73 research outputs found
Making the invisible enemy visible.
Structural biology plays a crucial role in the fight against COVID-19, permitting us to ‘see’ and understand SARS-CoV-2. However, the macromolecular structures of SARS-CoV-2 proteins that were solved with great speed and urgency can contain errors that may hinder drug design. The Coronavirus Structural Task Force has been working behind the scenes to evaluate and improve these structures, making the results freely available at https://insidecorona.net/
Multi-Layered Films Containing a Biomimetic Stimuli-Responsive Recombinant Protein
Electrostatic self-assembly was used to fabricate new smart multi-layer coatings, using a recombinant elastin-like polymer (ELP) and chitosan as the counterion macromolecule. The ELP was bioproduced, purified and its purity and expected molecular weight were assessed. Aggregate size measurements, obtained by light scattering of dissolved ELP, were performed as a function of temperature and pH to assess the smart properties of the polymer. The build-up of multi-layered films containing ELP and chitosan, using a layer-by-layer methodology, was followed by quartz-crystal microbalance with dissipation monitoring. Atomic force microscopy analysis permitted to demonstrate that the topography of the multi-layered films could respond to temperature. This work opens new possibilities for the use of ELPs in the fabrication of biodegradable smart coatings and films, offering new platforms in biotechnology and in the biomedical area
High source levels and small active space of high-pitched song in bowhead whales (Balaena mysticetus)
© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Public Library of Science, doi:10.1371/journal.pone.0052072.The low-frequency, powerful vocalizations of blue and fin whales may potentially be detected by conspecifics across entire ocean basins. In contrast, humpback and bowhead whales produce equally powerful, but more complex broadband vocalizations composed of higher frequencies that suffer from higher attenuation. Here we evaluate the active space of high frequency song notes of bowhead whales (Balaena mysticetus) in Western Greenland using measurements of song source levels and ambient noise. Four independent, GPS-synchronized hydrophones were deployed through holes in the ice to localize vocalizing bowhead whales, estimate source levels and measure ambient noise. The song had a mean apparent source level of 185±2 dB rms re 1 µPa @ 1 m and a high mean centroid frequency of 444±48 Hz. Using measured ambient noise levels in the area and Arctic sound spreading models, the estimated active space of these song notes is between 40 and 130 km, an order of magnitude smaller than the estimated active space of low frequency blue and fin whale songs produced at similar source levels and for similar noise conditions. We propose that bowhead whales spatially compensate for their smaller communication range through mating aggregations that co-evolved with broadband song to form a complex and dynamic acoustically mediated sexual display.This work was funded by the Oticon Foundation (grant # 08-3469 to Arctic Station, OT). OT and MC were additionally funded by AP Møller og Hustru Chastine Mc-Kinney Møllers Fond til almene Formaal, MS by a PhD scholarship from the Oticon Foundation, FHJ by a Danish Council for Independent Research, Natural Sciences post-doctoral grant, SEP by a grant from the U.S. Office of Naval Research, and PTM by frame grants from the Danish Natural Science Research Council
Structure and dynamics of the active Gs-coupled human secretin receptor
The class B secretin GPCR (SecR) has broad physiological effects, with target potential for treatment of metabolic and cardiovascular disease. Molecular understanding of SecR binding and activation is important for its therapeutic exploitation. We combined cryo-electron microscopy, molecular dynamics, and biochemical cross-linking to determine a 2.3 Å structure, and interrogate dynamics, of secretin bound to the SecR:Gs complex. SecR exhibited a unique organization of its extracellular domain (ECD) relative to its 7-transmembrane (TM) core, forming more extended interactions than other family members. Numerous polar interactions formed between secretin and the receptor extracellular loops (ECLs) and TM helices. Cysteine-cross-linking, cryo-electron microscopy multivariate analysis and molecular dynamics simulations revealed that interactions between peptide and receptor were dynamic, and suggested a model for initial peptide engagement where early interactions between the far N-terminus of the peptide and SecR ECL2 likely occur following initial binding of the peptide C-terminus to the ECD
Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors
We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property-free knowledge base for future anticoronavirus drug discovery
Модельные характеристики кардиореспираторной системы высококвалифицированных гребцов на байдарках и каноэ
The most frequently used approach for protein structure prediction is currently homology modeling. The 3D model building phase of this methodology is critical for obtaining an accurate and biologically useful prediction. The most widely employed tool to perform this task is MODELLER. This program implements the "modeling by satisfaction of spatial restraints" strategy and its core algorithm has not been altered significantly since the early 1990s. In this work, we have explored the idea of modifying MODELLER with two effective, yet computationally light strategies to improve its 3D modeling performance. Firstly, we have investigated how the level of accuracy in the estimation of structural variability between a target protein and its templates in the form of σ values profoundly influences 3D modeling. We show that the σ values produced by MODELLER are on average weakly correlated to the true level of structural divergence between target-template pairs and that increasing this correlation greatly improves the program's predictions, especially in multiple-template modeling. Secondly, we have inquired into how the incorporation of statistical potential terms (such as the DOPE potential) in the MODELLER's objective function impacts positively 3D modeling quality by providing a small but consistent improvement in metrics such as GDT-HA and lDDT and a large increase in stereochemical quality. Python modules to harness this second strategy are freely available at https://github.com/pymodproject/altmod. In summary, we show that there is a large room for improving MODELLER in terms of 3D modeling quality and we propose strategies that could be pursued in order to further increase its performance
Structural basis of TIR-domain-assembly formation in MAL- and MyD88-dependent TLR4 signaling
Toll-like receptor (TLR) signaling is a key innate immunity response to pathogens. Recruitment of signaling adapters such as MAL (TIRAP) and MyD88 to the TLRs requires Toll/interleukin-1 receptor (TIR)-domain interactions, which remain structurally elusive. Here we show that MAL TIR domains spontaneously and reversibly form filaments in vitro. They also form cofilaments with TLR4 TIR domains and induce formation of MyD88 assemblies. A 7-Å-resolution cryo-EM structure reveals a stable MAL protofilament consisting of two parallel strands of TIR-domain subunits in a BB-loop-mediated head-to-tail arrangement. Interface residues that are important for the interaction are conserved among different TIR domains. Although large filaments of TLR4, MAL or MyD88 are unlikely to form during cellular signaling, structure-guided mutagenesis, combined with in vivo interaction assays, demonstrated that the MAL interactions defined within the filament represent a template for a conserved mode of TIR-domain interaction involved in both TLR and interleukin-1 receptor signaling
The CCP4 suite: integrative software for macromolecular crystallography
The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world
How insulin-like growth factor I binds to a hybrid insulin receptor type 1 insulin-like growth factor receptor
Monomers of the insulin receptor and type 1 insulin-like growth factor receptor (IGF-1R) can combine stochastically to form heterodimeric hybrid receptors. These hybrid receptors display ligand binding and signaling properties that differ from those of the homodimeric receptors. Here, we describe the cryoelectron microscopy structure of such a hybrid receptor in complex with insulin-like growth factor I (IGF-I). The structure (ca. 3.7 Å resolution) displays a single IGF-I ligand, bound in a similar fashion to that seen for IGFs in complex with IGF-1R. The IGF-I ligand engages the first leucine-rich-repeat domain and cysteine-rich region of the IGF-1R monomer (rather than those of the insulin receptor monomer), consistent with the determinants for IGF binding residing in the IGF-1R cysteine-rich region. The structure broadens our understanding of this receptor family and assists in delineating the key structural motifs involved in binding their respective ligands
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