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Proteins Evolve on the Edge of Supramolecular Self-Assembly
200a
Monday, February 13, 2017
HSA, (~35-40 mg/ml) and g-globulins, IgG, (~10-15 mg/ml). To study and understand the behavior of therapeutic antibodies in the presence of HSA, human IgG, and other serum components, tracer experiments are done pairwise as a function of HSA, IgG and therapeutic protein concentration. A plot of 1/s vs concentration reveals thermodynamic nonideality or a slowing of the sedimentation rate due to itself or another component (s ¼ s0/(1 þ Ksc)). This generates a 3x3 matrix of data that describes self- and cross-term hydrodynamic nonideality Ks. The goal is to develop a preclinical method for quantitative hydrodynamic analysis of therapeutic proteins in crowded environments like serum. (Supported by Boehringer-Ingelheim.) 987-Pos Board B55 Computational Characterization of Oligomerization of FVFLM Peptide and its Ability to Inhibit Beta Amyloid Aggregation Maksim Kouza1, Anirban Banerji2, Andrzej Kolinski1, Irina Alexandra Buhimschi3, Andrzej Kloczkowski2. 1 Faculty of Chemistry, University of Warsaw, Warsaw, Poland, 2Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH, USA, 3Center for Perinatal Research, Nationwide Children’s Hospital, Columbus, OH, USA. Preeclampsia, a pregnancy-specific disorder, shares typical pathophysiological features with protein misfolding disorders including Alzheimer’s disease1. Characteristic for preeclampsia is the involvement of multiple proteins of which fragments of SERPINA1 and b-amyloid co-aggregate in urine and placenta of preeclamptic women. This work explores the biophysical basis of this interaction by investigating the multidimensional efficacy of the FVFLM sequence in SERPINA1, as a model inhibitory agent of b-amyloid aggregation. Several algorithms predict FVFLM peptide as being a highly amyloidogenic2,3. After studying the oligomerization of FVFLM peptides using allatom molecular dynamics simulations with the GROMOS43a1 force field and explicit water, we report that FVFLM can aggregate and its aggregation is spontaneous with a remarkably faster rate than that recorded for KLVFF (aggregation ‘‘hot-spot’’ from b-amyloid). The population of fibril-prone conformations in the monomeric state of KLVFF was found to be lower than FVFLM indicating the faster aggregation process of FVFLM4. The fast kinetics of FVFLM aggregation was found to be driven primarily by core-like aromatic interactions originating from the anti-parallel orientation of complementarily uncharged strands. We also demonstrate a high propensity of FVFLM for KLVFF binding. When present, FVFLM disrupts the b-amyloid aggregation pathway and we propose that FVFLM-like peptides might be used to prevent the assembly of full-length Ab or other pro-amyloidogenic peptides into amyloid fibrils. 1. Buhimschi, I.A. et al. Protein misfolding, congophilia, oligomerization, and defective amyloid processing in preeclampsia. Science translational medicine6, 245ra292 (2014). 2. Zambrano, R. et al. AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures. Nucleic Acids Res (2015). 3. Kouza, M., Faraggi, E., Kolinski, A. & Kloczkowski, A. in Prediction of Protein Secondary Structure, Vol. 1484. (eds. Y. Zhou, A. Kloczkowski, E. Faraggi & Y. Yang) 7-24 (Humana Press, New York; 2016). 4. Nam, H.B., Kouza, M., Hoang, Z. & Li, M.S. Relationship between population of the fibril-prone conformation in the monomeric state and oligomer formation times of peptides: Insights from all-atom simulations. J Chem Phys 132, 165104 (2010) 988-Pos Board B56 A Novel Coarse-Grained Model to Study Liquid-Liquid Phase Separation of Disordered Proteins Gregory L. Dignon1, Wenwei Zheng2, Robert Best2, Jeetain Mittal1. 1 Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, USA, 2National Institutes of Health, Bethesda, MD, USA. Recent studies have led to the discovery of droplets composed of disordered protein chains in a separate liquid-like phase. Such assemblies have been found to be relevant to physiological function as membraneless compartments in living cells including the nucleolus and ribonucleoprotein (RNP) granules as well as many organelles in prokaryotic cells (1). The thermodynamic driving force for this phase separation, however, is still not well characterized. Fused in Sarcoma (FUS) is an RNA binding protein that naturally forms these droplets as RNP granules which aid with DNA repair. The low complexity domain, FUS LC is a fully disordered domain and has been observed to form these droplets on its own in vitro (2). Mutations of FUS can result in transformation of these assemblies into poorly soluble aggregates involved in the pathogenesis of Amyotrophic Lateral Sclerosis and Frontotemporal Dementia (3). As the spatiotemporal scales involved
in the phase separation of proteins cannot be resolved using fully detailed all-atom models, we develop a simple Ca;-based coarse-grained model that treats each amino acid in the chain as a single interaction site. The model is parameterized to treat each of the twenty naturally occurring amino acids differently in order to capture sequence-specific effects. Development of the proposed model involves top-down comparisons with experimental data available from the recent literature as well as comparisons with atomistic simulations of a single chain. We then use this model to characterize the droplet formation for FUS LC including the proposed transition from liquid-like to solid-like aggregates. We are also able to capture known trends in FUS LC phase separation as a function of salt concentration and diseaserelated mutations. This model should aid in the molecular understanding of phase behavior of disordered proteins thus aiding in development of therapeutic strategies. 1.Brangwynne, C. P.; Eckmann, C. R.; Courson, D. S.; Rybarska, A.; Hoege, C.; Gharakhani, J.; Julicher, F.; Hyman, A. A. Science 2009, 324, 1729-1732 2.Burke, K. A.; Janke, A. M.; Rhine, C. L.; Fawzi, N. L. Molecular Cell 2015, 60, 231-241 3.Patel, A.; Lee H. O.; Jawerth, L.; Dechsel, D.; Hyman, A. A.; Alberti, S. and othersCell 2015, 162, 1066-1077 989-Pos Board B57 Proteins Evolve on the Edge of Supramolecular Self-Assembly He´ctor Garcia Seisdedos. Structural Biology, Weizmann Institute of Science, Rehovot, Israel. In cells, over one third of proteins self-associate with multiple copies of themselves to form symmetric homomers. These protein complexes entail unique geometric and functional properties, underlining the virtue of symmetry in proteins. Yet, symmetry can also pose a risk. In sickle cell disease, the symmetry of hemoglobin exacerbates the effect of a mutation, resulting in harmful fibril formation. Here we assessed the universality of this Achilles heel by determining how readily mutations can induce homomers to further self-assemble. We predicted that mutations solely increasing surface hydrophobicity could frequently induce de novo intermolecular interactions driving polymerization. We investigated twelve distinct homomers and, remarkably, we observed their polymerization in all cases, with seven forming micrometer-long fibrils in vivo. Biophysical measurements and electron microscopy indicated that mutants self-assembled in their folded states. Though surface mutations are often regarded as benign due to their minimal impact on protein stability, we exposed their dramatic potential to trigger de novo interactions and polymerization when compounded by symmetry. Accordingly, an analysis of all symmetric proteins of known structure revealed strategically placed charged residues at sensitive surfaces patches, suggesting a mechanism for protection against mis-assembly in these regions. The potential of symmetric proteins to polymerize upon mutation is thus a general mechanism by which protein fibrils can form in vivo, is a target of negative selection, and can be exploited in protein design and nanotechnology. 990-Pos Board B58 Great Interactions: Binding Incorrect Partners to Learn about Protein Recognition and Function Lydie Vamparys1, Benoist Laurent1, Alessandra Carbone2, Sophie Sacquin-Mora1. 1 Institut de Biologie Physico-Chimique, Laboratoire de Biochimie The´orique, CNRS UPR9080, Paris, France, 2Sorbonne Universite´, UPMC U-Paris 6, Laboratoire de Biologie Computationnelle et quantitative, CNRS UMR7238, Paris, France. Protein-protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross-docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein’s binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross-docking predictions using the area under the specificity-sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on
Monday, February 13, 2017
HSA, (~35-40 mg/ml) and g-globulins, IgG, (~10-15 mg/ml). To study and understand the behavior of therapeutic antibodies in the presence of HSA, human IgG, and other serum components, tracer experiments are done pairwise as a function of HSA, IgG and therapeutic protein concentration. A plot of 1/s vs concentration reveals thermodynamic nonideality or a slowing of the sedimentation rate due to itself or another component (s ¼ s0/(1 þ Ksc)). This generates a 3x3 matrix of data that describes self- and cross-term hydrodynamic nonideality Ks. The goal is to develop a preclinical method for quantitative hydrodynamic analysis of therapeutic proteins in crowded environments like serum. (Supported by Boehringer-Ingelheim.) 987-Pos Board B55 Computational Characterization of Oligomerization of FVFLM Peptide and its Ability to Inhibit Beta Amyloid Aggregation Maksim Kouza1, Anirban Banerji2, Andrzej Kolinski1, Irina Alexandra Buhimschi3, Andrzej Kloczkowski2. 1 Faculty of Chemistry, University of Warsaw, Warsaw, Poland, 2Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH, USA, 3Center for Perinatal Research, Nationwide Children’s Hospital, Columbus, OH, USA. Preeclampsia, a pregnancy-specific disorder, shares typical pathophysiological features with protein misfolding disorders including Alzheimer’s disease1. Characteristic for preeclampsia is the involvement of multiple proteins of which fragments of SERPINA1 and b-amyloid co-aggregate in urine and placenta of preeclamptic women. This work explores the biophysical basis of this interaction by investigating the multidimensional efficacy of the FVFLM sequence in SERPINA1, as a model inhibitory agent of b-amyloid aggregation. Several algorithms predict FVFLM peptide as being a highly amyloidogenic2,3. After studying the oligomerization of FVFLM peptides using allatom molecular dynamics simulations with the GROMOS43a1 force field and explicit water, we report that FVFLM can aggregate and its aggregation is spontaneous with a remarkably faster rate than that recorded for KLVFF (aggregation ‘‘hot-spot’’ from b-amyloid). The population of fibril-prone conformations in the monomeric state of KLVFF was found to be lower than FVFLM indicating the faster aggregation process of FVFLM4. The fast kinetics of FVFLM aggregation was found to be driven primarily by core-like aromatic interactions originating from the anti-parallel orientation of complementarily uncharged strands. We also demonstrate a high propensity of FVFLM for KLVFF binding. When present, FVFLM disrupts the b-amyloid aggregation pathway and we propose that FVFLM-like peptides might be used to prevent the assembly of full-length Ab or other pro-amyloidogenic peptides into amyloid fibrils. 1. Buhimschi, I.A. et al. Protein misfolding, congophilia, oligomerization, and defective amyloid processing in preeclampsia. Science translational medicine6, 245ra292 (2014). 2. Zambrano, R. et al. AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures. Nucleic Acids Res (2015). 3. Kouza, M., Faraggi, E., Kolinski, A. & Kloczkowski, A. in Prediction of Protein Secondary Structure, Vol. 1484. (eds. Y. Zhou, A. Kloczkowski, E. Faraggi & Y. Yang) 7-24 (Humana Press, New York; 2016). 4. Nam, H.B., Kouza, M., Hoang, Z. & Li, M.S. Relationship between population of the fibril-prone conformation in the monomeric state and oligomer formation times of peptides: Insights from all-atom simulations. J Chem Phys 132, 165104 (2010) 988-Pos Board B56 A Novel Coarse-Grained Model to Study Liquid-Liquid Phase Separation of Disordered Proteins Gregory L. Dignon1, Wenwei Zheng2, Robert Best2, Jeetain Mittal1. 1 Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, USA, 2National Institutes of Health, Bethesda, MD, USA. Recent studies have led to the discovery of droplets composed of disordered protein chains in a separate liquid-like phase. Such assemblies have been found to be relevant to physiological function as membraneless compartments in living cells including the nucleolus and ribonucleoprotein (RNP) granules as well as many organelles in prokaryotic cells (1). The thermodynamic driving force for this phase separation, however, is still not well characterized. Fused in Sarcoma (FUS) is an RNA binding protein that naturally forms these droplets as RNP granules which aid with DNA repair. The low complexity domain, FUS LC is a fully disordered domain and has been observed to form these droplets on its own in vitro (2). Mutations of FUS can result in transformation of these assemblies into poorly soluble aggregates involved in the pathogenesis of Amyotrophic Lateral Sclerosis and Frontotemporal Dementia (3). As the spatiotemporal scales involved
in the phase separation of proteins cannot be resolved using fully detailed all-atom models, we develop a simple Ca;-based coarse-grained model that treats each amino acid in the chain as a single interaction site. The model is parameterized to treat each of the twenty naturally occurring amino acids differently in order to capture sequence-specific effects. Development of the proposed model involves top-down comparisons with experimental data available from the recent literature as well as comparisons with atomistic simulations of a single chain. We then use this model to characterize the droplet formation for FUS LC including the proposed transition from liquid-like to solid-like aggregates. We are also able to capture known trends in FUS LC phase separation as a function of salt concentration and diseaserelated mutations. This model should aid in the molecular understanding of phase behavior of disordered proteins thus aiding in development of therapeutic strategies. 1.Brangwynne, C. P.; Eckmann, C. R.; Courson, D. S.; Rybarska, A.; Hoege, C.; Gharakhani, J.; Julicher, F.; Hyman, A. A. Science 2009, 324, 1729-1732 2.Burke, K. A.; Janke, A. M.; Rhine, C. L.; Fawzi, N. L. Molecular Cell 2015, 60, 231-241 3.Patel, A.; Lee H. O.; Jawerth, L.; Dechsel, D.; Hyman, A. A.; Alberti, S. and othersCell 2015, 162, 1066-1077 989-Pos Board B57 Proteins Evolve on the Edge of Supramolecular Self-Assembly He´ctor Garcia Seisdedos. Structural Biology, Weizmann Institute of Science, Rehovot, Israel. In cells, over one third of proteins self-associate with multiple copies of themselves to form symmetric homomers. These protein complexes entail unique geometric and functional properties, underlining the virtue of symmetry in proteins. Yet, symmetry can also pose a risk. In sickle cell disease, the symmetry of hemoglobin exacerbates the effect of a mutation, resulting in harmful fibril formation. Here we assessed the universality of this Achilles heel by determining how readily mutations can induce homomers to further self-assemble. We predicted that mutations solely increasing surface hydrophobicity could frequently induce de novo intermolecular interactions driving polymerization. We investigated twelve distinct homomers and, remarkably, we observed their polymerization in all cases, with seven forming micrometer-long fibrils in vivo. Biophysical measurements and electron microscopy indicated that mutants self-assembled in their folded states. Though surface mutations are often regarded as benign due to their minimal impact on protein stability, we exposed their dramatic potential to trigger de novo interactions and polymerization when compounded by symmetry. Accordingly, an analysis of all symmetric proteins of known structure revealed strategically placed charged residues at sensitive surfaces patches, suggesting a mechanism for protection against mis-assembly in these regions. The potential of symmetric proteins to polymerize upon mutation is thus a general mechanism by which protein fibrils can form in vivo, is a target of negative selection, and can be exploited in protein design and nanotechnology. 990-Pos Board B58 Great Interactions: Binding Incorrect Partners to Learn about Protein Recognition and Function Lydie Vamparys1, Benoist Laurent1, Alessandra Carbone2, Sophie Sacquin-Mora1. 1 Institut de Biologie Physico-Chimique, Laboratoire de Biochimie The´orique, CNRS UPR9080, Paris, France, 2Sorbonne Universite´, UPMC U-Paris 6, Laboratoire de Biologie Computationnelle et quantitative, CNRS UMR7238, Paris, France. Protein-protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross-docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein’s binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross-docking predictions using the area under the specificity-sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on