Cryo-EM structure of the octameric pore of Clostridium perfringens ß-toxin.

Clostridium perfringens is one of the most widely distributed and successful pathogens producing an impressive arsenal of toxins. One of the most potent toxins produced is the C. perfringens ß-toxin (CPB). This toxin is the main virulence factor of type C strains. We describe the cryo-electron microscopy (EM) structure of CPB oligomer. We show that CPB forms homo-octameric pores like the hetero-oligomeric pores of the bi-component leukocidins, with important differences in the receptor binding region and the N-terminal latch domain. Intriguingly, the octameric CPB pore complex contains a second 16-stranded ß-barrel protrusion atop of the cap domain that is formed by the N-termini of the eight protomers. We propose that CPB, together with the newly identified Epx toxins, is a member a new subclass of the hemolysin-like family. In addition, we show that the ß-barrel protrusion domain can be modified without affecting the pore-forming ability, thus making the pore particularly attractive for macromolecule sensing and nanotechnology. The cryo-EM structure of the octameric pore of CPB will facilitate future developments in both nanotechnology and basic research.

Allophycocyanin A is a carbon dioxide receptor in the cyanobacterial phycobilisome.

Light harvesting is fundamental for production of ATP and reducing equivalents for CO2 fixation during photosynthesis. However, electronic energy transfer (EET) through a photosystem can harm the photosynthetic apparatus when not balanced with CO2. Here, we show that CO2 binding to the light-harvesting complex modulates EET in photosynthetic cyanobacteria. More specifically, CO2 binding to the allophycocyanin alpha subunit of the light-harvesting complex regulates EET and its fluorescence quantum yield in the cyanobacterium Synechocystis sp. PCC 6803. CO2 binding decreases the inter-chromophore distance in the allophycocyanin trimer. The result is enhanced EET in vitro and in live cells. Our work identifies a direct target for CO2 in the cyanobacterial light-harvesting apparatus and provides insights into photosynthesis regulation.

Identification of Graphene Dispersion Agents through Molecular Fingerprints.

The scalable production and dispersion of 2D materials, like graphene, is critical to enable their use in commercial applications. While liquid exfoliation is commonly used, solvents such as N-methyl-pyrrolidone (NMP) are toxic and difficult to scale up. However, the search for alternative solvents is hindered by the intimidating size of the chemical space. Here, we present a computational pipeline informing the identification of effective exfoliation agents. Classical molecular dynamics simulations provide statistical sampling of interactions, enabling the identification of key molecular descriptors for a successful solvent. The statistically representative configurations from these simulations, studied with quantum mechanical calculations, allow us to gain insights onto the chemophysical interactions at the surface-solvent interface. As an exemplar, through this pipeline we identify a potential graphene exfoliation agent 2-pyrrolidone and experimentally demonstrate it to be as effective as NMP. Our workflow can be generalized to any 2D material and solvent system, enabling the screening of a wide range of compounds and solvents to identify safer and cheaper means of producing dispersions.

Complementing machine learning-based structure predictions with native mass spectrometry.

The advent of machine learning-based structure prediction algorithms such as AlphaFold2 (AF2) and RoseTTa Fold have moved the generation of accurate structural models for the entire cellular protein machinery into the reach of the scientific community. However, structure predictions of protein complexes are based on user-provided input and may require experimental validation. Mass spectrometry (MS) is a versatile, time-effective tool that provides information on post-translational modifications, ligand interactions, conformational changes, and higher-order oligomerization. Using three protein systems, we show that native MS experiments can uncover structural features of ligand interactions, homology models, and point mutations that are undetectable by AF2 alone. We conclude that machine learning can be complemented with MS to yield more accurate structural models on a small and large scale.

Electrospray ionization of native membrane proteins proceeds via a charge equilibration step.

Electrospray ionization mass spectrometry is increasingly applied to study the structures and interactions of membrane protein complexes. However, the charging mechanism is complicated by the presence of detergent micelles during ionization. Here, we show that the final charge of membrane proteins can be predicted by their molecular weight when released from the non-charge reducing saccharide detergents. Our data indicate that PEG detergents lower the charge depending on the number of detergent molecules in the surrounding micelle, whereas fos-choline detergents may additionally participate in ion-ion reactions after desolvation. The supercharging reagent sulfolane, on the other hand, has no discernible effect on the charge of detergent-free membrane proteins. Taking our observations into the context of protein-detergent interactions in the gas phase, we propose a charge equilibration model for the generation of native-like membrane protein ions. During ionization of the protein-detergent complex, the ESI charges are distributed between detergent and protein according to proton affinity of the detergent, number of detergent molecules, and surface area of the protein. Charge equilibration influenced by detergents determines the final charge state of membrane proteins. This process likely contributes to maintaining a native-like fold after detergent release and can be harnessed to stabilize particularly labile membrane protein complexes in the gas phase.

Biobox: a toolbox for biomolecular modelling.

MOTIVATION: The implementation of biomolecular modelling methods and analyses can be cumbersome, often carried out with in-house software reimplementing common tasks, and requiring the integration of diverse software libraries. RESULTS: We present Biobox, a Python-based toolbox facilitating the implementation of biomolecular modelling methods. AVAILABILITY AND IMPLEMENTATION: Biobox is freely available on https://github.com/degiacom/biobox, along with its API and interactive Jupyter notebook tutorials.

Transmembrane Protein Docking with JabberDock.

Transmembrane proteins act as an intermediary for a broad range of biological process. Making up 20% to 30% of the proteome, their ubiquitous nature has resulted in them comprising 50% of all targets in drug design. Despite their importance, they make up only 4% of all structures in the PDB database, primarily owing to difficulties associated with isolating and characterizing them. Membrane protein docking algorithms could help to fill this knowledge gap, yet only few exist. Moreover, these existing methods achieve success rates lower than the current best soluble proteins docking software. We present and test a pipeline using our software, JabberDock, to dock membrane proteins. JabberDock docks shapes representative of membrane protein structure and dynamics in their biphasic environment. We verify JabberDock's ability to yield accurate predictions by applying it to a benchmark of 20 transmembrane dimers, returning a success rate of 75.0%. This makes our software very competitive among available membrane protein-protein docking tools.

Mass Photometry of Membrane Proteins.

Integral membrane proteins (IMPs) are biologically highly significant but challenging to study because they require maintaining a cellular lipid-like environment. Here, we explore the application of mass photometry (MP) to IMPs and membrane-mimetic systems at the single-particle level. We apply MP to amphipathic vehicles, such as detergents and amphipols, as well as to lipid and native nanodiscs, characterizing the particle size, sample purity, and heterogeneity. Using methods established for cryogenic electron microscopy, we eliminate detergent background, enabling high-resolution studies of membrane-protein structure and interactions. We find evidence that, when extracted from native membranes using native styrene-maleic acid nanodiscs, the potassium channel KcsA is present as a dimer of tetramers-in contrast to results obtained using detergent purification. Finally, using lipid nanodiscs, we show that MP can help distinguish between functional and non-functional nanodisc assemblies, as well as determine the critical factors for lipid nanodisc formation.

Software Requirements for the Analysis and Interpretation of Native Ion Mobility Mass Spectrometry Data.

The past few years have seen a dramatic increase in applications of native mass and ion mobility spectrometry, especially for the study of proteins and protein complexes. This increase has been catalyzed by the availability of commercial instrumentation capable of carrying out such analyses. As in most fields, however, the software to process the data generated from new instrumentation lags behind. Recently, a number of research groups have started addressing this by developing software, but further improvements are still required in order to realize the full potential of the data sets generated. In this perspective, we describe practical aspects as well as challenges in processing native mass spectrometry (MS) and ion mobility-MS data sets and provide a brief overview of currently available tools. We then set out our vision of future developments that would bring the community together and lead to the development of a common platform to expedite future computational developments, provide standardized processing approaches, and serve as a location for the deposition of data for this emerging field. This perspective has been written by members of the European Cooperation in Science and Technology Action on Native MS and Related Methods for Structural Biology (EU COST Action BM1403) as an introduction to the software tools available in this area. It is intended to serve as an overview for newcomers and to stimulate discussions in the community on further developments in this field, rather than being an in-depth review. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05791) focuses on computational approaches used in this field.

Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches.

In structural biology, collision cross sections (CCSs) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.

Computational Strategies and Challenges for Using Native Ion Mobility Mass Spectrometry in Biophysics and Structural Biology.

Native mass spectrometry (MS) allows the interrogation of structural aspects of macromolecules in the gas phase, under the premise of having initially maintained their solution-phase noncovalent interactions intact. In the more than 25 years since the first reports, the utility of native MS has become well established in the structural biology community. The experimental and technological advances during this time have been rapid, resulting in dramatic increases in sensitivity, mass range, resolution, and complexity of possible experiments. As experimental methods have improved, there have been accompanying developments in computational approaches for analyzing and exploiting the profusion of MS data in a structural and biophysical context. In this perspective, we consider the computational strategies currently being employed by the community, aspects of best practice, and the challenges that remain to be addressed. Our perspective is based on discussions within the European Cooperation in Science and Technology Action on Native Mass Spectrometry and Related Methods for Structural Biology (EU COST Action BM1403), which involved participants from across Europe and North America. It is intended not as an in-depth review but instead to provide an accessible introduction to and overview of the topic-to inform newcomers to the field and stimulate discussions in the community about addressing existing challenges. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05792) focuses on software tools available to help researchers tackle some of the challenges enumerated here.

Protein Docking Using a Single Representation for Protein Surface, Electrostatics, and Local Dynamics.

Predicting the assembly of multiple proteins into specific complexes is critical to understanding their biological function in an organism and thus the design of drugs to address their malfunction. Proteins are flexible molecules, which inherently pose a problem to any protein docking computational method, where even a simple rearrangement of the side chain and backbone atoms at the interface of binding partners complicates the successful determination of the correct docked pose. Herein, we present a means of representing protein surface, electrostatics, and local dynamics within a single volumetric descriptor. We show that our representations can be physically related to the surface-accessible solvent area and mass of the protein. We then demonstrate that the application of this representation into a protein-protein docking scenario bypasses the need to compensate for, and predict, specific side chain packing at the interface of binding partners. This representation is leveraged in our de novo protein docking software, JabberDock, which can accurately and robustly predict difficult target complexes with an average success rate of >54%, which is comparable to or greater than the currently available methods.

HspB1 phosphorylation regulates its intramolecular dynamics and mechanosensitive molecular chaperone interaction with filamin C.

Mechanical force-induced conformational changes in proteins underpin a variety of physiological functions, typified in muscle contractile machinery. Mutations in the actin-binding protein filamin C (FLNC) are linked to musculoskeletal pathologies characterized by altered biomechanical properties and sometimes aggregates. HspB1, an abundant molecular chaperone, is prevalent in striated muscle where it is phosphorylated in response to cues including mechanical stress. We report the interaction and up-regulation of both proteins in three mouse models of biomechanical stress, with HspB1 being phosphorylated and FLNC being localized to load-bearing sites. We show how phosphorylation leads to increased exposure of the residues surrounding the HspB1 phosphosite, facilitating their binding to a compact multidomain region of FLNC proposed to have mechanosensing functions. Steered unfolding of FLNC reveals that its extension trajectory is modulated by the phosphorylated region of HspB1. This may represent a posttranslationally regulated chaperone-client protection mechanism targeting over-extension during mechanical stress.

Coupling Molecular Dynamics and Deep Learning to Mine Protein Conformational Space.

Flexibility is often a key determinant of protein function. To elucidate the link between their molecular structure and role in an organism, computational techniques such as molecular dynamics can be leveraged to characterize their conformational space. Extensive sampling is, however, required to obtain reliable results, useful to rationalize experimental data or predict outcomes before experiments are carried out. We demonstrate that a generative neural network trained on protein structures produced by molecular simulation can be used to obtain new, plausible conformations complementing pre-existing ones. To demonstrate this, we show that a trained neural network can be exploited in a protein-protein docking scenario to account for broad hinge motions taking place upon binding. Overall, this work shows that neural networks can be used as an exploratory tool for the study of molecular conformational space.

Structural and functional consequences of age-related isomerization in α-crystallins.

Long-lived proteins are subject to spontaneous degradation and may accumulate a range of modifications over time, including subtle alterations such as side-chain isomerization. Recently, tandem MS has enabled identification and characterization of such peptide isomers, including those differing only in chirality. However, the structural and functional consequences of these perturbations remain largely unexplored. Here, we examined the impact of isomerization of aspartic acid or epimerization of serine at four sites mapping to crucial oligomeric interfaces in human αA- and αB-crystallin, the most abundant chaperone proteins in the eye lens. To characterize the effect of isomerization on quaternary assembly, we utilized synthetic peptide mimics, enzyme assays, molecular dynamics calculations, and native MS experiments. The oligomerization of recombinant forms of αA- and αB-crystallin that mimic isomerized residues deviated from native behavior in all cases. Isomerization also perturbs recognition of peptide substrates, either enhancing or inhibiting kinase activity. Specifically, epimerization of serine (αASer-162) dramatically weakened inter-subunit binding. Furthermore, phosphorylation of αBSer-59, known to play an important regulatory role in oligomerization, was severely inhibited by serine epimerization and altered by isomerization of nearby αBAsp-62. Similarly, isomerization of αBAsp-109 disrupted a vital salt bridge with αBArg-120, a contact that when broken has previously been shown to yield aberrant oligomerization and aggregation in several disease-associated variants. Our results illustrate how isomerization of amino acid residues, which may seem to be only a minor structural perturbation, can disrupt native structural interactions with profound consequences for protein assembly and activity.

On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies.

Ion mobility mass spectrometry (IM/MS) can provide structural information on intact protein complexes. Such data, including connectivity and collision cross sections (CCS) of assemblies' subunits, can in turn be used as a guide to produce representative super coarse-grained models. These models are constituted by ensembles of overlapping spheres, each representing a protein subunit. A model is considered plausible if the CCS and sphere-overlap levels of its subunits fall within predetermined confidence intervals. While the first is determined by experimental error, the latter is based on a statistical analysis on a range of protein dimers. Here, we first propose a new expression to describe the overlap between two spheres. Then we analyze the effect of specific overlap cutoff choices on the precision and accuracy of super coarse-grained models. Finally, we propose a method to determine overlap cutoff levels on a per-case scenario, based on collected CCS data, and show that it can be applied to the characterization of the assembly topology of symmetrical homo-multimers. Graphical Abstract.

The epilepsy-associated protein TBC1D24 is required for normal development, survival and vesicle trafficking in mammalian neurons.

Mutations in the Tre2/Bub2/Cdc16 (TBC)1 domain family member 24 (TBC1D24) gene are associated with a range of inherited neurological disorders, from drug-refractory lethal epileptic encephalopathy and DOORS syndrome (deafness, onychodystrophy, osteodystrophy, mental retardation, seizures) to non-syndromic hearing loss. TBC1D24 has been implicated in neuronal transmission and maturation, although the molecular function of the gene and the cause of the apparently complex disease spectrum remain unclear. Importantly, heterozygous TBC1D24 mutation carriers have also been reported with seizures, suggesting that haploinsufficiency for TBC1D24 is significant clinically. Here we have systematically investigated an allelic series of disease-associated mutations in neurons alongside a new mouse model to investigate the consequences of TBC1D24 haploinsufficiency to mammalian neurodevelopment and synaptic physiology. The cellular studies reveal that disease-causing mutations that disrupt either of the conserved protein domains in TBC1D24 are implicated in neuronal development and survival and are likely acting as loss-of-function alleles. We then further investigated TBC1D24 haploinsufficiency in vivo and demonstrate that TBC1D24 is also crucial for normal presynaptic function: genetic disruption of Tbc1d24 expression in the mouse leads to an impairment of endocytosis and an enlarged endosomal compartment in neurons with a decrease in spontaneous neurotransmission. These data reveal the essential role for TBC1D24 at the mammalian synapse and help to define common synaptic mechanisms that could underlie the varied effects of TBC1D24 mutations in neurological disease.

It takes a dimer to tango: Oligomeric small heat shock proteins dissociate to capture substrate.

Small heat-shock proteins (sHsps) are ubiquitous molecular chaperones, and sHsp mutations or altered expression are linked to multiple human disease states. sHsp monomers assemble into large oligomers with dimeric substructure, and the dynamics of sHsp oligomers has led to major questions about the form that captures substrate, a critical aspect of their mechanism of action. We show here that substructural dimers of two plant dodecameric sHsps, Ta16.9 and homologous Ps18.1, are functional units in the initial encounter with unfolding substrate. We introduced inter-polypeptide disulfide bonds at the two dodecameric interfaces, dimeric and nondimeric, to restrict how their assemblies can dissociate. When disulfide-bonded at the nondimeric interface, mutants of Ta16.9 and Ps18.1 (TaCT-ACD and PsCT-ACD) were inactive but, when reduced, had WT-like chaperone activity, demonstrating that dissociation at nondimeric interfaces is essential for sHsp activity. Moreover, the size of the TaCT-ACD and PsCT-ACD covalent unit defined a new tetrahedral geometry for these sHsps, different from that observed in the Ta16.9 X-ray structure. Importantly, oxidized Tadimer (disulfide bonded at the dimeric interface) exhibited greatly enhanced ability to protect substrate, indicating that strengthening the dimeric interface increases chaperone efficiency. Temperature-induced size and secondary structure changes revealed that folded sHsp dimers interact with substrate and that dimer stability affects chaperone efficiency. These results yield a model in which sHsp dimers capture substrate before assembly into larger, heterogeneous sHsp-substrate complexes for substrate refolding or degradation, and suggest that tuning the strength of the dimer interface can be used to engineer sHsp chaperone efficiency.

Lipid binding attenuates channel closure of the outer membrane protein OmpF.

Strong interactions between lipids and proteins occur primarily through association of charged headgroups and amino acid side chains, rendering the protonation status of both partners important. Here we use native mass spectrometry to explore lipid binding as a function of charge of the outer membrane porin F (OmpF). We find that binding of anionic phosphatidylglycerol (POPG) or zwitterionic phosphatidylcholine (POPC) to OmpF is sensitive to electrospray polarity while the effects of charge are less pronounced for other proteins in outer or mitochondrial membranes: the ferripyoverdine receptor (FpvA) or the voltage-dependent anion channel (VDAC). Only marginal charge-induced differences were observed for inner membrane proteins: the ammonia channel (AmtB) or the mechanosensitive channel. To understand these different sensitivities, we performed an extensive bioinformatics analysis of membrane protein structures and found that OmpF, and to a lesser extent FpvA and VDAC, have atypically high local densities of basic and acidic residues in their lipid headgroup-binding regions. Coarse-grained molecular dynamics simulations, in mixed lipid bilayers, further implicate changes in charge by demonstrating preferential binding of anionic POPG over zwitterionic POPC to protonated OmpF, an effect not observed to the same extent for AmtB. Moreover, electrophysiology and mass-spectrometry-based ligand-binding experiments, at low pH, show that POPG can maintain OmpF channels in open conformations for extended time periods. Since the outer membrane is composed almost entirely of anionic lipopolysaccharide, with similar headgroup properties to POPG, such anionic lipid binding could prevent closure of OmpF channels, thereby increasing access of antibiotics that use porin-mediated pathways.

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.