Mechanism of action of phthalazinone derivatives against rabies virus.

Rabies, a viral zoonosis, is responsible for almost 59,000 deaths each year, despite the existence of an effective post-exposure prophylaxis. Indeed, rabies causes acute encephalomyelitis, with a case-fatality rate of 100 % after the onset of neurological clinical signs. Therefore, the development of therapies to inhibit the rabies virus (RABV) is crucial. Here, we identified, from a 30,000 compound library screening, phthalazinone derivative compounds as potent inhibitors of RABV infection and more broadly of Lyssavirus and even Mononegavirales infections. Combining in vitro experiments, structural modelling, in silico docking and in vivo assays, we demonstrated that phthalazinone derivatives display a strong inhibition of lyssaviruses infection by acting directly on the replication complex of the virus, and with noticeable effects in delaying the onset of the clinical signs in our mouse model.

AlignScape, displaying sequence similarity using self-organizing maps.

The current richness of sequence data needs efficient methodologies to display and analyze the complexity of the information in a compact and readable manner. Traditionally, phylogenetic trees and sequence similarity networks have been used to display and analyze sequences of protein families. These methods aim to shed light on key computational biology problems such as sequence classification and functional inference. Here, we present a new methodology, AlignScape, based on self-organizing maps. AlignScape is applied to three large families of proteins: the kinases and GPCRs from human, and bacterial T6SS proteins. AlignScape provides a map of the similarity landscape and a tree representation of multiple sequence alignments These representations are useful to display, cluster, and classify sequences as well as identify functional trends. The efficient GPU implementation of AlignScape allows the analysis of large MSAs in a few minutes. Furthermore, we show how the AlignScape analysis of proteins belonging to the T6SS complex can be used to predict coevolving partners.

Building Protein Atomic Models from Cryo-EM Density Maps and Residue Co-Evolution.

Electron cryo-microscopy (cryo-EM) has emerged as a powerful method by which to obtain three-dimensional (3D) structures of macromolecular complexes at atomic or near-atomic resolution. However, de novo building of atomic models from near-atomic resolution (3-5 Å) cryo-EM density maps is a challenging task, in particular because poorly resolved side-chain densities hamper sequence assignment by automatic procedures at a lower resolution. Furthermore, segmentation of EM density maps into individual subunits remains a difficult problem when the structure of the subunits is not known, or when significant conformational rearrangement occurs between the isolated and associated form of the subunits. To tackle these issues, we have developed a graph-based method to thread most of the C-α trace of the protein backbone into the EM density map. The EM density is described as a weighted graph such that the resulting minimum spanning tree encompasses the high-density regions of the map. A pruning algorithm cleans the tree and finds the most probable positions of the C-α atoms, by using side-chain density when available, as a collection of C-α trace fragments. By complementing experimental EM maps with contact predictions from sequence co-evolutionary information, we demonstrate that this approach can correctly segment EM maps into individual subunits and assign amino acid sequences to backbone traces to generate atomic models.

Deciphering the Molecular Interaction Between the Adhesion G Protein-Coupled Receptor ADGRV1 and its PDZ-Containing Regulator PDZD7.

Hearing relies on the transduction of sound-evoked vibrations into electrical signals, occurring in the stereocilia bundle of inner ear hair cells. The G protein-coupled receptor (GPCR) ADGRV1 and the multi-PDZ protein PDZD7 play a critical role in the formation and function of stereocilia through their scaffolding and signaling properties. During hair cell development, the GPCR activity of ADGRV1 is specifically inhibited by PDZD7 through an unknown mechanism. Here, we describe the key interactions mediated by the two N-terminal PDZ domains of PDZD7 and the cytoplasmic domain of ADGRV1. Both PDZ domains can bind to the C-terminal PDZ binding motif (PBM) of ADGRV1 with the critical contribution of atypical C-terminal ß extensions. The two PDZ domains form a supramodule in solution, stabilized upon PBM binding. Interestingly, we showed that the stability and binding properties of the PDZ tandem are affected by two deafness-causing mutations located in the binding grooves of PDZD7 PDZ domains.

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.

CC17 group B Streptococcus exploits integrins for neonatal meningitis development.

Group B Streptococcus (GBS) is the major cause of human neonatal infections. A single clone, designated CC17-GBS, accounts for more than 80% of meningitis cases, the most severe form of the infection. However, the events allowing blood-borne GBS to penetrate the brain remain largely elusive. In this study, we identified the host transmembrane receptors α5ß1 and αvß3 integrins as the ligands of Srr2, a major CC17-GBS-specific adhesin. Two motifs located in the binding region of Srr2 were responsible for the interaction between CC17-GBS and these integrins. We demonstrated in a blood-brain-barrier cellular model that both integrins contributed to the adhesion and internalization of CC17-GBS. Strikingly, both integrins were overexpressed during the postnatal period in the brain vessels of the blood-brain barrier and blood-cerebrospinal fluid barrier and contributed to juvenile susceptibility to CC17 meningitis. Finally, blocking these integrins decreased the ability of CC17-GBS to cross into the CNS of juvenile mice in an in vivo model of meningitis. Our study demonstrated that CC17-GBS exploits integrins in order to cross the brain vessels, leading to meningitis. Importantly, it provides host molecular insights into neonate's susceptibility to CC17-GBS meningitis, thereby opening new perspectives for therapeutic and prevention strategies of GBS-elicited meningitis.

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.

Quantitative Structural Interpretation of Protein Crosslinks.

Chemical crosslinking, combined with mass spectrometry analysis, is a key source of information for characterizing the structure of large protein assemblies, in the context of molecular modeling. In most approaches, the interpretation is limited to simple spatial restraints, neglecting physico-chemical interactions between the crosslinker and the protein and their flexibility. Here we present a method, named NRGXL (new realistic grid for crosslinks), which models the flexibility of the crosslinker and the linked side-chains, by explicitly sampling many conformations. Also, the method can efficiently deal with overall protein dynamics. This method creates a physical model of the crosslinker and associated energy. A classifier based on it outperforms others, based on Euclidean distance or solvent-accessible distance and its efficiency makes it usable for validating 3D models from crosslinking data. NRGXL is freely available as a web server at: https://nrgxl.pasteur.fr.

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.

Conformational sampling of CpxA: Connecting HAMP motions to the histidine kinase function.

In the histidine kinase family, the HAMP and DHp domains are considered to play an important role into the transmission of signal arising from environmental conditions to the auto-phosphorylation site and to the binding site of response regulator. Several conformational motions inside HAMP have been proposed to transmit this signal: (i) the gearbox model, (ii) α helices rotations, pistons and scissoring, (iii) transition between ordered and disordered states. In the present work, we explore by temperature-accelerated molecular dynamics (TAMD), an enhanced sampling technique, the conformational space of the cytoplasmic region of histidine kinase CpxA. Several HAMP motions, corresponding to α helices rotations, pistoning and scissoring have been detected and correlated to the segmental motions of HAMP and DHp domains of CpxA.

Biogenesis and structure of a type VI secretion baseplate.

To support their growth in a competitive environment and cause pathogenesis, bacteria have evolved a broad repertoire of macromolecular machineries to deliver specific effectors and toxins. Among these multiprotein complexes, the type VI secretion system (T6SS) is a contractile nanomachine that targets both prokaryotic and eukaryotic cells. The T6SS comprises two functional subcomplexes: a bacteriophage-related tail structure anchored to the cell envelope by a membrane complex. As in other contractile injection systems, the tail is composed of an inner tube wrapped by a sheath and built on the baseplate. In the T6SS, the baseplate is not only the tail assembly platform, but also docks the tail to the membrane complex and hence serves as an evolutionary adaptor. Here we define the biogenesis pathway and report the cryo-electron microscopy (cryo-EM) structure of the wedge protein complex of the T6SS from enteroaggregative Escherichia coli (EAEC). Using an integrative approach, we unveil the molecular architecture of the whole T6SS baseplate and its interaction with the tail sheath, offering detailed insights into its biogenesis and function. We discuss architectural and mechanistic similarities but also reveal key differences with the T4 phage and Mu phage baseplates.

Ordering Protein Contact Matrices.

Numerous biophysical approaches provide information about residues spatial proximity in proteins. However, correct assignment of the protein fold from this proximity information is not straightforward if the spatially close protein residues are not assigned to residues in the primary sequence. Here, we propose an algorithm to assign such residue numbers by ordering the columns and lines of the raw protein contact matrix directly obtained from proximity information between unassigned amino acids. The ordering problem is formatted as the search of a trail within a graph connecting protein residues through the nonzero contact values. The algorithm performs in two steps: (i) finding the longest trail of the graph using an original dynamic programming algorithm, (ii) clustering the individual ordered matrices using a self-organizing map (SOM) approach. The combination of the dynamic programming and self-organizing map approaches constitutes a quite innovative point of the present work. The algorithm was validated on a set of about 900 proteins, representative of the sizes and proportions of secondary structures observed in the Protein Data Bank. The algorithm was revealed to be efficient for noise levels up to 40%, obtaining average gaps of about 20% at maximum between ordered and initial matrices. The proposed approach paves the ways toward a method of fold prediction from noisy proximity information, as TM scores larger than 0.5 have been obtained for ten randomly chosen proteins, in the case of a noise level of 10%. The methods has been also validated on two experimental cases, on which it performed satisfactorily.

Meet-U: Educating through research immersion.

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.

Identification of novel leishmanicidal molecules by virtual and biochemical screenings targeting Leishmania eukaryotic translation initiation factor 4A.

Leishmaniases are neglected parasitic diseases in spite of the major burden they inflict on public health. The identification of novel drugs and targets constitutes a research priority. For that purpose we used Leishmania infantum initiation factor 4A (LieIF), an essential translation initiation factor that belongs to the DEAD-box proteins family, as a potential drug target. We modeled its structure and identified two potential binding sites. A virtual screening of a diverse chemical library was performed for both sites. The results were analyzed with an in-house version of the Self-Organizing Maps algorithm combined with multiple filters, which led to the selection of 305 molecules. Effects of these molecules on the ATPase activity of LieIF permitted the identification of a promising hit (208) having a half maximal inhibitory concentration (IC50) of 150 ± 15 µM for 1 µM of protein. Ten chemical analogues of compound 208 were identified and two additional inhibitors were selected (20 and 48). These compounds inhibited the mammalian eIF4I with IC50 values within the same range. All three hits affected the viability of the extra-cellular form of L. infantum parasites with IC50 values at low micromolar concentrations. These molecules showed non-significant toxicity toward THP-1 macrophages. Furthermore, their anti-leishmanial activity was validated with experimental assays on L. infantum intramacrophage amastigotes showing IC50 values lower than 4.2 µM. Selected compounds exhibited selectivity indexes between 19 to 38, which reflects their potential as promising anti-Leishmania molecules.

Structural Characterization of Whirlin Reveals an Unexpected and Dynamic Supramodule Conformation of Its PDZ Tandem.

Hearing relies on the transduction of sound-evoked vibrations into electric signals, occurring in the stereocilia bundle of hair cells. The bundle is organized in a staircase pattern formed by rows of packed stereocilia. This architecture is pivotal to transduction and involves a network of scaffolding proteins with hitherto uncharacterized features. Key interactions in this network are mediated by PDZ domains. Here, we describe the architecture of the first two PDZ domains of whirlin, a protein involved in these assemblies and associated with congenital deaf-blindness. C-terminal hairpin extensions of the PDZ domains mediate the transient supramodular assembly, which improves the binding capacity of the first domain. We determined a detailed structural model of the closed conformation of the PDZ tandem and characterized its equilibrium with an ensemble of open conformations. The structural and dynamic behavior of this PDZ tandem provides key insights into the regulatory mechanisms involved in the hearing machinery.

Building Graphs To Describe Dynamics, Kinetics, and Energetics in the d-ALa:d-Lac Ligase VanA.

The d-Ala:d-Lac ligase, VanA, plays a critical role in the resistance of vancomycin. Indeed, it is involved in the synthesis of a peptidoglycan precursor, to which vancomycin cannot bind. The reaction catalyzed by VanA requires the opening of the so-called "ω-loop", so that the substrates can enter the active site. Here, the conformational landscape of VanA is explored by an enhanced sampling approach: the temperature-accelerated molecular dynamics (TAMD). Analysis of the molecular dynamics (MD) and TAMD trajectories recorded on VanA permits a graphical description of the structural and kinetics aspects of the conformational space of VanA, where the internal mobility and various opening modes of the ω-loop play a major role. The other important feature is the correlation of the ω-loop motion with the movements of the opposite domain, defined as containing the residues A149-Q208. Conformational and kinetic clusters have been determined and a path describing the ω-loop opening was extracted from these clusters. The determination of this opening path, as well as the relative importance of hydrogen bonds along the path, permit one to propose some key residue interactions for the kinetics of the ω-loop opening.

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.

Improved large-scale prediction of growth inhibition patterns using the NCI60 cancer cell line panel.

MOTIVATION: Recent large-scale omics initiatives have catalogued the somatic alterations of cancer cell line panels along with their pharmacological response to hundreds of compounds. In this study, we have explored these data to advance computational approaches that enable more effective and targeted use of current and future anticancer therapeutics. RESULTS: We modelled the 50% growth inhibition bioassay end-point (GI50) of 17,142 compounds screened against 59 cancer cell lines from the NCI60 panel (941,831 data-points, matrix 93.08% complete) by integrating the chemical and biological (cell line) information. We determine that the protein, gene transcript and miRNA abundance provide the highest predictive signal when modelling the GI50 endpoint, which significantly outperformed the DNA copy-number variation or exome sequencing data (Tukey's Honestly Significant Difference, P <0.05). We demonstrate that, within the limits of the data, our approach exhibits the ability to both interpolate and extrapolate compound bioactivities to new cell lines and tissues and, although to a lesser extent, to dissimilar compounds. Moreover, our approach outperforms previous models generated on the GDSC dataset. Finally, we determine that in the cases investigated in more detail, the predicted drug-pathway associations and growth inhibition patterns are mostly consistent with the experimental data, which also suggests the possibility of identifying genomic markers of drug sensitivity for novel compounds on novel cell lines. CONTACT: terez@pasteur.fr; ab454@ac.cam.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information.

Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.

Neisseria meningitidis Type IV Pili Composed of Sequence Invariable Pilins Are Masked by Multisite Glycosylation.

The ability of pathogens to cause disease depends on their aptitude to escape the immune system. Type IV pili are extracellular filamentous virulence factors composed of pilin monomers and frequently expressed by bacterial pathogens. As such they are major targets for the host immune system. In the human pathogen Neisseria meningitidis, strains expressing class I pilins contain a genetic recombination system that promotes variation of the pilin sequence and is thought to aid immune escape. However, numerous hypervirulent clinical isolates express class II pilins that lack this property. This raises the question of how they evade immunity targeting type IV pili. As glycosylation is a possible source of antigenic variation it was investigated using top-down mass spectrometry to provide the highest molecular precision on the modified proteins. Unlike class I pilins that carry a single glycan, we found that class II pilins display up to 5 glycosylation sites per monomer on the pilus surface. Swapping of pilin class and genetic background shows that the pilin primary structure determines multisite glycosylation while the genetic background determines the nature of the glycans. Absence of glycosylation in class II pilins affects pilus biogenesis or enhances pilus-dependent aggregation in a strain specific fashion highlighting the extensive functional impact of multisite glycosylation. Finally, molecular modeling shows that glycans cover the surface of class II pilins and strongly decrease antibody access to the polypeptide chain. This strongly supports a model where strains expressing class II pilins evade the immune system by changing their sugar structure rather than pilin primary structure. Overall these results show that sequence invariable class II pilins are cloaked in glycans with extensive functional and immunological consequences.