A humoral stress response protects Drosophila tissues from antimicrobial peptides.

7An efficient immune system must provide protection against a broad range of pathogens without causing excessive collateral tissue damage. While immune effectors have been well characterized, we know less about the resilience mechanisms protecting the host from its own immune response. Antimicrobial peptides (AMPs) are small, cationic peptides that contribute to innate defenses by targeting negatively charged membranes of microbes. While protective against pathogens, AMPs can be cytotoxic to host cells. Here, we reveal that a family of stress-induced proteins, the Turandots, protect the Drosophila respiratory system from AMPs, increasing resilience to stress. Flies lacking Turandot genes are susceptible to environmental stresses due to AMP-induced tracheal apoptosis. Turandot proteins bind to host cell membranes and mask negatively charged phospholipids, protecting them from cationic pore-forming AMPs. Collectively, these data demonstrate that Turandot stress proteins mitigate AMP cytotoxicity to host tissues and therefore improve their efficacy.

Beyond the coupled distortion model: structural analysis of the single domain cupredoxin AcoP, a green mononuclear copper centre with original features.

Cupredoxins are widely occurring copper-binding proteins with a typical Greek-key beta barrel fold. They are generally described as electron carriers that rely on a T1 copper centre coordinated by four ligands provided by the folded polypeptide. The discovery of novel cupredoxins demonstrates the high diversity of this family, with variations in terms of copper-binding ligands, copper centre geometry, redox potential, as well as biological function. AcoP is a periplasmic cupredoxin belonging to the iron respiratory chain of the acidophilic bacterium Acidithiobacillus ferrooxidans. AcoP presents original features, including high resistance to acidic pH and a constrained green-type copper centre of high redox potential. To understand the unique properties of AcoP, we undertook structural and biophysical characterization of wild-type AcoP and of two Cu-ligand mutants (H166A and M171A). The crystallographic structures, including native reduced AcoP at 1.65 Å resolution, unveil a typical cupredoxin fold. The presence of extended loops, never observed in previously characterized cupredoxins, might account for the interaction of AcoP with physiological partners. The Cu-ligand distances, determined by both X-ray diffraction and EXAFS, show that the AcoP metal centre seems to present both T1 and T1.5 features, in turn suggesting that AcoP might not fit well to the coupled distortion model. The crystal structures of two AcoP mutants confirm that the active centre of AcoP is highly constrained. Comparative analysis with other cupredoxins of known structures, suggests that in AcoP the second coordination sphere might be an important determinant of active centre rigidity due to the presence of an extensive hydrogen bond network. Finally, we show that other cupredoxins do not perfectly follow the coupled distortion model as well, raising the suspicion that further alternative models to describe copper centre geometries need to be developed, while the importance of rack-induced contributions should not be underestimated.

Structural mechanism of mitochondrial membrane remodelling by human OPA1.

Distinct morphologies of the mitochondrial network support divergent metabolic and regulatory processes that determine cell function and fate1-3. The mechanochemical GTPase optic atrophy 1 (OPA1) influences the architecture of cristae and catalyses the fusion of the mitochondrial inner membrane4,5. Despite its fundamental importance, the molecular mechanisms by which OPA1 modulates mitochondrial morphology are unclear. Here, using a combination of cellular and structural analyses, we illuminate the molecular mechanisms that are key to OPA1-dependent membrane remodelling and fusion. Human OPA1 embeds itself into cardiolipin-containing membranes through a lipid-binding paddle domain. A conserved loop within the paddle domain inserts deeply into the bilayer, further stabilizing the interactions with cardiolipin-enriched membranes. OPA1 dimerization through the paddle domain promotes the helical assembly of a flexible OPA1 lattice on the membrane, which drives mitochondrial fusion in cells. Moreover, the membrane-bending OPA1 oligomer undergoes conformational changes that pull the membrane-inserting loop out of the outer leaflet and contribute to the mechanics of membrane remodelling. Our findings provide a structural framework for understanding how human OPA1 shapes mitochondrial morphology and show us how human disease mutations compromise OPA1 functions.

Protein target highlights in CASP15: Analysis of models by structure providers.

We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the submitted predictions. While the overall ability to predict three-dimensional protein structures continues to impress, reproducing uncommon features not previously observed in experimental structures is still a challenge. Furthermore, instances with conformational flexibility and large multimeric complexes highlight the need for novel scoring strategies to better emphasize biologically relevant structural regions. Looking ahead, closer integration of computational and experimental techniques will play a key role in determining the next challenges to be unraveled in the field of structural molecular biology.

PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces.

Proteins are essential molecular building blocks of life, responsible for most biological functions as a result of their specific molecular interactions. However, predicting their  binding  interfaces remains a challenge. In this study, we present a geometric transformer that acts directly on atomic coordinates labeled only with element names. The resulting model-the Protein Structure Transformer, PeSTo-surpasses the current state of the art in predicting protein-protein interfaces and can also predict and differentiate between interfaces involving nucleic acids, lipids, ions, and small molecules with high confidence. Its low computational cost enables processing high volumes of structural data, such as molecular dynamics ensembles allowing for the discovery of interfaces that remain otherwise inconspicuous in static experimentally solved structures. Moreover, the growing foldome provided by de novo structural predictions can be easily analyzed, providing new opportunities to uncover unexplored biology.

Sustainable Refining of Vegetable Oil Made Easy with a Designer Phospholipase C Enzyme.

The increasing demand pressures the vegetable oil industry to develop novel refining methods. Degumming with type C phospholipases (PLCs) is a green technology and provides extra oil. However, natural PLCs are not active under the harsh conditions used in oil refining plants, requiring additional unit operations. These upfront capital expenditures and the associated operational costs hinder the adoption of this method. Here, we present a process based on ChPLC, a synthetic PLC obtained by consensus sequence design, possessing superior thermal stability and catalytic properties. Using ChPLC, crude soybean oil degumming was completed at 80 °C in 30 min, the temperature and residence time imposed by the design of existing oil refining plants. Remarkably, an extra yield of oil of 2% was obtained using 60% of the dose recommended for PLCs marketed today, saving upfront investments and reducing the operational cost of degumming. A techno-economic analysis indicates that, for medium size plants, ChPLC reduces the overall cost of soybean oil enzymatic degumming by 58%. The process presented here facilitates the implementation of enzymatic technologies to oil producers, regardless of their processing capacity, bringing potential annual benefits in the billion-dollar range for the global economy.

CERT1 mutations perturb human development by disrupting sphingolipid homeostasis.

Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome.

Dynamics of CLIMP-63 S-acylation control ER morphology.

The complex architecture of the endoplasmic reticulum (ER) comprises distinct dynamic features, many at the nanoscale, that enable the coexistence of the nuclear envelope, regions of dense sheets and a branched tubular network that spans the cytoplasm. A key player in the formation of ER sheets is cytoskeleton-linking membrane protein 63 (CLIMP-63). The mechanisms by which CLIMP-63 coordinates ER structure remain elusive. Here, we address the impact of S-acylation, a reversible post-translational lipid modification, on CLIMP-63 cellular distribution and function. Combining native mass-spectrometry, with kinetic analysis of acylation and deacylation, and data-driven mathematical modelling, we obtain in-depth understanding of the CLIMP-63 life cycle. In the ER, it assembles into trimeric units. These occasionally exit the ER to reach the plasma membrane. However, the majority undergoes S-acylation by ZDHHC6 in the ER where they further assemble into highly stable super-complexes. Using super-resolution microscopy and focused ion beam electron microscopy, we show that CLIMP-63 acylation-deacylation controls the abundance and fenestration of ER sheets. Overall, this study uncovers a dynamic lipid post-translational regulation of ER architecture.

Structure and functionality of a multimeric human COQ7:COQ9 complex.

Coenzyme Q (CoQ) is a redox-active lipid essential for core metabolic pathways and antioxidant defense. CoQ is synthesized upon the mitochondrial inner membrane by an ill-defined "complex Q" metabolon. Here, we present structure-function analyses of a lipid-, substrate-, and NADH-bound complex comprising two complex Q subunits: the hydroxylase COQ7 and the lipid-binding protein COQ9. We reveal that COQ7 adopts a ferritin-like fold with a hydrophobic channel whose substrate-binding capacity is enhanced by COQ9. Using molecular dynamics, we further show that two COQ7:COQ9 heterodimers form a curved tetramer that deforms the membrane, potentially opening a pathway for the CoQ intermediates to translocate from the bilayer to the proteins' lipid-binding sites. Two such tetramers assemble into a soluble octamer with a pseudo-bilayer of lipids captured within. Together, these observations indicate that COQ7 and COQ9 cooperate to access hydrophobic precursors within the membrane and coordinate subsequent synthesis steps toward producing CoQ.

Online tools to easily build virtual molecular models for display in augmented and virtual reality on the web.

Several groups developed in the last years augmented and virtual reality (AR/VR) software to visualize 3D molecules, most rather static, limited in content, and requiring software installs, some even requiring expensive hardware. We launched in 2020 moleculARweb (https://molecularweb.epfl.ch), a website that offers interactive content for chemistry and structural biology education through commodity web-based AR that works on consumer devices like smartphones, tablets and laptops. Among thousands of users, teachers increasingly request more biological macromolecules to be available, a demand that we cannot address individually. Therefore, to allow users to build their own material, we built a web interface where they can create online AR experiences in few steps starting from Protein Data Bank, AlphaFold or custom uploaded structures, or from virtual objects/scenes exported from the Visual Molecular Dynamics program, without any programming knowledge. The web tool also returns WebXR sessions for viewing and manipulating the models in WebXR-compatible devices including smartphones, tablets, and also immersive VR headsets with WebXR-capable browsers, where models can be manipulated even with bare hands when supported by the device. The tool is accessible for free at https://molecularweb.epfl.ch/pages/pdb2ar.html.

Visualization, Interactive Handling and Simulation of Molecules in Commodity Augmented Reality in Web Browsers Using moleculARweb's Virtual Modeling Kits.

moleculARweb (https://molecularweb.epfl.ch) began as a website for education and outreach in chemistry and structural biology through augmented reality (AR) content that runs in the web browsers of regular devices like smartphones, tablets, and computers. Here we present two evolutions of moleculARweb's Virtual Modeling Kits (VMK), tools where users can build and view molecules, and explore their mechanics, in 3D AR by handling the molecules in full 3D with custom-printed cube markers (VMK 2.0) or by moving around a simulated scene with mouse or touch gestures (VMK 3.0). Upon simulation the molecules experience visually realistic torsions, clashes, and hydrogen-bonding interactions that the user can manually switch on and off to explore their effects. Moreover, by manually tuning a fictitious temperature the users can accelerate conformational transitions or 'freeze' specific conformations for careful inspection in 3D. Even some phase transitions and separations can be simulated. We here showcase these and other features of the new VMKs connecting them to possible specific applications to teaching and self-learning of concepts from general, organic, biological and physical chemistry; and in assisting with small tasks in molecular modelling for research. Last, in a short discussion section we overview what future developments are needed for the 'dream tool' for the future of chemistry education and work.

How Technologies Assisted Science Learning at Home During the COVID-19 Pandemic.

As most other aspects of life, education was strongly affected by the lockdowns imposed to slow down the spread of the COVID-19 pandemic. Teachers at all levels of education suddenly faced the challenge of adapting their courses to online versions. This posed various problems, from the pedagogical and psychological components of having to teach and learn online to the technical problems of internet connectivity and especially of rethinking hands-on activities. The latter point was especially important for subjects who involve very practical learning, for which teachers had to find out alternative activities that the students could carry out at home. In the subjects dealing with natural sciences, impaired access to instrumentation and reagents was a major limitation, but the community turned out very resourceful. Here I demonstrate this resourcefulness for the case of undergraduate chemistry and biology courses, focusing on how do-it-yourself open technologies, smartphone-based instruments and simulations, at-home chemistry with household reagents, online video material, and introductory programming and bioinformatics, which helped to overcome these difficult times and likely even shape the future of science education.

S-acylation controls SARS-CoV-2 membrane lipid organization and enhances infectivity.

SARS-CoV-2 virions are surrounded by a lipid bilayer that contains membrane proteins such as spike, responsible for target-cell binding and virus fusion. We found that during SARS-CoV-2 infection, spike becomes lipid modified, through the sequential action of the S-acyltransferases ZDHHC20 and 9. Particularly striking is the rapid acylation of spike on 10 cytosolic cysteines within the ER and Golgi. Using a combination of computational, lipidomics, and biochemical approaches, we show that this massive lipidation controls spike biogenesis and degradation, and drives the formation of localized ordered cholesterol and sphingolipid-rich lipid nanodomains in the early Golgi, where viral budding occurs. Finally, S-acylation of spike allows the formation of viruses with enhanced fusion capacity. Our study points toward S-acylating enzymes and lipid biosynthesis enzymes as novel therapeutic anti-viral targets.

Investigating Crosstalk Among PTMs Provides Novel Insight Into the Structural Basis Underlying the Differential Effects of Nt17 PTMs on Mutant Httex1 Aggregation.

Post-translational modifications (PTMs) within the first 17 amino acids (Nt17) of the Huntingtin protein (Htt) have been shown to inhibit the aggregation and attenuate the toxicity of mutant Htt proteins in vitro and in various models of Huntington's disease. Here, we expand on these studies by investigating the effect of methionine eight oxidation (oxM8) and its crosstalk with lysine 6 acetylation (AcK6) or threonine 3 phosphorylation (pT3) on the aggregation of mutant Httex1 (mHttex1). We show that M8 oxidation delays but does not inhibit the aggregation and has no effect on the final morphologies of mHttex1aggregates. The presence of both oxM8 and AcK6 resulted in dramatic inhibition of Httex1 fibrillization. Circular dichroism spectroscopy and molecular dynamics simulation studies show that PTMs that lower the mHttex1 aggregation rate (oxM8, AcK6/oxM8, pT3, pT3/oxM8, and pS13) result in increased population of a short N-terminal helix (first eight residues) in Nt17 or decreased abundance of other helical forms, including long helix and short C-terminal helix. PTMs that did not alter the aggregation rate (AcK6) of mHttex1 exhibit a similar distribution of helical conformation as the unmodified peptides. These results show that the relative abundance of N- vs. C-terminal helical conformations and long helices, rather than the overall helicity of Nt17, better explains the effect of different Nt17 PTMs on mHttex1; thus, explaining the lack of correlation between the effect of PTMs on the overall helicity of Nt17 and mHttex1 aggregation in vitro. Taken together, our results provide novel structural insight into the differential effects of single PTMs and crosstalk between different PTMs in regulating mHttex1 aggregation.

3D architecture and structural flexibility revealed in the subfamily of large glutamate dehydrogenases by a mycobacterial enzyme.

Glutamate dehydrogenases (GDHs) are widespread metabolic enzymes that play key roles in nitrogen homeostasis. Large glutamate dehydrogenases composed of 180 kDa subunits (L-GDHs180) contain long N- and C-terminal segments flanking the catalytic core. Despite the relevance of L-GDHs180 in bacterial physiology, the lack of structural data for these enzymes has limited the progress of functional studies. Here we show that the mycobacterial L-GDH180 (mL-GDH180) adopts a quaternary structure that is radically different from that of related low molecular weight enzymes. Intersubunit contacts in mL-GDH180 involve a C-terminal domain that we propose as a new fold and a flexible N-terminal segment comprising ACT-like and PAS-type domains that could act as metabolic sensors for allosteric regulation. These findings uncover unique aspects of the structure-function relationship in the subfamily of L-GDHs.

Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures.

Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the limitations of prediction methods and of the datasets used to train them, which result in low reliability for actual applications despite globally capturing trends. Here, we review these and other issues by analyzing one of the most detailed, carefully curated datasets of melting temperature change (ΔTm) upon mutation for proteins with high-resolution structures. After examining the composition of this dataset to discuss imbalances and biases, we inspect several of its entries assisted by an online app for data navigation and structure display and aided by a neural network that predicts ΔTm with accuracy close to that of programs available to this end. We pose that the ΔTm predictions of our network, and also likely those of other programs, account only for a baseline-like general effect of each type of amino acid substitution which then requires substantial corrections to reproduce the actual stability changes. The corrections are very different for each specific case and arise from fine structural details which are not well represented in the dataset and which, despite appearing reasonable upon visual inspection of the structures, are hard to encode and parametrize. Based on these observations, additional analyses, and a review of recent literature, we propose recommendations for developers of stability prediction methods and for efforts aimed at improving the datasets used for training. We leave our interactive interface for analysis available online at http://lucianoabriata.altervista.org/papersdata/proteinstability2021/s1626navigation.html so that users can further explore the dataset and baseline predictions, possibly serving as a tool useful in the context of structural biology and protein biotechnology research and as material for education in protein biophysics.

A minimalistic cyclic ice-binding peptide from phage display.

Developing molecules that emulate the properties of naturally occurring ice-binding proteins (IBPs) is a daunting challenge. Rather than relying on the (limited) existing structure-property relationships that have been established for IBPs, here we report the use of phage display for the identification of short peptide mimics of IBPs. To this end, an ice-affinity selection protocol is developed, which enables the selection of a cyclic ice-binding peptide containing just 14 amino acids. Mutational analysis identifies three residues, Asp8, Thr10 and Thr14, which are found to be essential for ice binding. Molecular dynamics simulations reveal that the side chain of Thr10 hydrophobically binds to ice revealing a potential mechanism. To demonstrate the biotechnological potential of this peptide, it is expressed as a fusion ('Ice-Tag') with mCherry and used to purify proteins directly from cell lysate.

Assessment of transferable forcefields for protein simulations attests improved description of disordered states and secondary structure propensities, and hints at multi-protein systems as the next challenge for optimization.

Continuous assessment of transferable forcefields for molecular simulations is essential to identify their weaknesses and direct improvement efforts. The latest efforts focused on better describing disordered proteins while retaining proper description of folded domains, important because forcefields of the previous generations produce overly compact disordered states. Such improvements should additionally alleviate the related problem of over-stabilized protein-protein interactions, which has been largely overlooked. Here we evaluated three state-of-the-art forcefields, current flagships of their respective developers, optimized for ordered and disordered proteins: CHARMM36m with its recommended corrected TIP3P* water, ff19SB with the recommended OPC water, and the 2019 a99SBdisp forcefield by D. E. Shaw Research with its modified TIP4P water; plus ff14SB with TIP3P as an example of the former generation of forcefields. Our evaluation entailed simulations of (i) multiple copies of a protein that is highly soluble yet undergoes weak dimerization, (ii) a disordered peptide with low, well-characterized alpha helical propensity, and (iii) a peptide known to form insoluble ß-aggregates. Our results recapitulate ff14SB-TIP3P over-stabilizing aggregates and secondary structures and place a99SBdisp-TIP4PD at the other end i.e. predicting overly weak intermolecular interactions despite reasonably predicting secondary structure propensities. In-between, CHARMM36m-TIP3P* still over-stabilizes aggregates but predicts residue-wise alpha helical propensities in solution slightly better than ff19SB-OPC, while ff19SB-OPC poses the best prediction of weak dimerization of the soluble protein still predicting aggregation of the ß-peptides. This independent assessment shows that the claimed forcefield improvements are real, but also that a right balance between noncovalent attraction and repulsion has not yet been reached. We thus propose developers to consider systems like those tested here in their forcefield tuning protocols. Last, the good performance of CHARMM36m-TIP3P* further shows that tuning 3-point water models might still be an alternative to the more costly 4-point models like OPC and TIP4PD.

State-of-the-art web services for de novo protein structure prediction.

Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent in the last round of the Critical Assessment of Structure Prediction (CASP), which presented several very good models for the hardest targets. Unfortunately, literature reporting on these advances often lacks digests tailored to lay end users; moreover, some of the top-ranking predictors do not provide webservers that can be used by nonexperts. How can then end users benefit from these advances and correctly interpret the predicted models? Here we review the web resources that biologists can use today to take advantage of these state-of-the-art methods in their research, including not only the best de novo modeling servers but also datasets of models precomputed by experts for structurally uncharacterized protein families. We highlight their features, advantages and pitfalls for predicting structures of proteins without clear templates. We present a broad number of applications that span from driving forward biochemical investigations that lack experimental structures to actually assisting experimental structure determination in X-ray diffraction, cryo-EM and other forms of integrative modeling. We also discuss issues that must be considered by users yet still require further developments, such as global and residue-wise model quality estimates and sources of residue coevolution other than monomeric tertiary structure.

Bottom-up de novo design of functional proteins with complex structural features.

De novo protein design has enabled the creation of new protein structures. However, the design of functional proteins has proved challenging, in part due to the difficulty of transplanting structurally complex functional sites to available protein structures. Here, we used a bottom-up approach to build de novo proteins tailored to accommodate structurally complex functional motifs. We applied the bottom-up strategy to successfully design five folds for four distinct binding motifs, including a bifunctionalized protein with two motifs. Crystal structures confirmed the atomic-level accuracy of the computational designs. These de novo proteins were functional as components of biosensors to monitor antibody responses and as orthogonal ligands to modulate synthetic signaling receptors in engineered mammalian cells. Our work demonstrates the potential of bottom-up approaches to accommodate complex structural motifs, which will be essential to endow de novo proteins with elaborate biochemical functions, such as molecular recognition or catalysis.