55 research outputs found

    Structural Basis of Multiple Sequential LC8 Sites: Insights from Interactions of Lc8 with Pac11

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    Interactions of LC8 with N-Terminal Segments of the Intermediate Chain of Cytoplasmic Dynein

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    LC8, a highly conserved 10-kDa light chain, and IC74, a 74-kDa intermediate chain, are presumed to promote the assembly of the cytoplasmic dynein motor protein complex and to be engaged in the controlled binding and release of cargo. The interactions of LC8 from Drosophila melanogaster with constructs of IC74 were characterized in vitro by affinity methods, limited proteolysis, and circular dichroism spectroscopy. Previously, we have performed limited proteolysis on the N-terminal domain of IC74, IC(1-289), when free and when bound to dynein light chains LC8 and Tctex-1[1]. We have also shown that upon addition of LC8, IC(1-289) undergoes a significant conformational change from a largely unfolded to a more ordered structure. The purpose of the work presented here is to determine whether residues 1-30 in IC74, predicted to be in a coiled coil, are involved in the stabilization of the protein upon binding to LC8. Constructs of IC74, IC(1-143), and IC(30-143) that include the LC8 binding site but with and without the first 30 residues were prepared, and their binding and protection patterns were compared to our previous results for IC(1-289). The results suggest that coiled coil residues 1-30 are not responsible for the increase in structure we observe when IC(1-289) binds to LC8

    Charting a new frontier of science by integrating mathematical modeling to understand and predict complex biological systems

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    Biological systems are staggeringly complex. To untangle this complexity and make predictions about biological systems is a continuous goal of biological research. One approach to achieve these goals is to emphasize the use of quantitative measures of biological processes. Advances in quantitative biology data collection and analysis across scales (molecular, cellular, organismal, ecological) has transformed how we understand, categorize, and predict complex biological systems. Simultaneously, thanks to increased computational power, mathematicians, engineers and physical scientists -- collectively termed theoreticians -- have developed sophisticated models of biological systems at different scales. But there is still a disconnect between the two fields. This surge of quantitative data creates an opportunity to apply, develop, and evaluate mathematical models of biological systems and explore novel methods of analysis. The novel modeling schemes can also offer deeper understanding of principles in biology. In the context of this paper, we use “models” to refer to mathematical representations of biological systems. This data revolution puts scientists in a unique position to leverage information-rich datasets to improve descriptive modeling. Moreover, advances in technology allow inclusion of heterogeneity and variability within these datasets and mathematical models. This inclusion may lead to identifying previously undetermined variables driving or maintaining heterogeneity and diversity. Improved inclusion of variation may even improve biologically meaningful predictions about how systems will respond to perturbations. Although some of these practices are mainstream in specific sub-fields of biology, such practices are not widespread across all fields of biological sciences. With resources dedicated to better integrating biology and mathematical modeling, we envision a transformational improvement in the ability to describe and predict complex biological systems

    Structural basis for assembly and function of the Nup82 complex in the nuclear pore scaffold

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    Nuclear pore complexes (NPCs) are huge assemblies formed from ∼30 different nucleoporins, typically organized in subcomplexes. One module, the conserved Nup82 complex at the cytoplasmic face of NPCs, is crucial to terminate mRNA export. To gain insight into the structure, assembly, and function of the cytoplasmic pore filaments, we reconstituted in yeast the Nup82–Nup159–Nsp1–Dyn2 complex, which was suitable for biochemical, biophysical, and electron microscopy analyses. Our integrative approach revealed that the yeast Nup82 complex forms an unusual asymmetric structure with a dimeric array of subunits. Based on all these data, we developed a three-dimensional structural model of the Nup82 complex that depicts how this module might be anchored to the NPC scaffold and concomitantly can interact with the soluble nucleocytoplasmic transport machinery

    Structural basis for assembly and function of the Nup82 complex in the nuclear pore scaffold

    Get PDF
    Nuclear pore complexes (NPCs) are huge assemblies formed from ∼30 different nucleoporins, typically organized in subcomplexes. One module, the conserved Nup82 complex at the cytoplasmic face of NPCs, is crucial to terminate mRNA export. To gain insight into the structure, assembly, and function of the cytoplasmic pore filaments, we reconstituted in yeast the Nup82–Nup159–Nsp1–Dyn2 complex, which was suitable for biochemical, biophysical, and electron microscopy analyses. Our integrative approach revealed that the yeast Nup82 complex forms an unusual asymmetric structure with a dimeric array of subunits. Based on all these data, we developed a three-dimensional structural model of the Nup82 complex that depicts how this module might be anchored to the NPC scaffold and concomitantly can interact with the soluble nucleocytoplasmic transport machinery

    A network of assembly factors is involved in remodeling rRNA elements during preribosome maturation

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    Eukaryotic ribosome biogenesis involves ∼200 assembly factors, but how these contribute to ribosome maturation is poorly understood. Here, we identify a network of factors on the nascent 60S subunit that actively remodels preribosome structure. At its hub is Rsa4, a direct substrate of the force-generating ATPase Rea1. We show that Rsa4 is connected to the central protuberance by binding to Rpl5 and to ribosomal RNA (rRNA) helix 89 of the nascent peptidyl transferase center (PTC) through Nsa2. Importantly, Nsa2 binds to helix 89 before relocation of helix 89 to the PTC. Structure-based mutations of these factors reveal the functional importance of their interactions for ribosome assembly. Thus, Rsa4 is held tightly in the preribosome and can serve as a “distribution box,” transmitting remodeling energy from Rea1 into the developing ribosome. We suggest that a relay-like factor network coupled to a mechano-enzyme is strategically positioned to relocate rRNA elements during ribosome maturation
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