 of the 13 known hinges, while predicting four additional, false hinges.