GPC3-Unc5 receptor complex structure and role in cell migration.

Neural migration is a critical step during brain development that requires the interactions of cell-surface guidance receptors. Cancer cells often hijack these mechanisms to disseminate. Here, we reveal crystal structures of Uncoordinated-5 receptor D (Unc5D) in complex with morphogen receptor glypican-3 (GPC3), forming an octameric glycoprotein complex. In the complex, four Unc5D molecules pack into an antiparallel bundle, flanked by four GPC3 molecules. Central glycan-glycan interactions are formed by N-linked glycans emanating from GPC3 (N241 in human) and C-mannosylated tryptophans of the Unc5D thrombospondin-like domains. MD simulations, mass spectrometry and structure-based mutants validate the crystallographic data. Anti-GPC3 nanobodies enhance or weaken Unc5-GPC3 binding and, together with mutant proteins, show that Unc5/GPC3 guide migrating pyramidal neurons in the mouse cortex, and cancer cells in an embryonic xenograft neuroblastoma model. The results demonstrate a conserved structural mechanism of cell guidance, where finely balanced Unc5-GPC3 interactions regulate cell migration.

Structural Basis of Teneurin-Latrophilin Interaction in Repulsive Guidance of Migrating Neurons.

Teneurins are ancient metazoan cell adhesion receptors that control brain development and neuronal wiring in higher animals. The extracellular C terminus binds the adhesion GPCR Latrophilin, forming a trans-cellular complex with synaptogenic functions. However, Teneurins, Latrophilins, and FLRT proteins are also expressed during murine cortical cell migration at earlier developmental stages. Here, we present crystal structures of Teneurin-Latrophilin complexes that reveal how the lectin and olfactomedin domains of Latrophilin bind across a spiraling beta-barrel domain of Teneurin, the YD shell. We couple structure-based protein engineering to biophysical analysis, cell migration assays, and in utero electroporation experiments to probe the importance of the interaction in cortical neuron migration. We show that binding of Latrophilins to Teneurins and FLRTs directs the migration of neurons using a contact repulsion-dependent mechanism. The effect is observed with cell bodies and small neurites rather than their processes. The results exemplify how a structure-encoded synaptogenic protein complex is also used for repulsive cell guidance.

Supramolecular organization and dynamics of mannosylated phosphatidylinositol lipids in the mycobacterial plasma membrane.

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), a disease that claims ~1.6 million lives annually. The current treatment regime is long and expensive, and missed doses contribute to drug resistance. Therefore, development of new anti-TB drugs remains one of the highest public health priorities. Mtb has evolved a complex cell envelope that represents a formidable barrier to antibiotics. The Mtb cell envelop consists of four distinct layers enriched for Mtb specific lipids and glycans. Although the outer membrane, comprised of mycolic acid esters, has been extensively studied, less is known about the plasma membrane, which also plays a critical role in impacting antibiotic efficacy. The Mtb plasma membrane has a unique lipid composition, with mannosylated phosphatidylinositol lipids (phosphatidyl-myoinositol mannosides, PIMs) comprising more than 50% of the lipids. However, the role of PIMs in the structure and function of the membrane remains elusive. Here, we used multiscale molecular dynamics (MD) simulations to understand the structure-function relationship of the PIM lipid family and decipher how they self-organize to shape the biophysical properties of mycobacterial plasma membranes. We assess both symmetric and asymmetric assemblies of the Mtb plasma membrane and compare this with residue distributions of Mtb integral membrane protein structures. To further validate the model, we tested known anti-TB drugs and demonstrated that our models agree with experimental results. Thus, our work sheds new light on the organization of the mycobacterial plasma membrane. This paves the way for future studies on antibiotic development and understanding Mtb membrane protein function.

Proteasome complexes experience profound structural and functional rearrangements throughout mammalian spermatogenesis.

During spermatogenesis, spermatogonia undergo a series of mitotic and meiotic divisions on their path to spermatozoa. To achieve this, a succession of processes requiring high proteolytic activity are in part orchestrated by the proteasome. The spermatoproteasome (s20S) is specific to the developing gametes, in which the gamete-specific α4s subunit replaces the α4 isoform found in the constitutive proteasome (c20S). Although the s20S is conserved across species and was shown to be crucial for germ cell development, its mechanism, function, and structure remain incompletely characterized. Here, we used advanced mass spectrometry (MS) methods to map the composition of proteasome complexes and their interactomes throughout spermatogenesis. We observed that the s20S becomes highly activated as germ cells enter meiosis, mainly through a particularly extensive 19S activation and, to a lesser extent, PA200 binding. Additionally, the proteasome population shifts from c20S (98%) to s20S (>82 to 92%) during differentiation, presumably due to the shift from α4 to α4s expression. We demonstrated that s20S, but not c20S, interacts with components of the meiotic synaptonemal complex, where it may localize via association with the PI31 adaptor protein. In vitro, s20S preferentially binds to 19S and displays higher trypsin- and chymotrypsin-like activities, both with and without PA200 activation. Moreover, using MS methods to monitor protein dynamics, we identified significant differences in domain flexibility between α4 and α4s. We propose that these differences induced by α4s incorporation result in significant changes in the way the s20S interacts with its partners and dictate its role in germ cell differentiation.

There and back again: bridging meso- and nano-scales to understand lipid vesicle patterning.

We describe a complete methodology to bridge the scales between nanoscale molecular dynamics and (micrometer) mesoscale Monte Carlo simulations in lipid membranes and vesicles undergoing phase separation, in which curving molecular species are furthermore embedded. To go from the molecular to the mesoscale, we notably appeal to physical renormalization arguments enabling us to rigorously infer the mesoscale interaction parameters from its molecular counterpart. We also explain how to deal with the physical timescales at stake at the mesoscale. Simulating the as-obtained mesoscale system enables us to equilibrate the long wavelengths of the vesicles of interest, up to the vesicle size. Conversely, we then backmap from the meso- to the nano-scale, which enables us to equilibrate in turn the short wavelengths down to the molecular length-scales. By applying our approach to the specific situation of patterning a vesicle membrane, we show that macroscopic membranes can thus be equilibrated at all length-scales in achievable computational time offering an original strategy to address the fundamental challenge of timescale in simulations of large bio-membrane systems.

The conical shape of DIM lipids promotes Mycobacterium tuberculosis infection of macrophages.

Phthiocerol dimycocerosate (DIM) is a major virulence factor of the pathogen Mycobacterium tuberculosis (Mtb). While this lipid promotes the entry of Mtb into macrophages, which occurs via phagocytosis, its molecular mechanism of action is unknown. Here, we combined biophysical, cell biology, and modeling approaches to reveal the molecular mechanism of DIM action on macrophage membranes leading to the first step of Mtb infection. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry showed that DIM molecules are transferred from the Mtb envelope to macrophage membranes during infection. Multiscale molecular modeling and 31P-NMR experiments revealed that DIM adopts a conical shape in membranes and aggregates in the stalks formed between 2 opposing lipid bilayers. Infection of macrophages pretreated with lipids of various shapes uncovered a general role for conical lipids in promoting phagocytosis. Taken together, these results reveal how the molecular shape of a mycobacterial lipid can modulate the biological response of macrophages.

Supramolecular assemblies underpin turnover of outer membrane proteins in bacteria.

Gram-negative bacteria inhabit a broad range of ecological niches. For Escherichia coli, this includes river water as well as humans and animals, where it can be both a commensal and a pathogen. Intricate regulatory mechanisms ensure that bacteria have the right complement of ß-barrel outer membrane proteins (OMPs) to enable adaptation to a particular habitat. Yet no mechanism is known for replacing OMPs in the outer membrane, an issue that is further confounded by the lack of an energy source and the high stability and abundance of OMPs. Here we uncover the process underpinning OMP turnover in E. coli and show it to be passive and binary in nature, in which old OMPs are displaced to the poles of growing cells as new OMPs take their place. Using fluorescent colicins as OMP-specific probes, in combination with ensemble and single-molecule fluorescence microscopy in vivo and in vitro, as well as molecular dynamics simulations, we established the mechanism for binary OMP partitioning. OMPs clustered to form ∼0.5-µm diameter islands, where their diffusion is restricted by promiscuous interactions with other OMPs. OMP islands were distributed throughout the cell and contained the Bam complex, which catalyses the insertion of OMPs in the outer membrane. However, OMP biogenesis occurred as a gradient that was highest at mid-cell but largely absent at cell poles. The cumulative effect is to push old OMP islands towards the poles of growing cells, leading to a binary distribution when cells divide. Hence, the outer membrane of a Gram-negative bacterium is a spatially and temporally organized structure, and this organization lies at the heart of how OMPs are turned over in the membrane.

Visualizing protein structures - tools and trends.

Molecular visualization is fundamental in the current scientific literature, textbooks and dissemination materials. It provides an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Tools for visual exploration of structural data have become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. This mini-review was written as a short and compact overview for scientists who need to visualize protein structures and want to make an informed decision which tool they should use. Here, we first describe a few 'Swiss Army knives' geared towards protein visualization for everyday use with an existing large user base, then focus on more specialized tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives.

Sharing Data from Molecular Simulations.

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/ ). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.

Lipid-Loving ANTs: Molecular Simulations of Cardiolipin Interactions and the Organization of the Adenine Nucleotide Translocase in Model Mitochondrial Membranes.

The exchange of ADP and ATP across the inner mitochondrial membrane is a fundamental cellular process. This exchange is facilitated by the adenine nucleotide translocase, the structure and function of which are critically dependent on the signature phospholipid of mitochondria, cardiolipin (CL). Here we employ multiscale molecular dynamics simulations to investigate CL interactions within a membrane environment. Using simulations at both coarse-grained and atomistic resolutions, we identify three CL binding sites on the translocase, in agreement with those seen in crystal structures and inferred from nuclear magnetic resonance measurements. Characterization of the free energy landscape for lateral lipid interaction via potential of mean force calculations demonstrates the strength of interaction compared to those of binding sites on other mitochondrial membrane proteins, as well as their selectivity for CL over other phospholipids. Extending the analysis to other members of the family, yeast Aac2p and mouse uncoupling protein 2, suggests a degree of conservation. Simulation of large patches of a model mitochondrial membrane containing multiple copies of the translocase shows that CL interactions persist in the presence of protein-protein interactions and suggests CL may mediate interactions between translocases. This study provides a key example of how computational microscopy may be used to shed light on regulatory lipid-protein interactions.

Epock: rapid analysis of protein pocket dynamics.

SUMMARY: The volume of an internal protein pocket is fundamental to ligand accessibility. Few programs that compute such volumes manage dynamic data from molecular dynamics (MD) simulations. Limited performance often prohibits analysis of large datasets. We present Epock, an efficient command-line tool that calculates pocket volumes from MD trajectories. A plugin for the VMD program provides a graphical user interface to facilitate input creation, run Epock and analyse the results. AVAILABILITY AND IMPLEMENTATION: Epock C++ source code, Python analysis scripts, VMD Tcl plugin, documentation and installation instructions are freely available at http://epock.bitbucket.org. CONTACT: benoist.laurent@gmail.com or baaden@smplinux.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Membrane stiffness is modified by integral membrane proteins.

The ease with which a cell membrane can bend and deform is important for a wide range of biological functions. Peripheral proteins that induce curvature in membranes (e.g. BAR domains) have been studied for a number of years. Little is known, however, about the effect of integral membrane proteins on the stiffness of a membrane (characterised by the bending rigidity, Kc). We demonstrate by computer simulation that adding integral membrane proteins at physiological densities alters the stiffness of the membrane. First we establish that the coarse-grained MARTINI forcefield is able to accurately reproduce the bending rigidity of a small patch of 1500 phosphatidyl choline lipids by comparing the calculated value to both experiment and an atomistic simulation of the same system. This enables us to simulate the dynamics of large (ca. 50 000 lipids) patches of membrane using the MARTINI coarse-grained description. We find that altering the lipid composition changes the bending rigidity. Adding integral membrane proteins to lipid bilayers also changes the bending rigidity, whilst adding a simple peripheral membrane protein has no effect. Our results suggest that integral membrane proteins can have different effects, and in the case of the bacterial outer membrane protein, BtuB, the greater the density of protein, the larger the reduction in stiffness.

Molecular Simulations of Gram-Negative Bacterial Membranes: A Vignette of Some Recent Successes.

In the following review we use recent examples from the literature to discuss progress in the area of atomistic and coarse-grained molecular dynamics simulations of selected bacterial membranes and proteins, with a particular focus on Gram-negative bacteria. As structural biology continues to provide increasingly high-resolution data on the proteins that reside within these membranes, simulations have an important role to play in linking these data with the dynamical behavior and function of these proteins. In particular, in the last few years there has been significant progress in addressing the issue of biochemical complexity of bacterial membranes such that the heterogeneity of the lipid and protein components of these membranes are now being incorporated into molecular-level models. Thus, in future we can look forward to complementary data from structural biology and molecular simulations combining to provide key details of structure-dynamics-function relationships in bacterial membranes.

Dimerization of the EphA1 receptor tyrosine kinase transmembrane domain: Insights into the mechanism of receptor activation.

EphA1 is a receptor tyrosine kinase (RTK) that plays a key role in developmental processes, including guidance of the migration of axons and cells in the nervous system. EphA1, in common with other RTKs, contains an N-terminal extracellular domain, a single transmembrane (TM) α-helix, and a C-terminal intracellular kinase domain. The TM helix forms a dimer, as seen in recent NMR studies. We have modeled the EphA1 TM dimer using a multiscale approach combining coarse-grain (CG) and atomistic molecular dynamics (MD) simulations. The one-dimensional potential of mean force (PMF) for this system, based on interhelix separation, has been calculated using CG MD simulations. This provides a view of the free energy landscape for helix-helix interactions of the TM dimer in a lipid bilayer. The resulting PMF profiles suggest two states, consistent with a rotation-coupled activation mechanism. The more stable state corresponds to a right-handed helix dimer interacting via an N-terminal glycine zipper motif, consistent with a recent NMR structure (2K1K). A second metastable state corresponds to a structure in which the glycine zipper motif is not involved. Analysis of unrestrained CG MD simulations based on representative models from the PMF calculations or on the NMR structure reveals possible pathways of interconversion between these two states, involving helix rotations about their long axes. This suggests that the interaction of TM helices in EphA1 dimers may be intrinsically dynamic. This provides a potential mechanism for signaling whereby extracellular events drive a shift in the repopulation of the underlying TM helix dimer energy landscape.

Blind prediction of interfacial water positions in CAPRI.

We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.

Recent Advances in Modeling Membrane ß-Barrel Proteins Using Molecular Dynamics Simulations: From Their Lipid Environments to Their Assemblies.

Spurred by advances in AI-driven modeling and experimental methods, molecular dynamics simulations are now acting as a platform to integrate these different approaches. This combination of methods is especially useful to understand ß-barrel proteins from the molecular level, e.g., identifying specific interactions with lipids or small molecules, up to assemblies comprised of hundreds of proteins and thousands of lipids. In this minireview, we will discuss recent advances, mainly from the last 5 years, in modeling ß-barrel proteins and their assemblies. These approaches require specific kinds of modeling and potentially different model resolutions that we will first describe in Subheading 1. We will then focus on different aspects of ß-barrel protein modeling: how different types of molecules can diffuse through ß-barrel proteins (Subheading 2); how lipids can interact with these proteins (Subheading 3); how ß-barrel proteins can interact with membrane partners (Subheading 4) or periplasmic extensions and partners (Subheading 5) to form large assemblies.

GPU-powered tools boost molecular visualization.

Recent advances in experimental structure determination provide a wealth of structural data on huge macromolecular assemblies such as the ribosome or viral capsids, available in public databases. Further structural models arise from reconstructions using symmetry orders or fitting crystal structures into low-resolution maps obtained by electron-microscopy or small angle X-ray scattering experiments. Visual inspection of these huge structures remains an important way of unravelling some of their secrets. However, such visualization cannot conveniently be carried out using conventional rendering approaches, either due to performance limitations or due to lack of realism. Recent developments, in particular drawing benefit from the capabilities of Graphics Processing Units (GPUs), herald the next generation of molecular visualization solutions addressing these issues. In this article, we present advances in computer science and visualization that help biologists visualize, understand and manipulate large and complex molecular systems, introducing concepts that remain little-known in the bioinformatics field. Furthermore, we compile currently available software and methods enhancing the shape perception of such macromolecular assemblies, for example based on surface simplification or lighting ameliorations.

Bendix: intuitive helix geometry analysis and abstraction.

UNLABELLED: The flexibility of α-helices is important for membrane protein function and calls for better visualization and analysis. Software is presented that quantifies and projects the helix axis evolution over time, with the choice of uniform or analytic heatmap graphics according to the local geometry. Bendix supports static, molecular dynamics, atomistic and coarse-grained input. AVAILABILITY AND IMPLEMENTATION: Bendix source code and documentation, including installation instructions, are freely available at http://sbcb.bioch.ox.ac.uk/Bendix. Bendix is written in Tcl as an extension to VMD and is supported by all major operating systems.

Molecular Modeling and Simulation of the Mycobacterial Cell Envelope: From Individual Components to Cell Envelope Assemblies.

Unlike typical Gram-positive bacteria, the cell envelope of mycobacteria is unique and composed of a mycobacterial outer membrane, also known as the mycomembrane, a peptidoglycan layer, and a mycobacterial inner membrane, which is analogous to that of Gram-negative bacteria. Despite its importance, however, our understanding of this complex cell envelope is rudimentary at best. Thus, molecular modeling and simulation of such an envelope can benefit the scientific community by proposing new hypotheses about the biophysical properties of its different layers. In this Perspective, we present recent advances in molecular modeling and simulation of the mycobacterial cell envelope from individual components to cell envelope assemblies. We also show how modeling other types of cell envelopes, such as that of Escherichia coli, may help modeling part of the mycobacterial envelopes. We hope that the studies presented here are just the beginning of the road and more and more new modeling and simulation studies help us to understand crucial questions related to mycobacteria such as antibiotic resistance or bacterial survival in the host.

MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations.

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation, such as temperature and simulation length, and identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore collected MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and increase populating and standardizing metadata to reuse this valuable matter.