Principles of assembly reveal a periodic table of protein complexes

Monitoring Metallo-Macromolecular Assembly Equilibria by Ion Mobility-Mass Spectrometry

Ion mobility-mass spectrometry (IM-MS) allows the separation of isomeric and isobaric species on the basis of their size, shape, and charge. The fast separation timescale (ms) and high sensitivity of these measurements make IM-MS an ideally suitable method for monitoring changes in macromolecular structure, such as those occurring in interconverting terpyridine-based metallosupramolecular self-assemblies. IM-MS is used to verify the elemental composition (size) and architecture (shape) of the self-assembled products. Additionally, this article demonstrates its applicability to the elucidation of concentration-driven association-dissociation (fusion-fission) equilibria between isobaric structures. IM-MS enables both quantitative separation and identification of the interconverting complexes as well as derivation of the corresponding equilibrium constants (i.e., thermodynamic information) from extracted IM-MS abundance data.

Design of metalloproteins and novel protein folds using variational autoencoders

The design of novel proteins has many applications but remains an attritional process with success in isolated cases. Meanwhile, deep learning technologies have exploded in popularity in recent years and are increasingly applicable to biology due to the rise in available data. We attempt to link protein design and deep learning by using variational autoencoders to generate protein sequences conditioned on desired properties. Potential copper and calcium binding sites are added to non-metal binding proteins without human intervention and compared to a hidden Markov model. In another use case, a grammar of protein structures is developed and used to produce sequences for a novel protein topology. One candidate structure is found to be stable by molecular dynamics simulation. The ability of our model to confine the vast search space of protein sequences and to scale easily has the potential to assist in a variety of protein design tasks.

Maintaining and breaking symmetry in homomeric coiled-coil assemblies

In coiled-coil (CC) protein structures α-helices wrap around one another to form rope-like assemblies. Most natural and designed CCs have two–four helices and cyclic (C_n) or dihedral (D_n) symmetry. Increasingly, CCs with five or more helices are being reported. A subset of these higher-order CCs is of interest as they have accessible central channels that can be functionalised; they are α-helical barrels. These extended cavities are surprising given the drive to maximise buried hydrophobic surfaces during protein folding and assembly in water. Here, we show that α-helical barrels can be maintained by the strategic placement of β-branched aliphatic residues lining the lumen. Otherwise, the structures collapse or adjust to give more-complex multi-helix assemblies without C_n or D_n symmetry. Nonetheless, the structural hallmark of CCs—namely, knobs-into-holes packing of side chains between helices—is maintained leading to classes of CCs hitherto unobserved in nature or accessed by design.

Higher order coiled coils with five or more helices can form α-helical barrels. Here the authors show that placing β-branched aliphatic residues along the lumen yields stable and open α-helical barrels, which is of interest for the rational design of functional proteins; whereas, the absence of β-branched side chains leads to unusual low-symmetry α-helical bundles.

DynBench3D, a Web-Resource to Dynamically Generate Benchmark Sets of Large Heteromeric Protein Complexes

Multi-protein machines are responsible for most cellular tasks, and many efforts have been invested in the systematic identification and characterization of thousands of these macromolecular assemblies. However, unfortunately, the (quasi) atomic details necessary to understand their function are available only for a tiny fraction of the known complexes. The computational biology community is developing strategies to integrate structural data of different nature, from electron microscopy to X-ray crystallography, to model large molecular machines, as it has been done for individual proteins and interactions with remarkable success. However, unlike for binary interactions, there is no reliable gold-standard set of three-dimensional (3D) complexes to benchmark the performance of these methodologies and detect their limitations. Here, we present a strategy to dynamically generate non-redundant sets of 3D heteromeric complexes with three or more components. By changing the values of sequence identity and component overlap between assemblies required to define complex redundancy, we can create sets of representative complexes with known 3D structure (i.e., target complexes). Using an identity threshold of 20% and imposing a fraction of component overlap of <0.5, we identify 495 unique target complexes, which represent a real non-redundant set of heteromeric assemblies with known 3D structure. Moreover, for each target complex, we also identify a set of assemblies, of varying degrees of identity and component overlap, that can be readily used as input in a complex modeling exercise (i.e., template subcomplexes). We hope that resources like this will significantly help the development and progress assessment of novel methodologies, as docking benchmarks and blind prediction contests did. The interactive resource is accessible at https://DynBench3D.irbbarcelona.org.

Determining the Structural and Energetic Basis of Allostery in a De Novo Designed Metalloprotein Assembly

Despite significant progress in protein design, the construction of protein assemblies that display complex functions (e.g., catalysis or allostery) remains a significant challenge. We recently reported the de novo construction of an allosteric supramolecular protein assembly (Zn-C38/C81/C96R14) in which the dissociation and binding of ZnII ions were coupled over a distance of 15 Å to the selective hydrolytic breakage and formation of a single disulfide bond. Zn-C38/C81/C96R14 was constructed by ZnII-templated assembly of a monomeric protein (R1, a derivative of cytochrome cb562) into a tetramer, followed by progressive incorporation of noncovalent and disulfide bonding interactions into the protein-protein interfaces to create a strained quaternary architecture. The interfacial strain thus built allowed mechanical coupling between the binding/dissociation of ZnII and formation/hydrolysis of a single disulfide bond (C38-C38) out of a possible six. While the earlier study provided structural evidence for the two end-states of allosteric coupling, the energetic basis for allosteric coupling and the minimal structural requirements for building this allosteric system were not understood. Toward this end, we have characterized the structures and Zn-binding properties of two related protein constructs (C38/C96R1 and C38R1) which also possess C38-C38 disulfide bonds. In addition, we have carried out extensive molecular dynamics simulations of C38/C81/C96R14 to understand the energetic basis for the selective cleavage of the C38-C38 disulfide bond upon ZnII dissociation. Our analyses reveal that the local interfacial environment around the C38-C38 bond is key to its selective cleavage, but this cleavage is only possible within the context of a stable quaternary architecture which enables structural coupling between ZnII coordination and the protein-protein interfaces.

Determinism and boundedness of self-assembling structures

Self-assembly processes are widespread in nature and lie at the heart of many biological and physical phenomena. The characteristics of self-assembly building blocks determine the structures that they form. Two crucial properties are the determinism and boundedness of the self-assembly. The former tells us whether the same set of building blocks always generates the same structure, and the latter whether it grows indefinitely. These properties are highly relevant in the context of protein structures, as the difference between deterministic protein self-assembly and nondeterministic protein aggregation is central to a number of diseases. Here we introduce a graph theoretical approach that can determine the determinism and boundedness for several geometries and dimensionalities of self-assembly more accurately and quickly than conventional methods. We apply this methodology to a previously studied lattice self-assembly model and discuss generalizations to a wide range of other self-assembling systems.

Quantitative mass imaging of single biological macromolecules

The cellular processes underpinning life are orchestrated by proteins and their interactions. The associated structural and dynamic heterogeneity, despite being key to function, poses a fundamental challenge to existing analytical and structural methodologies. We used interferometric scattering microscopy to quantify the mass of single biomolecules in solution with 2% sequence mass accuracy, up to 19-kilodalton resolution, and 1-kilodalton precision. We resolved oligomeric distributions at high dynamic range, detected small-molecule binding, and mass-imaged proteins with associated lipids and sugars. These capabilities enabled us to characterize the molecular dynamics of processes as diverse as glycoprotein cross-linking, amyloidogenic protein aggregation, and actin polymerization. Interferometric scattering mass spectrometry allows spatiotemporally resolved measurement of a broad range of biomolecular interactions, one molecule at a time.

Phylogenetic divergence of cell biological features

Most cellular features have a range of states, but understanding the mechanisms responsible for interspecific divergence is a challenge for evolutionary cell biology. Models are developed for the distribution of mean phenotypes likely to evolve under the joint forces of mutation and genetic drift in the face of constant selection pressures. Mean phenotypes will deviate from optimal states to a degree depending on the effective population size, potentially leading to substantial divergence in the absence of diversifying selection. The steady-state distribution for the mean can even be bimodal, with one domain being largely driven by selection and the other by mutation pressure, leading to the illusion of phenotypic shifts being induced by movement among alternative adaptive domains. These results raise questions as to whether lineage-specific selective pressures are necessary to account for interspecific divergence, providing a possible platform for the establishment of null models for the evolution of cell-biological traits.

Theory for the Liquid-Liquid Phase Separation in Aqueous Antibody Solutions

This study presents the theory for liquid-liquid phase separation for systems of molecules modeling monoclonal antibodies. Individual molecule is depicted as an assembly of seven hard spheres, organized to mimic the Y-shaped antibody. We consider the antibody-antibody interactions either through Fab, Fab' (two Fab fragments may be different), or Fc domain. Interaction between these three domains of the molecule (hereafter denoted as A, B, and C, respectively) is modeled by a short-range square-well attraction. To obtain numerical results for the model under study, we adapt Wertheim's thermodynamic perturbation theory. We use this model to calculate the liquid-liquid phase separation curve and the second virial coefficient B2. Various interaction scenarios are examined to see how the strength of the site-site interactions and their range shape the coexistence curve. In the asymmetric case, where an attraction between two sites is favored and the interaction energies for the other sites kept constant, critical temperature first increases and than strongly decreases. Some more microscopic information, for example, the probability for the particular two sites to be connected, has been calculated. Analysis of the experimental liquid-liquid phase diagrams, obtained from literature, is presented. In addition, we calculate the second virial coefficient under conditions leading to the liquid-liquid phase separation and present this quantity on the graph B2 versus protein concentration.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states.

Automated evaluation of quaternary structures from protein crystals

A correct assessment of the quaternary structure of proteins is a fundamental prerequisite to understanding their function, physico-chemical properties and mode of interaction with other proteins. Currently about 90% of structures in the Protein Data Bank are crystal structures, in which the correct quaternary structure is embedded in the crystal lattice among a number of crystal contacts. Computational methods are required to 1) classify all protein-protein contacts in crystal lattices as biologically relevant or crystal contacts and 2) provide an assessment of how the biologically relevant interfaces combine into a biological assembly. In our previous work we addressed the first problem with our EPPIC (Evolutionary Protein Protein Interface Classifier) method. Here, we present our solution to the second problem with a new method that combines the interface classification results with symmetry and topology considerations. The new algorithm enumerates all possible valid assemblies within the crystal using a graph representation of the lattice and predicts the most probable biological unit based on the pairwise interface scoring. Our method achieves 85% precision (ranging from 76% to 90% for different oligomeric types) on a new dataset of 1,481 biological assemblies with consensus of PDB annotations. Although almost the same precision is achieved by PISA, currently the most popular quaternary structure assignment method, we show that, due to the fundamentally different approach to the problem, the two methods are complementary and could be combined to improve biological assembly assignments. The software for the automatic assessment of protein assemblies (EPPIC version 3) has been made available through a web server at http://www.eppic-web.org.

X-ray diffraction experiments are the main experimental technique to reveal the detailed atomic 3-dimensional structure of proteins. In these experiments, proteins are packed into crystals, an environment that is far away from their native solution environment. Determining which parts of the structure reflect the protein’s state in the cell rather than being artifacts of the crystal environment can be a difficult task. How the different protein subunits assemble together in solution is known as the quaternary structure. Finding the correct quaternary structure is important both to understand protein oligomerization and for the understanding of protein-protein interactions at large. Here we present a new method to automatically determine the quaternary structure of proteins given their crystal structure. We provide a theoretical basis for properties that correct protein assemblies should possess, and provide a systematic evaluation of all possible assemblies according to these properties. The method provides a guidance to the experimental structural biologist as well as to structural bioinformaticians analyzing protein structures in bulk. Assemblies are provided for all proteins in the Protein Data Bank through a public website and database that is updated weekly as new structures are released.

Analytical symmetry detection in protein assemblies. I. Cyclic symmetries

Symmetry in protein, and, more generally, in macromolecular assemblies is a key point to understand their structure, stability and function. Many symmetrical assemblies are currently present in the Protein Data Bank (PDB) and some of them are among the largest solved structures, thus an efficient computational method is needed for the exhaustive analysis of these. The cyclic symmetry groups represent the most common assemblies in the PDB. These are also the building blocks for higher-order symmetries. This paper presents a mathematical formulation to find the position and the orientation of the symmetry axis in a cyclic symmetrical protein assembly, and also to assess the quality of this symmetry. Our method can also detect symmetries in partial assemblies. We provide an efficient C++ implementation of the method and demonstrate its efficiency on several examples including partial assemblies and pseudo symmetries. We also compare the method with two other published techniques and show that it is significantly faster on all the tested examples. Our method produces results with a machine precision, its cost function is solely based on 3D Euclidean geometry, and most of the operations are performed analytically. The method is available athttp://team.inria.fr/nano-d/software/ananas. The graphical user interface of the method built for the SAMSON platform is available athttp://samson-connect.net.

Crystal structures of eukaryote glycosyltransferases reveal biologically relevant enzyme homooligomers

Glycosyltransferases (GTases) transfer sugar moieties to proteins, lipids or existing glycan or polysaccharide molecules. GTases form an important group of enzymes in the Golgi, where the synthesis and modification of glycoproteins and glycolipids take place. Golgi GTases are almost invariably type II integral membrane proteins, with the C-terminal globular catalytic domain residing in the Golgi lumen. The enzymes themselves are divided into 103 families based on their sequence homology. There is an abundance of published crystal structures of GTase catalytic domains deposited in the Protein Data Bank (PDB). All of these represent either of the two main characteristic structural folds, GT-A or GT-B, or present a variation thereof. Since GTases can function as homomeric or heteromeric complexes in vivo, we have summarized the structural features of the dimerization interfaces in crystal structures of GTases, as well as considered the biochemical data available for these enzymes. For this review, we have considered all 898 GTase crystal structures in the Protein Data Bank and highlight the dimer formation characteristics of various GTases based on 24 selected structures.

Cotranslational protein assembly imposes evolutionary constraints on homomeric proteins

Cotranslational protein folding can facilitate rapid formation of functional structures. However, it can also cause premature assembly of protein complexes, if two interacting nascent chains are in close proximity. By analyzing known protein structures, we show that homomeric protein contacts are enriched toward the C termini of polypeptide chains across diverse proteomes. We hypothesize that this is the result of evolutionary constraints for folding to occur before assembly. Using high-throughput imaging of protein homomers in Escherichia coli and engineered protein constructs with N- and C-terminal oligomerization domains, we show that, indeed, proteins with C-terminal homomeric interface residues consistently assemble more efficiently than those with N-terminal interface residues. Using in vivo, in vitro and in silico experiments, we identify features that govern successful assembly of homomers, which have implications for protein design and expression optimization.

Structural properties of genotype-phenotype maps

The map between genotype and phenotype is fundamental to biology. Biological information is stored and passed on in the form of genotypes, and expressed in the form of phenotypes. A growing body of literature has examined a wide range of genotype-phenotype (GP) maps and has established a number of properties that appear to be shared by many GP maps. These properties are 'structural' in the sense that they are properties of the distribution of phenotypes across the point-mutation network of genotypes. They include: a redundancy of genotypes, meaning that many genotypes map to the same phenotypes, a highly non-uniform distribution of the number of genotypes per phenotype, a high robustness of phenotypes and the ability to reach a large number of new phenotypes within a small number of mutational steps. A further important property is that the robustness and evolvability of phenotypes are positively correlated. In this review, I give an overview of the study of GP maps with particular emphasis on these structural properties, and discuss a model that attempts to explain why these properties arise, as well as some of the fundamental ways in which the structure of GP maps can affect evolutionary outcomes.

Structural principles that enable oligomeric small heat-shock protein paralogs to evolve distinct functions

Oligomeric proteins assemble with exceptional selectivity, even in the presence of closely related proteins, to perform their cellular roles. We show that most proteins related by gene duplication of an oligomeric ancestor have evolved to avoid hetero-oligomerization and that this correlates with their acquisition of distinct functions. We report how coassembly is avoided by two oligomeric small heat-shock protein paralogs. A hierarchy of assembly, involving intermediates that are populated only fleetingly at equilibrium, ensures selective oligomerization. Conformational flexibility at noninterfacial regions in the monomers prevents coassembly, allowing interfaces to remain largely conserved. Homomeric oligomers must overcome the entropic benefit of coassembly and, accordingly, homomeric paralogs comprise fewer subunits than homomers that have no paralogs.

Quaternary structure influences the peroxidase activity of peroxiredoxin 3

Peroxiredoxins are abundant peroxidase enzymes that are key regulators of the cellular redox environment. A major subgroup of these proteins, the typical 2-Cys peroxiredoxins, can switch between dimers and decameric or dodecameric rings, during the catalytic cycle. The necessity of this change in quaternary structure for function as a peroxidase is not fully understood. In order to explore this, human peroxiredoxin 3 (Prx3) protein was engineered to form both obligate dimers (S75E Prx3) and stabilised dodecameric rings (S78C Prx3), uncoupling structural transformations from the catalytic cycle. The obligate dimer, S75E Prx3, retained catalytic activity towards hydrogen peroxide, albeit significantly lower than the wildtype and S78C proteins, suggesting an evolutionary advantage of having higher order self-assemblies.

Visualization and analysis of non-covalent contacts using the Protein Contacts Atlas

Visualizations of biomolecular structures empower us to gain insights into biological functions, generate testable hypotheses, and communicate biological concepts. Typical visualizations (such as ball and stick) primarily depict covalent bonds. In contrast, non-covalent contacts between atoms, which govern normal physiology, pathogenesis, and drug action, are seldom visualized. We present the Protein Contacts Atlas, an interactive resource of non-covalent contacts from over 100,000 PDB crystal structures. We developed multiple representations for visualization and analysis of non-covalent contacts at different scales of organization: atoms, residues, secondary structure, subunits, and entire complexes. The Protein Contacts Atlas enables researchers from different disciplines to investigate diverse questions in the framework of non-covalent contacts, including the interpretation of allostery, disease mutations and polymorphisms, by exploring individual subunits, interfaces, and protein-ligand contacts and by mapping external information. The Protein Contacts Atlas is available at http://www.mrc-lmb.cam.ac.uk/pca/ and also through PDBe.

Experimental Characterization of Protein Complex Structure, Dynamics, and Assembly

Experimental methods for the characterization of protein complexes have been instrumental in achieving our current understanding of the protein universe and continue to progress with each year that passes. In this chapter, we review some of the most important tools and techniques in the field, covering the important points in X-ray crystallography, cryo-electron microscopy, NMR spectroscopy, and mass spectrometry. Novel developments are making it possible to study large protein complexes at near-atomic resolutions, and we also now have the ability to study the dynamics and assembly pathways of protein complexes across a range of sizes.

Computational Modelling of Protein Complex Structure and Assembly

Sequence and structure space are nowadays sufficiently large that we can use computational methods to model the structure of proteins based on sequence similarity alone. Not only useful as a standalone tool, homology modelling has also had a transformative effect on the ease with which we can solve crystal structures and electron density maps. Another technique-molecular dynamics-aims to model protein structures from first principles and, thanks to increases in computational power, is slowly becoming a viable tool for studying protein complexes. Finally, the prediction of protein assembly pathways from three-dimensional structures of complexes is also now becoming possible.

The importance of thermodynamics for molecular systems, and the importance of molecular systems for thermodynamics

Improved understanding of molecular systems has only emphasised the sophistication of networks within the cell. Simultaneously, the advance of nucleic acid nanotechnology, a platform within which reactions can be exquisitely controlled, has made the development of artificial architectures and devices possible. Vital to this progress has been a solid foundation in the thermodynamics of molecular systems. In this pedagogical review and perspective, we discuss how thermodynamics determines both the overall potential of molecular networks, and the minute details of design. We then argue that, in turn, the need to understand molecular systems is helping to drive the development of theories of thermodynamics at the microscopic scale.

Toward Large-Scale Computational Prediction of Protein Complexes

Cellular functions are often performed by multiprotein structures called protein complexes. These complexes are dynamic structures that evolve during the cell cycle or in response to external and internal stimuli, and are tightly regulated by protein expression in different tissues resulting in quantitative and qualitative variation of protein complexes. Advances in high-throughput techniques, such as mass-spectrometry and yeast two-hybrid provided a large amount of data on protein-protein interactions. This sparked the development of computational methods able to predict protein complex formation under a variety of biological and clinical conditions. However, the challenges that need to be addressed for successful computational protein complex prediction are highly complex.The post-genomic era saw an emerging number of algorithms and software, which are able to predict protein complexes from protein-protein interaction networks and a variety of other sources. Despite the high capacity of these methods to qualitatively predict protein complexes, they could provide only limited or no quantitative information of the predicted complexes. Recently, a new large-scale simulation of protein complexes was able to achieve this task by simulating protein complex formation on the proteome scale.In this chapter, we review representative methods that can predict multiple protein complexes at different scales and discuss how these can be combined with emerging sources of data in order to improve protein complex characterization.

Photocontrolled protein assembly for constructing programmed two-dimensional nanomaterials

A rapid and efficient strategy was developed to construct photocontrolled 2D protein nanosheets with an orderly arrangement.

Characterizing Intact Macromolecular Complexes Using Native Mass Spectrometry

Native mass spectrometry (MS) enables the characterization of macromolecular assemblies with high sensitivity. It can reveal the stoichiometry of subunits as well as their two-dimensional interaction network and provide information regarding the dynamic behavior of macromolecular complexes. Here, we describe the workflow to perform native MS experiments. In addition, we illustrate the quality control analysis of proteins using MS in denaturing conditions.

Hierarchical design of artificial proteins and complexes toward synthetic structural biology

In multiscale structural biology, synthetic approaches are important to demonstrate biophysical principles and mechanisms underlying the structure, function, and action of bio-nanomachines. A central goal of "synthetic structural biology" is the design and construction of artificial proteins and protein complexes as desired. In this paper, I review recent remarkable progress of an array of approaches for hierarchical design of artificial proteins and complexes that signpost the path forward toward synthetic structural biology as an emerging interdisciplinary field. Topics covered include combinatorial and protein-engineering approaches for directed evolution of artificial binding proteins and membrane proteins, binary code strategy for structural and functional de novo proteins, protein nanobuilding block strategy for constructing nano-architectures, protein-metal-organic frameworks for 3D protein complex crystals, and rational and computational approaches for design/creation of artificial proteins and complexes, novel protein folds, ideal/optimized protein structures, novel binding proteins for targeted therapeutics, and self-assembling nanomaterials. Protein designers and engineers look toward a bright future in synthetic structural biology for the next generation of biophysics and biotechnology.

Self-assembly of model proteins into virus capsids

We consider self-assembly of proteins into a virus capsid by the methods of molecular dynamics. The capsid corresponds either to SPMV or CCMV and is studied with and without the RNA molecule inside. The proteins are flexible and described by the structure-based coarse-grained model augmented by electrostatic interactions. Previous studies of the capsid self-assembly involved solid objects of a supramolecular scale, e.g. corresponding to capsomeres, with engineered couplings and stochastic movements. In our approach, a single capsid is dissociated by an application of a high temperature for a variable period and then the system is cooled down to allow for self-assembly. The restoration of the capsid proceeds to various extent, depending on the nature of the dissociated state, but is rarely complete because some proteins depart too far unless the process takes place in a confined space.

Size Exclusion Chromatography-Ion Mobility-Mass Spectrometry Coupling: a Step Toward Structural Biology

Noncovalent interactions are essential for the structural organization of biomacromolecules in cells. For this reason, the study of the biophysical, dynamic, and architectural interactions among biomacromolecules is essential. Since mass spectrometry requires compatible solutions while preserving the noncovalent bonding network, we envisioned that size exclusion chromatography coupled with ion mobility and mass spectrometry would be a valuable technique to desalt the initial sample and provide solution and gas-phase structural information in a single stage experiment. Such coupling allowed obtaining information on solution protein complex composition with SEC separation and on authenticity and purity with IMS-MS. Our study demonstrated that such coupling is compatible, useful, as well as suitable for a routine analysis, in pharmaceutical industry, for example. Mobility data were reliable and injected standards allowed calibrating the collision cross-section scale. Graphical Abstract ᅟ.

Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space

Network motifs have been studied extensively over the past decade, and certain motifs, such as the feed-forward loop, play an important role in regulatory networks. Recent studies have used Boolean network motifs to explore the link between form and function in gene regulatory networks and have found that the structure of a motif does not strongly determine its function, if this is defined in terms of the gene expression patterns the motif can produce. Here, we offer a different, higher-level definition of the ‘function’ of a motif, in terms of two fundamental properties of its dynamical state space as a Boolean network. One is the basin entropy, which is a complexity measure of the dynamics of Boolean networks. The other is the diversity of cyclic attractor lengths that a given motif can produce. Using these two measures, we examine all 104 topologically distinct three-node motifs and show that the structural properties of a motif, such as the presence of feedback loops and feed-forward loops, predict fundamental characteristics of its dynamical state space, which in turn determine aspects of its functional versatility. We also show that these higher-level properties have a direct bearing on real regulatory networks, as both basin entropy and cycle length diversity show a close correspondence with the prevalence, in neural and genetic regulatory networks, of the 13 connected motifs without self-interactions that have been studied extensively in the literature.

Biogenic manganese oxide nanoparticle formation by a multimeric multicopper oxidase Mnx

Bacteria that produce Mn oxides are extraordinarily skilled engineers of nanomaterials that contribute significantly to global biogeochemical cycles. Their enzyme-based reaction mechanisms may be genetically tailored for environmental remediation applications or bioenergy production. However, significant challenges exist for structural characterization of the enzymes responsible for biomineralization. The active Mn oxidase in Bacillus sp. PL-12, Mnx, is a complex composed of a multicopper oxidase (MCO), MnxG, and two accessory proteins, MnxE and MnxF. MnxG shares sequence similarity with other, structurally characterized MCOs. MnxE and MnxF have no similarity to any characterized proteins. The ~200 kDa complex has been recalcitrant to crystallization, so its structure is unknown. Here, we show that native mass spectrometry defines the subunit topology and copper binding of Mnx, while high-resolution electron microscopy visualizes the protein and nascent Mn oxide minerals. These data provide critical structural information for understanding Mn biomineralization by such unexplored enzymes.

Significant challenges exist for structural characterization of enzymes responsible for biomineralization. Here the authors show that native mass spectrometry and high resolution electron microscopy can define the subunit topology and copper binding of a manganese oxidizing complex, and describe early stage formation of its mineral products

Spatiotemporal Analysis of K-Ras Plasma Membrane Interactions Reveals Multiple High Order Homo-oligomeric Complexes

Self-assembly of plasma membrane-associated Ras GTPases has major implications to the regulation of cell signaling. However, the structural basis of homo-oligomerization and the fractional distribution of oligomeric states remained undetermined. We have addressed these issues by deciphering the distribution of dimers and higher-order oligomers of K-Ras4B, the most frequently mutated Ras isoform in human cancers. We focused on the constitutively active G12V K-Ras and two of its variants, K101E and K101C/E107C, which respectively destabilize and stabilize oligomers. Using raster image correlation spectroscopy and number and brightness analysis combined with fluorescence recovery after photobleaching, fluorescence correlation spectroscopy and electron microscopy in live cells, we show that G12V K-Ras exists as a mixture of monomers, dimers and larger oligomers, while the K101E mutant is predominantly monomeric and K101C/E107C is dominated by oligomers. This observation demonstrates the ability of K-Ras to exist in multiple oligomeric states whose population can be altered by interfacial mutations. Using molecular modeling and simulations we further show that K-Ras uses two partially overlapping interfaces to form compositionally and topologically diverse oligomers. Our results thus provide the first detailed insight into the multiplicity, structure, and membrane organization of K-Ras homomers.

Protein complex prediction via dense subgraphs and false positive analysis

Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks), which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters and information based on protein functionality. However, some schemes still require much processing time or the quality of their results can be improved. Furthermore, most of the results obtained with computational tools are not accompanied by an analysis of false positives. We propose an effective and efficient mining algorithm for discovering highly connected subgraphs, which is our base for defining protein complexes. Our representation is based on transforming the PPI network into a directed acyclic graph that reduces the number of represented edges and the search space for discovering subgraphs. Our approach considers weighted and unweighted PPI networks. We compare our best alternative using PPI networks from Saccharomyces cerevisiae (yeast) and Homo sapiens (human) with state-of-the-art approaches in terms of clustering, biological metrics and execution times, as well as three gold standards for yeast and two for human. Furthermore, we analyze false positive predicted complexes searching the PDBe (Protein Data Bank in Europe) database in order to identify matching protein complexes that have been purified and structurally characterized. Our analysis shows that more than 50 yeast protein complexes and more than 300 human protein complexes found to be false positives according to our prediction method, i.e., not described in the gold standard complex databases, in fact contain protein complexes that have been characterized structurally and documented in PDBe. We also found that some of these protein complexes have recently been classified as part of a Periodic Table of Protein Complexes. The latest version of our software is publicly available at http://doi.org/10.6084/m9.figshare.5297314.v1.

Evolutionary diversification of protein-protein interactions by interface add-ons

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

Reversible unfolding of infectious prion assemblies reveals the existence of an oligomeric elementary brick

Mammalian prions, the pathogens that cause transmissible spongiform encephalopathies, propagate by self-perpetuating the structural information stored in the abnormally folded, aggregated conformer (PrP^Sc) of the host-encoded prion protein (PrP^C). To date, no structural model related to prion assembly organization satisfactorily describes how strain-specified structural information is encoded and by which mechanism this information is transferred to PrP^C. To achieve progress on this issue, we correlated the PrP^Sc quaternary structural transition from three distinct prion strains during unfolding and refolding with their templating activity. We reveal the existence of a mesoscopic organization in PrP^Sc through the packing of a highly stable oligomeric elementary subunit (suPrP), in which the strain structural determinant (SSD) is encoded. Once kinetically trapped, this elementary subunit reversibly loses all replicative information. We demonstrate that acquisition of the templating interface and infectivity requires structural rearrangement of suPrP, in concert with its condensation. The existence of such an elementary brick scales down the SSD support to a small oligomer and provide a basis of reflexion for prion templating process and propagation.

Prions are self-propagating assemblies with all necessary and sufficient replicative information stored in the 3D structure of the misfolded form of PrP called PrP^Sc. Since the emergence of the prion theory in the 80s, many attempts have been done to identify prion replicative information at molecular scale. Different models have been constructed based on a broad panel of experimental observations and some of them predict the existence of periodic elements constituting prion assemblies. Here, by using partial unfolding approaches, we trapped an oligomeric conformer that we called suPrP, which could constitute the elementary brick of prion assemblies. Once isolated, this elementary brick is devoid of infectivity. However, it becomes infectious once condensated into larger assemblies. The identification of the elementary PrP building block provides a new structural basis for understanding prion replicative information storage and spreading.

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.

Signalling assemblies: the odds of symmetry

The assembly of proteins into complexes is fundamental to nearly all biological signalling processes. Symmetry is a dominant feature of the structures of experimentally determined protein complexes, observed in the vast majority of homomers and many heteromers. However, some asymmetric structures exist, and asymmetry also often forms transiently, intractable to traditional structure determination methods. Here, we explore the role of protein complex symmetry and asymmetry in cellular signalling, focusing on receptors, transcription factors and transmembrane channels, among other signalling assemblies. We highlight a recurrent tendency for asymmetry to be crucial for signalling function, often being associated with activated states. We conclude with a discussion of how consideration of protein complex symmetry and asymmetry has significant potential implications and applications for pharmacology and human disease.

Proteins evolve on the edge of supramolecular self-assembly

The self-association of proteins into symmetric complexes is ubiquitous in all kingdoms of life. Symmetric complexes possess unique geometric and functional properties, but their internal symmetry can pose a risk. In sickle-cell disease, the symmetry of haemoglobin exacerbates the effect of a mutation, triggering assembly into harmful fibrils. Here we examine the universality of this mechanism and its relation to protein structure geometry. We introduced point mutations solely designed to increase surface hydrophobicity among 12 distinct symmetric complexes from Escherichia coli. Notably, all responded by forming supramolecular assemblies in vitro, as well as in vivo upon heterologous expression in Saccharomyces cerevisiae. Remarkably, in four cases, micrometre-long fibrils formed in vivo in response to a single point mutation. Biophysical measurements and electron microscopy revealed that mutants self-assembled in their folded states and so were not amyloid-like. Structural examination of 73 mutants identified supramolecular assembly hot spots predictable by geometry. A subsequent structural analysis of 7,471 symmetric complexes showed that geometric hot spots were buffered chemically by hydrophilic residues, suggesting a mechanism preventing mis-assembly of these regions. Thus, point mutations can frequently trigger folded proteins to self-assemble into higher-order structures. This potential is counterbalanced by negative selection and can be exploited to design nanomaterials in living cells.

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as "building blocks" for a range of customized intracellular scaffolds. We summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering.

Functional determinants of protein assembly into homomeric complexes

Approximately half of proteins with experimentally determined structures can interact with other copies of themselves and assemble into homomeric complexes, the overwhelming majority of which (>96%) are symmetric. Although homomerisation is often assumed to a functionally beneficial result of evolutionary selection, there has been little systematic analysis of the relationship between homomer structure and function. Here, utilizing the large numbers of structures and functional annotations now available, we have investigated how proteins that assemble into different types of homomers are associated with different biological functions. We observe that homomers from different symmetry groups are significantly enriched in distinct functions, and can often provide simple physical and geometrical explanations for these associations in regards to substrate recognition or physical environment. One of the strongest associations is the tendency for metabolic enzymes to form dihedral complexes, which we suggest is closely related to allosteric regulation. We provide a physical explanation for why allostery is related to dihedral complexes: it allows for efficient propagation of conformational changes across isologous (i.e. symmetric) interfaces. Overall we demonstrate a clear relationship between protein function and homomer symmetry that has important implications for understanding protein evolution, as well as for predicting protein function and quaternary structure.

Characterization of the oligomeric states of the CK2 α2β2 holoenzyme in solution

The regulatory mechanism of protein kinase CK2 has still to be fully clarified. The prevailing hypothesis is that CK2 is controlled by a self-polymerisation mechanism leading to inactive supramolecular assemblies that, when needed, can be disassembled into the α2β2 monomer, the active form of the holoenzyme. In vitro, monomeric α2β2 seems present only at high ionic strengths, typically 0.35–0.50 M NaCl, while at lower salt concentrations oligomers are formed. In the present study, size-exclusion chromatography (SEC), dynamic light scattering (DLS), small-angle X-ray scattering (SAXS) and mutagenesis have been employed for the characterization of the oligomeric states of CK2 in solution. SAXS measurements at 0.35 M NaCl show for the first time the shape of the α2β2 active monomer in solution. At 0.25 M salt, despite single average properties indicating an aggregated holoenzyme, deconvolution analysis of SAXS data reveals an equilibrium involving not only circular trimeric and linear oligomeric (3–4 units) forms of α2β2, but also considerable amounts of the monomer. Together SAXS and mutagenesis confirm the presence in solution of the oligomers deduced by crystal structures. The lack of intermediate species such as αβ2, α or β2 indicates that the holoenzyme is a strong complex that does not spontaneously dissociate, challenging what was recently proposed on the basis of mass spectrometry data. A significant novel finding is that a considerable amount of monomer, the active form of CK2, is present also at low salt. The solution properties of CK2 shown in the present study complement the model of regulation by polymerization.

Reconstructing Ancient Proteins to Understand the Causes of Structure and Function

A central goal in biochemistry is to explain the causes of protein sequence, structure, and function. Mainstream approaches seek to rationalize sequence and structure in terms of their effects on function and to identify function's underlying determinants by comparing related proteins to each other. Although productive, both strategies suffer from intrinsic limitations that have left important aspects of many proteins unexplained. These limits can be overcome by reconstructing ancient proteins, experimentally characterizing their properties, and retracing their evolution through time. This approach has proven to be a powerful means for discovering how historical changes in sequence produced the functions, structures, and other physical/chemical characteristics of modern proteins. It has also illuminated whether protein features evolved because of functional optimization, historical constraint, or blind chance. Here we review recent studies employing ancestral protein reconstruction and show how they have produced new knowledge not only of molecular evolutionary processes but also of the underlying determinants of modern proteins' physical, chemical, and biological properties.

Structural modeling of the AhR:ARNT complex in the bHLH-PASA-PASB region elucidates the key determinants of dimerization

Elucidation of the dimerization process of the aryl hydrocarbon receptor (AhR) with the AhR nuclear translocator (ARNT) is crucial for understanding the mechanisms underlying the functional activity of AhR, including mediation of the toxicity of environmental contaminants. In this work, for the first time a structural model of the AhR:ARNT dimer encompassing the entire bHLH-PASA-PASB domain region is proposed. It is developed by using a template-based modeling approach, relying on the recently available crystallographic structures of two dimers of homologous systems in the bHLH-PAS family of proteins: the CLOCK:BMAL1 and the HIF2α:ARNT heterodimers. The structural and energetic characteristics of the modeled AhR:ARNT protein-protein interface are determined by evaluating the variations in solvent accessible surface area, the total binding free energy and the per-residue free energy contributions obtained by the MM-GBSA method and the Energy Decomposition Analysis. The analyses of the intricate network of inter-domain interactions at the dimerization interfaces provide insights into the key determinants of dimerization. These are confirmed by comparison of the computational findings with the available experimental mutagenesis and functional analysis data. The results presented here on the AhR:ARNT dimer structure and interactions provide a framework to start analyzing the mechanism of AhR transformation into its functional DNA binding form.