38 research outputs found

    Structural mechanism for the recognition and ubiquitination of a single nucleosome residue by Rad6-Bre1

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    Cotranscriptional ubiquitination of histone H2B is key to gene regulation. The yeast E3 ubiquitin ligase Bre1 (human RNF20/40) pairs with the E2 ubiquitin conjugating enzyme Rad6 to monoubiquitinate H2B at Lys123. How this single lysine residue on the nucleosome core particle (NCP) is targeted by the Rad6-Bre1 machinery is unknown. Using chemical cross-linking and mass spectrometry, we identified the functional interfaces of Rad6, Bre1, and NCPs in a defined in vitro system. The Bre1 RING domain cross-links exclusively with distinct regions of histone H2B and H2A, indicating a spatial alignment of Bre1 with the NCP acidic patch. By docking onto the NCP surface in this distinct orientation, Bre1 positions the Rad6 active site directly over H2B Lys123. The Spt-Ada-Gcn5 acetyltransferase (SAGA) H2B deubiquitinase module competes with Bre1 for binding to the NCP acidic patch, indicating regulatory control. Our study reveals a mechanism that ensures site-specific NCP ubiquitination and fine-tuning of opposing enzymatic activities

    The Structure and Regulation of Human Muscle α-Actinin

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    SummaryThe spectrin superfamily of proteins plays key roles in assembling the actin cytoskeleton in various cell types, crosslinks actin filaments, and acts as scaffolds for the assembly of large protein complexes involved in structural integrity and mechanosensation, as well as cell signaling. α-actinins in particular are the major actin crosslinkers in muscle Z-disks, focal adhesions, and actin stress fibers. We report a complete high-resolution structure of the 200 kDa α-actinin-2 dimer from striated muscle and explore its functional implications on the biochemical and cellular level. The structure provides insight into the phosphoinositide-based mechanism controlling its interaction with sarcomeric proteins such as titin, lays a foundation for studying the impact of pathogenic mutations at molecular resolution, and is likely to be broadly relevant for the regulation of spectrin-like proteins

    Snake Cytotoxins Bind to Membranes via Interactions with Phosphatidylserine Head Groups of Lipids

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    The major representatives of Elapidae snake venom, cytotoxins (CTs), share similar three-fingered fold and exert diverse range of biological activities against various cell types. CT-induced cell death starts from the membrane recognition process, whose molecular details remain unclear. It is known, however, that the presence of anionic lipids in cell membranes is one of the important factors determining CT-membrane binding. In this work, we therefore investigated specific interactions between one of the most abundant of such lipids, phosphatidylserine (PS), and CT 4 of Naja kaouthia using a combined, experimental and modeling, approach. It was shown that incorporation of PS into zwitterionic liposomes greatly increased the membrane-damaging activity of CT 4 measured by the release of the liposome-entrapped calcein fluorescent dye. The CT-induced leakage rate depends on the PS concentration with a maximum at approximately 20% PS. Interestingly, the effects observed for PS were much more pronounced than those measured for another anionic lipid, sulfatide. To delineate the potential PS binding sites on CT 4 and estimate their relative affinities, a series of computer simulations was performed for the systems containing the head group of PS and different spatial models of CT 4 in aqueous solution and in an implicit membrane. This was done using an original hybrid computational protocol implementing docking, Monte Carlo and molecular dynamics simulations. As a result, at least three putative PS-binding sites with different affinities to PS molecule were delineated. Being located in different parts of the CT molecule, these anion-binding sites can potentially facilitate and modulate the multi-step process of the toxin insertion into lipid bilayers. This feature together with the diverse binding affinities of the sites to a wide variety of anionic targets on the membrane surface appears to be functionally meaningful and may adjust CT action against different types of cells

    A membrane-inserted structural model of the yeast mitofusin Fzo1

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    Mitofusins are large transmembrane GTPases of the dynamin-related protein family, and are required for the tethering and fusion of mitochondrial outer membranes. Their full-length structures remain unknown, which is a limiting factor in the study of outer membrane fusion. We investigated the structure and dynamics of the yeast mitofusin Fzo1 through a hybrid computational and experimental approach, combining molecular modelling and all-atom molecular dynamics simulations in a lipid bilayer with site-directed mutagenesis and in vivo functional assays. The predicted architecture of Fzo1 improves upon the current domain annotation, with a precise description of the helical spans linked by flexible hinges, which are likely of functional significance. In vivo site-directed mutagenesis validates salient aspects of this model, notably, the long-distance contacts and residues participating in hinges. GDP is predicted to interact with Fzo1 through the G1 and G4 motifs of the GTPase domain. The model reveals structural determinants critical for protein function, including regions that may be involved in GTPase domain-dependent rearrangements

    On a mechanistic impact of transmembrane tetramerization in the pathological activation of RTKs

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    Constitutive activation of receptor tyrosine kinases (RTKs) via different mutations has a strong impact on the development of severe human disorders, including cancer. Here we propose a putative activation scenario of RTKs, whereby transmembrane (TM) mutations can also promote higher-order oligomerization of the receptors that leads to the subsequent ligand-free activation. We illustrate this scenario using a computational modelling framework comprising sequence-based structure prediction and all-atom 1 µs molecular dynamics (MD) simulations in a lipid membrane for a previously characterised oncogenic TM mutation V536E in platelet-derived growth factor receptor alpha (PDGFRA). We show that in the course of MD simulations the mutant TM tetramer retains stable and compact configuration strengthened by tight protein-protein interactions, while the wild type TM tetramer demonstrates looser packing and a tendency to dissociate. Moreover, the mutation affects the characteristic motions of mutated TM helical segments by introducing additional non-covalent crosslinks in the middle of the TM tetramer, which operate as mechanical hinges. This leads to dynamic decoupling of the C-termini from the rigidified N-terminal parts and facilitates more pronounced possible displacement between the C-termini of the mutant TM helical regions that can provide more freedom for mutual rearrangement of the kinase domains located downstream. Our results for the V536E mutation in the context of PDGFRA TM tetramer allow for the possibility that the effect of oncogenic TM mutations can go beyond alternating the structure and dynamics of TM dimeric states and might also promote the formation of higher-order oligomers directly contributing to ligand-independent signalling effectuated by PDGFRA and other RTKs

    Protein Electrostatic Properties Predefining the Level of Surface Hydrophobicity Change upon Phosphorylation

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    We use explicit-solvent, molecular dynamics simulations to study the change in polar properties of a solvent-accessible surface for proteins undergoing phosphorylation. We analyze eight different pairs of proteins representing different structural classes in native and phosphorylated states and estimate the polarity of their surface using the molecular hydrophobicity potential approach. Whereas the phosphorylation-induced hydrophobicity change in the vicinity of phosphosites does not vary strongly among the studied proteins, the equivalent change for complete proteins covers a surprisingly wide range of effects including even an increase in the overall hydrophobicity in some cases. Importantly, the observed changes are strongly related to electrostatic properties of proteins, such as the net charge per residue, the distribution of charged side-chain contacts, and the isoelectric point. These features predefine the level of surface hydrophobicity change upon phosphorylation and may thus contribute to the phosphorylation-induced alteration of the interactions between a protein and its environment

    Self-Consistent Framework Connecting Experimental Proxies of Protein Dynamics with Configurational Entropy

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    The recently developed NMR techniques enable estimation of protein configurational entropy change from the change in the average methyl order parameters. This experimental observable, however, does not directly measure the contribution of intramolecular couplings, protein main-chain motions, or angular dynamics. Here, we carry out a self-consistent computational analysis of the impact of these missing contributions on an extensive set of molecular dynamics simulations of different proteins undergoing binding. Specifically, we compare the configurational entropy change in protein complex formation as obtained by the maximum information spanning tree approximation (MIST), which treats the above entropy contributions directly, and the change in the average NMR methyl and NH order parameters. Our parallel implementation of MIST allows us to treat hard angular degrees of freedom as well as couplings up to full pairwise order explicitly, while still involving a high degree of sampling and tackling molecules of biologically relevant sizes. First, we demonstrate a remarkably strong linear relationship between the total configurational entropy change and the average change in both methyl and backbone-NH order parameters. Second, in contrast to canonical assumptions, we show that the main-chain and angular terms contribute significantly to the overall configurational entropy change and also scale linearly with it. Consequently, linear models starting from the average methyl order parameters are able to capture the contribution of main-chain and angular terms well. After applying the quantum-mechanical harmonic oscillator entropy formalism, we establish a similarly strong linear relationship for X-ray crystallographic B-factors. Finally, we demonstrate that the observed linear relationships remain robust against drastic undersampling and argue that they reflect an intrinsic property of compact proteins. Despite their remarkable strength, however, the above linear relationships yield estimates of configurational entropy change whose accuracy appears to be sufficient for qualitative applications only

    PARENT: A Parallel Software Suite for the Calculation of Configurational Entropy in Biomolecular Systems

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    Accurate estimation of configurational entropy from the <i>in silico</i>-generated biomolecular ensembles, e.g., from molecular dynamics (MD) trajectories, is dependent strongly on exhaustive sampling for physical reasons. This, however, creates a major computational problem for the subsequent estimation of configurational entropy using the Maximum Information Spanning Tree (MIST) or Mutual Information Expansion (MIE) approaches for internal molecular coordinates. In particular, the available software for such estimation exhibits serious limitations when it comes to molecules with hundreds or thousands of atoms, because of its reliance on a serial program architecture. To overcome this problem, we have developed a parallel, hybrid MPI/openMP C++ implementation of MIST and MIE, called PARENT, which is particularly optimized for high-performance computing and provides efficient estimation of configurational entropy in different biological processes (e.g., protein–protein interactions). In addition, PARENT also allows for a detailed mapping of intramolecular allosteric networks. Here, we benchmark the program on a set of 1-μs-long MD trajectories of 10 different protein complexes and their components, demonstrating robustness and good scalability. A direct comparison between MIST and MIE on the same dataset demonstrates a superior convergence behavior for the former approach, when it comes to total simulation length and configurational-space binning
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