Bat coronaviruses related to SARS-CoV-2 and infectious for human cells.

The animal reservoir of SARS-CoV-2 is unknown despite reports of SARS-CoV-2-related viruses in Asian Rhinolophus bats1-4, including the closest virus from R. affinis, RaTG13 (refs. 5,6), and pangolins7-9. SARS-CoV-2 has a mosaic genome, to which different progenitors contribute. The spike sequence determines the binding affinity and accessibility of its receptor-binding domain to the cellular angiotensin-converting enzyme 2 (ACE2) receptor and is responsible for host range10-12. SARS-CoV-2 progenitor bat viruses genetically close to SARS-CoV-2 and able to enter human cells through a human ACE2 (hACE2) pathway have not yet been identified, although they would be key in understanding the origin of the epidemic. Here we show that such viruses circulate in cave bats living in the limestone karstic terrain in northern Laos, in the Indochinese peninsula. We found that the receptor-binding domains of these viruses differ from that of SARS-CoV-2 by only one or two residues at the interface with ACE2, bind more efficiently to the hACE2 protein than that of the SARS-CoV-2 strain isolated in Wuhan from early human cases, and mediate hACE2-dependent entry and replication in human cells, which is inhibited by antibodies that neutralize SARS-CoV-2. None of these bat viruses contains a furin cleavage site in the spike protein. Our findings therefore indicate that bat-borne SARS-CoV-2-like viruses that are potentially infectious for humans circulate in Rhinolophus spp. in the Indochinese peninsula.

Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets.

SUMMARY: Protein Interaction Explorer (PIE) is a new web-based tool integrated to our database iPPI-DB, specifically crafted to support structure-based drug discovery initiatives focused on protein-protein interactions (PPIs). Drawing upon extensive structural data encompassing thousands of heterodimer complexes, including those with successful ligands, PIE provides a comprehensive suite of tools dedicated to aid decision-making in PPI drug discovery. PIE enables researchers/bioinformaticians to identify and characterize crucial factors such as the presence of binding pockets or functional binding sites at the interface, predicting hot spots, and foreseeing similar protein-embedded pockets for potential repurposing efforts. AVAILABILITY AND IMPLEMENTATION: PIE is user-friendly and readily accessible at https://ippidb.pasteur.fr/targetcentric/. It relies on the NGL visualizer.

Acinetobacter type VI secretion system comprises a non-canonical membrane complex.

A. baumannii can rapidly acquire new resistance mechanisms and persist on abiotic surface, enabling the colonization of asymptomatic human host. In Acinetobacter the type VI secretion system (T6SS) is involved in twitching, surface motility and is used for interbacterial competition allowing the bacteria to uptake DNA. A. baumannii possesses a T6SS that has been well studied for its regulation and specific activity, but little is known concerning its assembly and architecture. The T6SS nanomachine is built from three architectural sub-complexes. Unlike the baseplate (BP) and the tail-tube complex (TTC), which are inherited from bacteriophages, the membrane complex (MC) originates from bacteria. The MC is the most external part of the T6SS and, as such, is subjected to evolution and adaptation. One unanswered question on the MC is how such a gigantesque molecular edifice is inserted and crosses the bacterial cell envelope. The A. baumannii MC lacks an essential component, the TssJ lipoprotein, which anchors the MC to the outer membrane. In this work, we studied how A. baumannii compensates the absence of a TssJ. We have characterized for the first time the A. baumannii's specific T6SS MC, its unique characteristic, its membrane localization, and assembly dynamics. We also defined its composition, demonstrating that its biogenesis employs three Acinetobacter-specific envelope-associated proteins that define an intricate network leading to the assembly of a five-proteins membrane super-complex. Our data suggest that A. baumannii has divided the function of TssJ by (1) co-opting a new protein TsmK that stabilizes the MC and by (2) evolving a new domain in TssM for homo-oligomerization, a prerequisite to build the T6SS channel. We believe that the atypical species-specific features we report in this study will have profound implication in our understanding of the assembly and evolutionary diversity of different T6SSs, that warrants future investigation.

Structure and Dynamics of Type 4a Pili and Type 2 Secretion System Endopili.

Within the highly diverse type four filament (TFF or T4F) superfamily, the machineries of type IVa pili (T4aP) and the type 2 secretion system (T2SS) in diderm bacteria exhibit a substantial sequence similarity despite divergent functions and distinct appearances: T4aP can extend micrometers beyond the outer membrane, whereas the endopili in the T2SS are restricted to the periplasm. The determination of the structure of individual components and entire filaments is crucial to understand how their structure enables them to serve different functions. However, the dynamics of these filaments poses a challenge for their high-resolution structure determination. This review presents different approaches that have been used to study the structure and dynamics of T4aP and T2SS endopili by means of integrative structural biology, cryo-electron microscopy (cryo-EM), and molecular dynamics simulations. Their conserved features and differences are presented. The non-helical stretch in the long-conserved N-terminal helix which is characteristic of all members of the TFF and the impact of calcium on structure, function, and dynamics of these filaments are discussed in detail.

InDeep: 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions.

MOTIVATION: Protein-protein interactions (PPIs) are key elements in numerous biological pathways and the subject of a growing number of drug discovery projects including against infectious diseases. Designing drugs on PPI targets remains a difficult task and requires extensive efforts to qualify a given interaction as an eligible target. To this end, besides the evident need to determine the role of PPIs in disease-associated pathways and their experimental characterization as therapeutics targets, prediction of their capacity to be bound by other protein partners or modulated by future drugs is of primary importance. RESULTS: We present InDeep, a tool for predicting functional binding sites within proteins that could either host protein epitopes or future drugs. Leveraging deep learning on a curated dataset of PPIs, this tool can proceed to enhanced functional binding site predictions either on experimental structures or along molecular dynamics trajectories. The benchmark of InDeep demonstrates that our tool outperforms state-of-the-art ligandable binding sites predictors when assessing PPI targets but also conventional targets. This offers new opportunities to assist drug design projects on PPIs by identifying pertinent binding pockets at or in the vicinity of PPI interfaces. AVAILABILITY AND IMPLEMENTATION: The tool is available on GitLab at https://gitlab.pasteur.fr/InDeep/InDeep. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bayesian inference of chromatin structure ensembles from population-averaged contact data.

Mounting experimental evidence suggests a role for the spatial organization of chromatin in crucial processes of the cell nucleus such as transcription regulation. Chromosome conformation capture techniques allow us to characterize chromatin structure by mapping contacts between chromosomal loci on a genome-wide scale. The most widespread modality is to measure contact frequencies averaged over a population of cells. Single-cell variants exist, but suffer from low contact numbers and have not yet gained the same resolution as population methods. While intriguing biological insights have already been garnered from ensemble-averaged data, information about three-dimensional (3D) genome organization in the underlying individual cells remains largely obscured because the contact maps show only an average over a huge population of cells. Moreover, computational methods for structure modeling of chromatin have mostly focused on fitting a single consensus structure, thereby ignoring any cell-to-cell variability in the model itself. Here, we propose a fully Bayesian method to infer ensembles of chromatin structures and to determine the optimal number of states in a principled, objective way. We illustrate our approach on simulated data and compute multistate models of chromatin from chromosome conformation capture carbon copy (5C) data. Comparison with independent data suggests that the inferred ensembles represent the underlying sample population faithfully. Harnessing the rich information contained in multistate models, we investigate cell-to-cell variability of chromatin organization into topologically associating domains, thus highlighting the ability of our approach to deliver insights into chromatin organization of great biological relevance.

quicksom: Self-Organizing Maps on GPUs for clustering of molecular dynamics trajectories.

SUMMARY: We implemented the Self-Organizing Maps algorithm running efficiently on GPUs, and also provide several clustering methods of the resulting maps. We provide scripts and a use case to cluster macro-molecular conformations generated by molecular dynamics simulations. AVAILABILITY AND IMPLEMENTATION: The method is available on GitHub and distributed as a pip package.

The iPPI-DB initiative: a community-centered database of protein-protein interaction modulators.

MOTIVATION: One avenue to address the paucity of clinically testable targets is to reinvestigate the druggable genome by tackling complicated types of targets such as Protein-Protein Interactions (PPIs). Given the challenge to target those interfaces with small chemical compounds, it has become clear that learning from successful examples of PPI modulation is a powerful strategy. Freely accessible databases of PPI modulators that provide the community with tractable chemical and pharmacological data, as well as powerful tools to query them, are therefore essential to stimulate new drug discovery projects on PPI targets. RESULTS: Here, we present the new version iPPI-DB, our manually curated database of PPI modulators. In this completely redesigned version of the database, we introduce a new web interface relying on crowdsourcing for the maintenance of the database. This interface was created to enable community contributions, whereby external experts can suggest new database entries. Moreover, the data model, the graphical interface, and the tools to query the database have been completely modernized and improved. We added new PPI modulators, new PPI targets and extended our focus to stabilizers of PPIs as well. AVAILABILITY AND IMPLEMENTATION: The iPPI-DB server is available at https://ippidb.pasteur.fr The source code for this server is available at https://gitlab.pasteur.fr/ippidb/ippidb-web/ and is distributed under GPL licence (http://www.gnu.org/licences/gpl). Queries can be shared through persistent links according to the FAIR data standards. Data can be downloaded from the website as csv files. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Structural determination of Streptococcus pyogenes M1 protein interactions with human immunoglobulin G using integrative structural biology.

Streptococcus pyogenes (Group A streptococcus; GAS) is an important human pathogen responsible for mild to severe, life-threatening infections. GAS expresses a wide range of virulence factors, including the M family proteins. The M proteins allow the bacteria to evade parts of the human immune defenses by triggering the formation of a dense coat of plasma proteins surrounding the bacteria, including IgGs. However, the molecular level details of the M1-IgG interaction have remained unclear. Here, we characterized the structure and dynamics of this interaction interface in human plasma on the surface of live bacteria using integrative structural biology, combining cross-linking mass spectrometry and molecular dynamics (MD) simulations. We show that the primary interaction is formed between the S-domain of M1 and the conserved IgG Fc-domain. In addition, we show evidence for a so far uncharacterized interaction between the A-domain and the IgG Fc-domain. Both these interactions mimic the protein G-IgG interface of group C and G streptococcus. These findings underline a conserved scavenging mechanism used by GAS surface proteins that block the IgG-receptor (FcγR) to inhibit phagocytic killing. We additionally show that we can capture Fab-bound IgGs in a complex background and identify XLs between the constant region of the Fab-domain and certain regions of the M1 protein engaged in the Fab-mediated binding. Our results elucidate the M1-IgG interaction network involved in inhibition of phagocytosis and reveal important M1 peptides that can be further investigated as future vaccine targets.

ARIAweb: a server for automated NMR structure calculation.

Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.

Enzymatic and Molecular Characterization of Anti-Leishmania Molecules That Differently Target Leishmania and Mammalian eIF4A Proteins, LieIF4A and eIF4AMus.

Previous investigations of the Leishmania infantum eIF4A-like protein (LieIF4A) as a potential drug target delivered cholestanol derivatives inhibitors. Here, we investigated the mode of action of cholesterol derivatives as a novel scaffold structure of LieIF4A inhibitors on the RNA-dependent ATPase activity of LieIF4A and its mammalian ortholog (eIF4AI). We compared their biochemical effects on RNA-dependent ATPase activities of both proteins and investigated if rocaglamide, a known inhibitor of eIF4A, could affect LieIF4A as well. Kinetic measurements were conducted at different concentrations of ATP, of the compound and in the presence of saturating whole yeast RNA concentrations. Kinetic analyses showed different ATP binding affinities for the two enzymes as well as different sensitivities to 7-α-aminocholesterol and rocaglamide. The 7-α-aminocholesterol inhibited LieIF4A with a higher binding affinity relative to cholestanol analogs. Cholesterol, another tested sterol, had no effect on the ATPase activity of LieIF4A or eIF4AI. The 7-α-aminocholesterol demonstrated an anti-Leishmania activity on L. infantum promastigotes. Additionally, docking simulations explained the importance of the double bond between C5 and C6 in 7-α-aminocholesterol and the amino group in the C7 position. In conclusion, Leishmania and mammalian eIF4A proteins appeared to interact differently with effectors, thus making LieIF4A a potential drug against leishmaniases.

Structure and function of minor pilins of type IV pili.

Type IV pili are versatile and highly flexible fibers formed on the surface of many Gram-negative and Gram-positive bacteria. Virulence and infection rate of several pathogenic bacteria, such as Neisseria meningitidis and Pseudomonas aeruginosa, are strongly dependent on the presence of pili as they facilitate the adhesion of the bacteria to the host cell. Disruption of the interactions between the pili and the host cells by targeting proteins involved in this interaction could, therefore, be a treatment strategy. A type IV pilus is primarily composed of multiple copies of protein subunits called major pilins. Additional proteins, called minor pilins, are present in lower abundance, but are essential for the assembly of the pilus or for its specific functions. One class of minor pilins is required to initiate the formation of pili, and may form a complex similar to that identified in the related type II secretion system. Other, species-specific minor pilins in the type IV pilus system have been shown to promote additional functions such as DNA binding, aggregation and adherence. Here, we will review the structure and the function of the minor pilins from type IV pili.

Sequence-specific DNA binding activity of the cross-brace zinc finger motif of the piggyBac transposase.

The piggyBac transposase (PB) is distinguished by its activity and utility in genome engineering, especially in humans where it has highly promising therapeutic potential. Little is known, however, about the structure-function relationships of the different domains of PB. Here, we demonstrate in vitro and in vivo that its C-terminal Cysteine-Rich Domain (CRD) is essential for DNA breakage, joining and transposition and that it binds to specific DNA sequences in the left and right transposon ends, and to an additional unexpectedly internal site at the left end. Using NMR, we show that the CRD adopts the specific fold of the cross-brace zinc finger protein family. We determine the interaction interfaces between the CRD and its target, the 5'-TGCGT-3'/3'-ACGCA-5' motifs found in the left, left internal and right transposon ends, and use NMR results to propose docking models for the complex, which are consistent with our site-directed mutagenesis data. Our results provide support for a model of the PB/DNA interactions in the context of the transpososome, which will be useful for the rational design of PB mutants with increased activity.

Target Engagement and Binding Mode of an Antituberculosis Drug to Its Bacterial Target Deciphered in Whole Living Cells by NMR.

Detailed information on hit-target interaction is very valuable for drug discovery efforts and indispensable for rational hit to lead optimization. We developed a new approach combining NMR in whole-cells in-cell NMR) and docking to characterize hit-target interaction at the atomic level. By using in-cell NMR, we validated target engagement of the antituberculosis imidazopyridine amide (IPA) series with the subunit b of the cytochrome bc1:aa3, the major respiratory terminal oxidase in mycobacteria. The most advanced IPA called Q203 is currently in clinical trial. Using its derivative IPA317, we identified the atoms of the drug interacting with the cytochrome b in whole cells. NMR data and the self-organizing map algorithm were used to cluster a large set of drug-target complex models. The selected ensemble revealed IPA317 in a transient cavity of the cytochrome b, interacting directly with the residue T313, which is the site of spontaneous mutation conferring resistance to the IPA series. Our approach constitutes a pipeline to obtain atomic information on hit-target interactions in the cellular context.

Dynamics of a type 2 secretion system pseudopilus unraveled by complementary approaches.

Secretion pili, bacterial fibers responsible for transporting proteins to the extracellular milieu in some secretion systems, are very strong structures but at the same time highly flexible. Their flexibility and helical symmetry make structure determination at atomic resolution a challenging task. We have previously used an integrative structural biology approach including liquid-state NMR, cryo-electron microscopy (cryo-EM), and modeling to determine the pseudo-atomic resolution structure of the type 2 secretion system pseudopilus in a mutant form, where we employed NMR to determine the high resolution structure of the pilin (the monomer building block of the pilus). In this work, we determine the pseudo-atomic structure of the wild type pilus, and compare the dynamics of wild type and mutant pili by normal mode analysis. We present a detailed NMR analysis of the dynamics of the pilin in isolation, and compare dynamics and solvent accessibility of isolated and assembled pilins by Hydrogen/Deuterium eXchange Mass Spectrometry (HDX-MS). These complementary approaches provide a comprehensive view of internal and overall dynamics of pili, crucial for their function.

Automated structure modeling of large protein assemblies using crosslinks as distance restraints.

Crosslinking mass spectrometry is increasingly used for structural characterization of multisubunit protein complexes. Chemical crosslinking captures conformational heterogeneity, which typically results in conflicting crosslinks that cannot be satisfied in a single model, making detailed modeling a challenging task. Here we introduce an automated modeling method dedicated to large protein assemblies ('XL-MOD' software is available at http://aria.pasteur.fr/supplementary-data/x-links) that (i) uses a form of spatial restraints that realistically reflects the distribution of experimentally observed crosslinked distances; (ii) automatically deals with ambiguous and/or conflicting crosslinks and identifies alternative conformations within a Bayesian framework; and (iii) allows subunit structures to be flexible during conformational sampling. We demonstrate our method by testing it on known structures and available crosslinking data. We also crosslinked and modeled the 17-subunit yeast RNA polymerase III at atomic resolution; the resulting model agrees remarkably well with recently published cryoelectron microscopy structures and provides additional insights into the polymerase structure.

mkgridXf: Consistent Identification of Plausible Binding Sites Despite the Elusive Nature of Cavities and Grooves in Protein Dynamics.

We describe here a method to identify potential binding sites in ensembles of protein structures as obtained by molecular dynamics simulations. This is a highly important task in the context of structure-based drug discovery, and many methods exist for the much simpler case of static structures. However, during molecular dynamics, the cavities and grooves that are used to define binding sites merge, split, appear, and disappear, and cover a large volume. Combined with the large number of sites (∼105 and more), these characteristics hamper a consistent and comprehensive definition of binding sites. Our method is based on the calculation of instantaneous cavities and of the pockets delineating them. Classification of the pockets over the structure ensemble generates consensus pockets, which define sites. Sites are reported as lists of atoms or residues. This avoids the pitfalls of the classification of cavities by spatial overlap, used in most existing methods, which is bound to fail on nonordered or unaligned ensembles or as soon as significant molecular motions are involved. To achieve a robust and consistent classification, we thoroughly optimized and benchmarked the method. For this, we assembled from the literature a set of reference sites on systems involving significant functional molecular motions. We tested different descriptors, metrics, and clustering methods. The resulting method is able to perform a global analysis of potential sites efficiently. Tests on examples show that our approach can make predictions of potential sites on the whole surface of a protein and identify novel sites absent from static structures.

Minimal NMR distance information for rigidity of protein graphs.

Nuclear Magnetic Resonance (NMR) experiments provide distances between nearby atoms of a protein molecule. The corresponding structure determination problem is to determine the 3D protein structure by exploiting such distances. We present a new order on the atoms of the protein, based on information from the chemistry of proteins and NMR experiments, which allows us to formulate the problem as a combinatorial search. Additionally, this order tells us what kind of NMR distance information is crucial to understand the cardinality of the solution set of the problem and its computational complexity.

Structure of Complement C3(H2O) Revealed By Quantitative Cross-Linking/Mass Spectrometry And Modeling.

The slow but spontaneous and ubiquitous formation of C3(H2O), the hydrolytic and conformationally rearranged product of C3, initiates antibody-independent activation of the complement system that is a key first line of antimicrobial defense. The structure of C3(H2O) has not been determined. Here we subjected C3(H2O) to quantitative cross-linking/mass spectrometry (QCLMS). This revealed details of the structural differences and similarities between C3(H2O) and C3, as well as between C3(H2O) and its pivotal proteolytic cleavage product, C3b, which shares functionally similarity with C3(H2O). Considered in combination with the crystal structures of C3 and C3b, the QCMLS data suggest that C3(H2O) generation is accompanied by the migration of the thioester-containing domain of C3 from one end of the molecule to the other. This creates a stable C3b-like platform able to bind the zymogen, factor B, or the regulator, factor H. Integration of available crystallographic and QCLMS data allowed the determination of a 3D model of the C3(H2O) domain architecture. The unique arrangement of domains thus observed in C3(H2O), which retains the anaphylatoxin domain (that is excised when C3 is enzymatically activated to C3b), can be used to rationalize observed differences between C3(H2O) and C3b in terms of complement activation and regulation.