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.

Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore.

Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. However, only a handful of techniques are available to accurately measure their levels, capture their complexity at a single molecule level, and characterize their multifaceted roles in health and disease. Nanopore sensing provides high sensitivity for the detection of low-abundance proteins, holding the potential to impact single-molecule proteomics and PTM detection, in particular. Here, we demonstrate the ability of a biological nanopore, the pore-forming toxin aerolysin, to detect and distinguish α-synuclein-derived peptides bearing single or multiple PTMs, namely, phosphorylation, nitration, and oxidation occurring at different positions and in various combinations. The characteristic current signatures of the α-synuclein peptide and its PTM variants could be confidently identified by using a deep learning model for signal processing. We further demonstrate that this framework can quantify α-synuclein peptides at picomolar concentrations and detect the C-terminal peptides generated by digestion of full-length α-synuclein. Collectively, our work highlights the advantage of using nanopores as a tool for simultaneous detection of multiple PTMs and facilitates their use in biomarker discovery and diagnostics.

Bicc1 ribonucleoprotein complexes specifying organ laterality are licensed by ANKS6-induced structural remodeling of associated ANKS3.

Organ laterality of vertebrates is specified by accelerated asymmetric decay of Dand5 mRNA mediated by Bicaudal-C1 (Bicc1) on the left side, but whether binding of this or any other mRNA to Bicc1 can be regulated is unknown. Here, we found that a CRISPR-engineered truncation in ankyrin and sterile alpha motif (SAM)-containing 3 (ANKS3) leads to symmetric mRNA decay mediated by the Bicc1-interacting Dand5 3' UTR. AlphaFold structure predictions of protein complexes and their biochemical validation by in vitro reconstitution reveal a novel interaction of the C-terminal coiled coil domain of ANKS3 with Bicc1 that inhibits binding of target mRNAs, depending on the conformation of ANKS3 and its regulation by ANKS6. The dual regulation of RNA binding by mutually opposing structured protein domains in this multivalent protein network emerges as a novel mechanism linking associated laterality defects and possibly other ciliopathies to perturbed dynamics in Bicc1 ribonucleoparticle (RNP) formation.

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.

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.

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.

Biological nanopores for single-molecule sensing.

Evolution has found countless ways to transport material across cells and cellular compartments separated by membranes. Protein assemblies are the cornerstone for the formation of channels and pores that enable this regulated passage of molecules in and out of cells, contributing to maintaining most of the fundamental processes that sustain living organisms. As in several other occasions, we have borrowed from the natural properties of these biological systems to push technology forward and have been able to hijack these nano-scale proteinaceous pores to learn about the physical and chemical features of molecules passing through them. Today, a large repertoire of biological pores is exploited as molecular sensors for characterizing biomolecules that are relevant for the advancement of life sciences and application to medicine. Although the technology has quickly matured to enable nucleic acid sensing with transformative implications for genomics, biological pores stand as some of the most promising candidates to drive the next developments in single-molecule proteomics.

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.

Prolyl endopeptidase-like is a (thio)esterase involved in mitochondrial respiratory chain function.

Deficiency of the serine hydrolase prolyl endopeptidase-like (PREPL) causes a recessive metabolic disorder characterized by neonatal hypotonia, feeding difficulties, and growth hormone deficiency. The pathophysiology of PREPL deficiency and the physiological substrates of PREPL remain largely unknown. In this study, we connect PREPL with mitochondrial gene expression and oxidative phosphorylation by analyzing its protein interactors. We demonstrate that the long PREPLL isoform localizes to mitochondria, whereas PREPLS remains cytosolic. Prepl KO mice showed reduced mitochondrial complex activities and disrupted mitochondrial gene expression. Furthermore, mitochondrial ultrastructure was abnormal in a PREPL-deficient patient and Prepl KO mice. In addition, we reveal that PREPL has (thio)esterase activity and inhibition of PREPL by Palmostatin M suggests a depalmitoylating function. We subsequently determined the crystal structure of PREPL, thereby providing insight into the mechanism of action. Taken together, PREPL is a (thio)esterase rather than a peptidase and PREPLL is involved in mitochondrial homeostasis.

BET1 variants establish impaired vesicular transport as a cause for muscular dystrophy with epilepsy.

BET1 is required, together with its SNARE complex partners GOSR2, SEC22b, and Syntaxin-5 for fusion of endoplasmic reticulum-derived vesicles with the ER-Golgi intermediate compartment (ERGIC) and the cis-Golgi. Here, we report three individuals, from two families, with severe congenital muscular dystrophy (CMD) and biallelic variants in BET1 (P1 p.(Asp68His)/p.(Ala45Valfs*2); P2 and P3 homozygous p.(Ile51Ser)). Due to aberrant splicing and frameshifting, the variants in P1 result in low BET1 protein levels and impaired ER-to-Golgi transport. Since in silico modeling suggested that p.(Ile51Ser) interferes with binding to interaction partners other than SNARE complex subunits, we set off and identified novel BET1 interaction partners with low affinity for p.(Ile51Ser) BET1 protein compared to wild-type, among them ERGIC-53. The BET1/ERGIC-53 interaction was validated by endogenous co-immunoprecipitation with both proteins colocalizing to the ERGIC compartment. Mislocalization of ERGIC-53 was observed in P1 and P2's derived fibroblasts; while in the p.(Ile51Ser) P2 fibroblasts specifically, mutant BET1 was also mislocalized along with ERGIC-53. Thus, we establish BET1 as a novel CMD/epilepsy gene and confirm the emerging role of ER/Golgi SNAREs in CMD.

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.

Specific Protein-Membrane Interactions Promote Packaging of Metallo-ß-Lactamases into Outer Membrane Vesicles.

Outer membrane vesicles (OMVs) act as carriers of bacterial products such as plasmids and resistance determinants, including metallo-ß-lactamases. The lipidated, membrane-anchored metallo-ß-lactamase NDM-1 can be detected in Gram-negative OMVs. The soluble domain of NDM-1 also forms electrostatic interactions with the membrane. Here, we show that these interactions promote its packaging into OMVs produced by Escherichia coli. We report that favorable electrostatic protein-membrane interactions are also at work in the soluble enzyme IMP-1 while being absent in VIM-2. These interactions correlate with an enhanced incorporation of IMP-1 compared to VIM-2 into OMVs. Disruption of these interactions in NDM-1 and IMP-1 impairs their inclusion into vesicles, confirming their role in defining the protein cargo in OMVs. These results also indicate that packaging of metallo-ß-lactamases into vesicles in their active form is a common phenomenon that involves cargo selection based on specific molecular interactions.

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.

Palmitoylated acyl protein thioesterase APT2 deforms membranes to extract substrate acyl chains.

Many biochemical reactions require controlled recruitment of proteins to membranes. This is largely regulated by posttranslational modifications. A frequent one is S-acylation, which consists of the addition of acyl chains and can be reversed by poorly understood acyl protein thioesterases (APTs). Using a panel of computational and experimental approaches, we dissect the mode of action of the major cellular thioesterase APT2 (LYPLA2). We show that soluble APT2 is vulnerable to proteasomal degradation, from which membrane binding protects it. Interaction with membranes requires three consecutive steps: electrostatic attraction, insertion of a hydrophobic loop and S-acylation by the palmitoyltransferases ZDHHC3 or ZDHHC7. Once bound, APT2 is predicted to deform the lipid bilayer to extract the acyl chain bound to its substrate and capture it in a hydrophobic pocket to allow hydrolysis. This molecular understanding of APT2 paves the way to understand the dynamics of APT2-mediated deacylation of substrates throughout the endomembrane system.

Extensive tissue-specific expression variation and novel regulators underlying circadian behavior.

Natural genetic variation affects circadian rhythms across the evolutionary tree, but the underlying molecular mechanisms are poorly understood. We investigated population-level, molecular circadian clock variation by generating >700 tissue-specific transcriptomes of Drosophila melanogaster (w1118 ) and 141 Drosophila Genetic Reference Panel (DGRP) lines. This comprehensive circadian gene expression atlas contains >1700 cycling genes including previously unknown central circadian clock components and tissue-specific regulators. Furthermore, >30% of DGRP lines exhibited aberrant circadian gene expression, revealing abundant genetic variation-mediated, intertissue circadian expression desynchrony. Genetic analysis of one line with the strongest deviating circadian expression uncovered a novel cry mutation that, as shown by protein structural modeling and brain immunohistochemistry, disrupts the light-driven flavin adenine dinucleotide cofactor photoreduction, providing in vivo support for the importance of this conserved photoentrainment mechanism. Together, our study revealed pervasive tissue-specific circadian expression variation with genetic variants acting upon tissue-specific regulatory networks to generate local gene expression oscillations.

CLoNe: automated clustering based on local density neighborhoods for application to biomolecular structural ensembles.

MOTIVATION: Proteins are intrinsically dynamic entities. Flexibility sampling methods, such as molecular dynamics or those arising from integrative modeling strategies, are now commonplace and enable the study of molecular conformational landscapes in many contexts. Resulting structural ensembles increase in size as technological and algorithmic advancements take place, making their analysis increasingly demanding. In this regard, cluster analysis remains a go-to approach for their classification. However, many state-of-the-art algorithms are restricted to specific cluster properties. Combined with tedious parameter fine-tuning, cluster analysis of protein structural ensembles suffers from the lack of a generally applicable and easy to use clustering scheme. RESULTS: We present CLoNe, an original Python-based clustering scheme that builds on the Density Peaks algorithm of Rodriguez and Laio. CLoNe relies on a probabilistic analysis of local density distributions derived from nearest neighbors to find relevant clusters regardless of cluster shape, size, distribution and amount. We show its capabilities on many toy datasets with properties otherwise dividing state-of-the-art approaches and improves on the original algorithm in key aspects. Applied to structural ensembles, CLoNe was able to extract meaningful conformations from membrane binding events and ligand-binding pocket opening as well as identify dominant dimerization motifs or inter-domain organization. CLoNe additionally saves clusters as individual trajectories for further analysis and provides scripts for automated use with molecular visualization software. AVAILABILITY AND IMPLEMENTATION: www.epfl.ch/labs/lbm/resources, github.com/LBM-EPFL/CLoNe. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.