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Structural Basis of the Signaling through a Bacterial Membrane Receptor HasR Deciphered by an Integrative Approach
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Wednesday, February 15, 2017
complex formation that could lead to an updated model of the complete distal C-ring. There is evidence that FliM middle domain is involved in dimeric interactions but no structure of this complex has been clearly determined. Using coevolving interactions we propose a model that is consistent with known indirect experimental data and points towards conformational heterogeneity. Our results that originate from coevolutionary analysis support a larger picture of C-ring formation and aim to close the gap between high-resolution monomers and the coarse grained understanding of macro-molecular assembly obtained with current methods. 2311-Plat Characterization of the Conformational Ensemble of Polyglutamine Peptides via Metadynamics MD Simulations and UV Resonance Raman Spectroscopy Riley J. Workman1, David Punihaole2, Ryan S. Jakubek2, Jeffry D. Madura1. 1 Chemistry and Biochemistry, Duquesne, Pittsburgh, PA, USA, 2Chemistry, University of Pittsburgh, Pittsburgh, PA, USA. Understanding the solution-state structures of polyglutamine peptides is crucial to developing fundamental insight into the etiology of at least 10 neurodegenerative disorders, including Huntington’s disease. Here, we utilize enhancedsampling and classical molecular dynamics to investigate in detail the model polyQ peptide, (Q10). Results from this computational work was compared to UV resonance Raman (UVRR) spectroscopy work performed by Punihaole et al., part of an ongoing collaboration. Our combined simulation and experimental results enable us to develop new, molecular-level insights into the solution-state structures of polyQ peptides. Using metadynamics MD simulations of Q10, we were able to characterize the peptide’s conformational free energy landscape. When compared with UVRR data, this landscape indicates that Q10 adopts two monomeric conformational states, a collapsed b-strand and a predominately PPII-like structure. Experimentally, these two structures do not readily interconvert, which suggests that a high activation barrier separates the two states. Using data from the metadynamics simulation, we identified the height and local metastable minima of this activation barrier. Classical MD simulations of Q10 have also provided new details regarding the conformations and hydrogen bonding environments of glutamine side chains in the PPII and b-strand-like structures in solution-state. Results from our MD simulations, as well as the comparison with experimental data collected by Punihaole et al. will be presented. 2312-Plat A New Pairwise Shape-Based Scoring Function to Consider Long-Range Interactions for Protein-Protein Docking Yumeng Yan, Shengyou Huang. School of Physics, Huazhong University of Science and Technology, Wuhan, China. Protein-protein docking is a valuable computational tool to study interactions between proteins, of which Fast-Fourier Transform (FFT)-based algorithms have been widely used as an initial step of post-docking methods or an independent docking approach due to its high computational efficiency and global sampling capability. As the foundation of scoring functions, shape complementarity plays a critical role in the success of FFT-based docking algorithms. Here, we have presented a new pairwise shape-based scoring function to consider long-range interactions for protein-protein docking. The longrange shape-based scoring (LSC) function is characterized by a protein core, a surface layer where the repulsion component is the sum of the contributions of neighboring core atoms, and an interacting layer where the favorable component comes from all the core and surface atoms in the protein. When tested on the 176 targets in the protein-protein docking benchmark 4.0 by the Weng group. Our LSC significantly improved the docking performance in both the success rate and the number of hits in binding mode prediction, compared to the shape-based scoring approaches in other protein-protein docking programs. When the top 1000 predictions were considered, LSC obtained a success rate of 56.3% and an average of 3.62 hits, compared to 48.9% and 2.96 of the hallmark shaped-based docking program ZDOCK 2.1. The improvement of LSC over other similar approaches provides a new initial-stage protein docking algorithm and also suggests a method to consider the long-range interaction effect in protein-protein docking. 2313-Plat Structural Basis of the Signaling through a Bacterial Membrane Receptor HasR Deciphered by an Integrative Approach Nadia Izadi Pruneyre. Structural Biology and Chemistry, Institut Pasteur, CNRS, Paris, France. Bacteria use diverse signaling pathways to control gene expression in response to external stimuli. In Gram-negative bacteria, the binding of some nutrients is sensed by their specific outer membrane transporters. A cascade of molecular
interactions between several proteins, located in three subcellular compartments, is then used to send this external signal towards the inside of the bacteria. This signaling pathway is involved in the regulation of gene expression and is crucial for the adaptation of bacteria to their environment. We have been studying a heme acquisition system (Has) developed by several commensal and pathogenic bacteria to acquire heme as iron source. Although various proteins involved in this process have been identified, signal transduction through this family of transporters is not well understood [1, 2, 3, 4]. Here, using an integrative approach (NMR, Xray, SAXS and electron microscopy) we have studied the structure of the transporter HasR, captured in two stages of the signaling process, i.e., before and after the arrival of signaling activators (heme and its carrier protein) [5]. Our results led us to propose a mechanism for the signal transfer form HasR to its interacellular partners. References [1] Krieg S, Huche F, Diederichs K, Izadi-Pruneyre N, Lecroisey A, Wandersman C, Delepelaire P & Welte W, Proc Natl Acad Sci U S A 106, 1045-1050 (2009). [2] Caillet-Saguy C, Piccioli M, Turano P, Izadi-Pruneyre N, Delepierre M, Bertini I & Lecroisey A, J Am Chem Soc, (5),1736-44 (2009). [3] Amorim GC, Prochnicka-Chalufour A, Delepelaire P, Lefevre J, Simenel C, Wandersman C, Delepierre M & Izadi-Pruneyre N, PloSOne, 8(3), e58964 (2013). [4] Malki I, Simenel C, Wojtowicz H, de Amorim GC, Prochnicka-Chalufour A, Hoos S, Raynal B, England P, Chaffotte A, Delepierre M, Delepelaire P & Izadi-Pruneyre N, PLoS One, 9(4), e89502 (2014). [5] Wojtowicz H, Prochnicka-Chalufour A, Cardoso de Amorim G, Roudenko O, Simenel C, Malki I, Pehaud-Arnaudet G, Gubellini F, Koutsioubas A, Perez J, Delepelaire P, Delepierre M, Fronzes R, Izadi-Pruneyre N, Biochem J 5,473(14):2239-48 (2016).
Platform: Single-Molecule Spectroscopy 2314-Plat Single-Molecule Dissection of the Role of Directionality in Protein Degradation by Clp Proteolytic Machines Hema Chandra Kotamarthi, Adrian Olivares, Benjamin Stein, Robert Sauer, Tania Baker. Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. Protein degradation by AAAþ proteases is an important biological process that maintains protein homeostasis by removing damaged and unneeded proteins.1 In principle, the rate of the proteolysis reaction can be influenced by the stability of the protein substrate, the sequence and location of its degradation tag (degron), and the chemo-mechanical properties of the AAAþ enzyme. Previous optical-trapping experiments probed single-molecule degradation initiated at a C-terminus of substrates with multiple copies of the titinI27 domain by two well-characterized AAAþ proteases, E. coli ClpXP and ClpAP. These studies demonstrated that destabilization of the titin domain by the V15P mutation resulted in faster enzymatic unfolding, with ClpAP being a faster unfoldase than ClpXP by a factor of ~3.2,3 In the current work, we use optical trapping to study ClpXP and ClpAP degradation initiated at the N-terminus of multi-domain titinI27 substrates. We find that ClpXP unfolds the wild-type and V15P titinI27 domains ~60 times faster in the N-to-C direction than in the C-to-N direction. Indeed, ClpXP unfolding of these domains is so fast that translocation becomes rate limiting in degradation. Ensemble assays confirm that ClpXP degradation of these substrates is much faster when the degron is at the N-terminus. Opticaltrapping experiments show that ClpAP unfolds the wild-type and V15P titinI27 substrates ~5 times faster in the N-to-C than C-to-N direction. Thus, the titinI27 domain has greater mechanical stability when pulled from the C-terminus than from the N-terminus, the location of the degron can have a very large impact on unfolding and degradation rates, and different AAAþ machines can unfold specific proteins more efficiently in one direction than the other. 1. Olivares, A.O., T.A. Baker, and R.T. Sauer, Nat Rev Microbiol, 14, 33-44 (2016). 2. Olivares, A.O., et al., Nat Struct Mol Biol, 21, 871-5 (2014). 3. Cordova, J.C., et al., Cell, 158, 647-58 (2014). 2315-Plat Regulated Snare Folding and Membrane Fusion Yongli Zhang. Cell Biology, Yale University, New Haven, CT, USA. All actions and thinking depend on delicate machinery at synapses that release neurotransmitters with extremely high speed and precision. Core components of the release machinery include SNARE proteins, Munc18-1, and synaptotagmin (Syt). SNAREs couple their stage-wise folding and assembly to synaptic vesicle fusion like a zipper, and Munc18-1 and Syt regulate the SNARE assembly. How these components work together to achieve the high speed and precision required for neurotransmission remain unclear. Using high-resolution
Wednesday, February 15, 2017
complex formation that could lead to an updated model of the complete distal C-ring. There is evidence that FliM middle domain is involved in dimeric interactions but no structure of this complex has been clearly determined. Using coevolving interactions we propose a model that is consistent with known indirect experimental data and points towards conformational heterogeneity. Our results that originate from coevolutionary analysis support a larger picture of C-ring formation and aim to close the gap between high-resolution monomers and the coarse grained understanding of macro-molecular assembly obtained with current methods. 2311-Plat Characterization of the Conformational Ensemble of Polyglutamine Peptides via Metadynamics MD Simulations and UV Resonance Raman Spectroscopy Riley J. Workman1, David Punihaole2, Ryan S. Jakubek2, Jeffry D. Madura1. 1 Chemistry and Biochemistry, Duquesne, Pittsburgh, PA, USA, 2Chemistry, University of Pittsburgh, Pittsburgh, PA, USA. Understanding the solution-state structures of polyglutamine peptides is crucial to developing fundamental insight into the etiology of at least 10 neurodegenerative disorders, including Huntington’s disease. Here, we utilize enhancedsampling and classical molecular dynamics to investigate in detail the model polyQ peptide, (Q10). Results from this computational work was compared to UV resonance Raman (UVRR) spectroscopy work performed by Punihaole et al., part of an ongoing collaboration. Our combined simulation and experimental results enable us to develop new, molecular-level insights into the solution-state structures of polyQ peptides. Using metadynamics MD simulations of Q10, we were able to characterize the peptide’s conformational free energy landscape. When compared with UVRR data, this landscape indicates that Q10 adopts two monomeric conformational states, a collapsed b-strand and a predominately PPII-like structure. Experimentally, these two structures do not readily interconvert, which suggests that a high activation barrier separates the two states. Using data from the metadynamics simulation, we identified the height and local metastable minima of this activation barrier. Classical MD simulations of Q10 have also provided new details regarding the conformations and hydrogen bonding environments of glutamine side chains in the PPII and b-strand-like structures in solution-state. Results from our MD simulations, as well as the comparison with experimental data collected by Punihaole et al. will be presented. 2312-Plat A New Pairwise Shape-Based Scoring Function to Consider Long-Range Interactions for Protein-Protein Docking Yumeng Yan, Shengyou Huang. School of Physics, Huazhong University of Science and Technology, Wuhan, China. Protein-protein docking is a valuable computational tool to study interactions between proteins, of which Fast-Fourier Transform (FFT)-based algorithms have been widely used as an initial step of post-docking methods or an independent docking approach due to its high computational efficiency and global sampling capability. As the foundation of scoring functions, shape complementarity plays a critical role in the success of FFT-based docking algorithms. Here, we have presented a new pairwise shape-based scoring function to consider long-range interactions for protein-protein docking. The longrange shape-based scoring (LSC) function is characterized by a protein core, a surface layer where the repulsion component is the sum of the contributions of neighboring core atoms, and an interacting layer where the favorable component comes from all the core and surface atoms in the protein. When tested on the 176 targets in the protein-protein docking benchmark 4.0 by the Weng group. Our LSC significantly improved the docking performance in both the success rate and the number of hits in binding mode prediction, compared to the shape-based scoring approaches in other protein-protein docking programs. When the top 1000 predictions were considered, LSC obtained a success rate of 56.3% and an average of 3.62 hits, compared to 48.9% and 2.96 of the hallmark shaped-based docking program ZDOCK 2.1. The improvement of LSC over other similar approaches provides a new initial-stage protein docking algorithm and also suggests a method to consider the long-range interaction effect in protein-protein docking. 2313-Plat Structural Basis of the Signaling through a Bacterial Membrane Receptor HasR Deciphered by an Integrative Approach Nadia Izadi Pruneyre. Structural Biology and Chemistry, Institut Pasteur, CNRS, Paris, France. Bacteria use diverse signaling pathways to control gene expression in response to external stimuli. In Gram-negative bacteria, the binding of some nutrients is sensed by their specific outer membrane transporters. A cascade of molecular
interactions between several proteins, located in three subcellular compartments, is then used to send this external signal towards the inside of the bacteria. This signaling pathway is involved in the regulation of gene expression and is crucial for the adaptation of bacteria to their environment. We have been studying a heme acquisition system (Has) developed by several commensal and pathogenic bacteria to acquire heme as iron source. Although various proteins involved in this process have been identified, signal transduction through this family of transporters is not well understood [1, 2, 3, 4]. Here, using an integrative approach (NMR, Xray, SAXS and electron microscopy) we have studied the structure of the transporter HasR, captured in two stages of the signaling process, i.e., before and after the arrival of signaling activators (heme and its carrier protein) [5]. Our results led us to propose a mechanism for the signal transfer form HasR to its interacellular partners. References [1] Krieg S, Huche F, Diederichs K, Izadi-Pruneyre N, Lecroisey A, Wandersman C, Delepelaire P & Welte W, Proc Natl Acad Sci U S A 106, 1045-1050 (2009). [2] Caillet-Saguy C, Piccioli M, Turano P, Izadi-Pruneyre N, Delepierre M, Bertini I & Lecroisey A, J Am Chem Soc, (5),1736-44 (2009). [3] Amorim GC, Prochnicka-Chalufour A, Delepelaire P, Lefevre J, Simenel C, Wandersman C, Delepierre M & Izadi-Pruneyre N, PloSOne, 8(3), e58964 (2013). [4] Malki I, Simenel C, Wojtowicz H, de Amorim GC, Prochnicka-Chalufour A, Hoos S, Raynal B, England P, Chaffotte A, Delepierre M, Delepelaire P & Izadi-Pruneyre N, PLoS One, 9(4), e89502 (2014). [5] Wojtowicz H, Prochnicka-Chalufour A, Cardoso de Amorim G, Roudenko O, Simenel C, Malki I, Pehaud-Arnaudet G, Gubellini F, Koutsioubas A, Perez J, Delepelaire P, Delepierre M, Fronzes R, Izadi-Pruneyre N, Biochem J 5,473(14):2239-48 (2016).
Platform: Single-Molecule Spectroscopy 2314-Plat Single-Molecule Dissection of the Role of Directionality in Protein Degradation by Clp Proteolytic Machines Hema Chandra Kotamarthi, Adrian Olivares, Benjamin Stein, Robert Sauer, Tania Baker. Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. Protein degradation by AAAþ proteases is an important biological process that maintains protein homeostasis by removing damaged and unneeded proteins.1 In principle, the rate of the proteolysis reaction can be influenced by the stability of the protein substrate, the sequence and location of its degradation tag (degron), and the chemo-mechanical properties of the AAAþ enzyme. Previous optical-trapping experiments probed single-molecule degradation initiated at a C-terminus of substrates with multiple copies of the titinI27 domain by two well-characterized AAAþ proteases, E. coli ClpXP and ClpAP. These studies demonstrated that destabilization of the titin domain by the V15P mutation resulted in faster enzymatic unfolding, with ClpAP being a faster unfoldase than ClpXP by a factor of ~3.2,3 In the current work, we use optical trapping to study ClpXP and ClpAP degradation initiated at the N-terminus of multi-domain titinI27 substrates. We find that ClpXP unfolds the wild-type and V15P titinI27 domains ~60 times faster in the N-to-C direction than in the C-to-N direction. Indeed, ClpXP unfolding of these domains is so fast that translocation becomes rate limiting in degradation. Ensemble assays confirm that ClpXP degradation of these substrates is much faster when the degron is at the N-terminus. Opticaltrapping experiments show that ClpAP unfolds the wild-type and V15P titinI27 substrates ~5 times faster in the N-to-C than C-to-N direction. Thus, the titinI27 domain has greater mechanical stability when pulled from the C-terminus than from the N-terminus, the location of the degron can have a very large impact on unfolding and degradation rates, and different AAAþ machines can unfold specific proteins more efficiently in one direction than the other. 1. Olivares, A.O., T.A. Baker, and R.T. Sauer, Nat Rev Microbiol, 14, 33-44 (2016). 2. Olivares, A.O., et al., Nat Struct Mol Biol, 21, 871-5 (2014). 3. Cordova, J.C., et al., Cell, 158, 647-58 (2014). 2315-Plat Regulated Snare Folding and Membrane Fusion Yongli Zhang. Cell Biology, Yale University, New Haven, CT, USA. All actions and thinking depend on delicate machinery at synapses that release neurotransmitters with extremely high speed and precision. Core components of the release machinery include SNARE proteins, Munc18-1, and synaptotagmin (Syt). SNAREs couple their stage-wise folding and assembly to synaptic vesicle fusion like a zipper, and Munc18-1 and Syt regulate the SNARE assembly. How these components work together to achieve the high speed and precision required for neurotransmission remain unclear. Using high-resolution