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Optimal Temperature Set for Replica Exchange Sampling
46a
Sunday, February 12, 2017
Based on recent findings, there is growing evidence that many biological systems in the brain integrate biochemical information with mechanical signals making critical decisions about cell differentiation, synaptic regulation, axonal growth, neuronal migration or proliferation. These events seem to be controlled by the mechanical behavior of intervening proteins in addition to their well-studied biochemistry; and therefore to obtain a quantitative understanding of the mechanical events implicated in neurosignaling events is becoming increasingly important. We have developed to this aim the MechStiff module that we implemented in ProDy API (1), based on an earlier comparison (2) of anisotropic network model predictions with single molecule atomic force microscopy (smAFM) data. We further used MechStiff module to evaluate the effective resistance of individual domains in the neuronal adhesion protein, contactin, to uniaxial tension. Contactins play an important role in maintaining the mechanical integrity and signaling properties of chemical synapses in the brain. To validate the predictions on the the molecular-level stress-strain behavior of contactin, we compared MechStiff predictions with smAFM measurements as well as results from steered molecular dynamics simulations. The multiscale approach combining anisotropic network model with molecular simulations emerges as a useful tool for interpreting experimental data and characterizing contactin nanomechanics. It also helps reveal the stress-induced conformational changes being accommodated by cell adhesion proteins and can be readily extended to elucidating the stress-induced dynamics of multicomponent or modular proteins. 1.Bakan, A., A. Dutta, W. Mao, Y. Liu, C. Chennubhotla, T. R. Lezon, and I. Bahar. 2014. Evol and ProDy for bridging protein sequence evolution and structural dynamics. Bioinformatics 30:2681-2683. 2.Eyal, E., and I. Bahar. 2008. Toward a molecular understanding of the anisotropic response of proteins to external forces: insights from elastic network models. Biophys. J. 94:3424-3435. 232-Plat Optimal Temperature Set for Replica Exchange Sampling Dominik Gront. Faculty of Chemistry, University of Warsaw, Warsaw, Poland. Replica Exchange Monte Carlo method has been introduced to improve sampling of a rugged energy landscape for such systems as polymers, biopolymers and spin glasses. Efficiency of the method however critically depends on the set of replica temperatures used for simulations. A novel method selecting these parameters has been recently proposed1, which numerically evaluates the probability of replica swap between temperatures based on estimated density of states for a system under study. Here we extend this method and prove it provides the optimal set of temperatures i.e. temperatures that guarantee the fastest flow of replicas from the lowest to the highest temperature. During an initial phase of the protocol, energy distributions are collected at different temperatures. Based on these observations, the density of states for the system is computed by the multihistogram method. Knowing the density, improved temperature set is established by minimizing the mean first passage time of replicas in the temperature space. The procedure has been illustrated with a coarse-grained protein folding simulation and all-atom dynamics in AMBER force field. The method has been implemented in BioShell package.2,3 1 D. Gront and A. Kolinski ‘‘Efficient scheme for optimization of parallel tempering Monte Carlo method’’ Journal of Physics: Condensed Matter 2007 19(3) 036225 http://dx.doi.org/10.1088/0953-8984/19/3/036225 2 D. Gront and A. Kolinski ‘‘BioShell - a package of tools for structural biology computations’’ Bioinformatics 2006 22(5):621-622 3 D. Gront and A. Kolinski ‘‘Utility library for structural bioinformatics’’ Bioinformatics 2008 24(4):584-585 233-Plat Molecular Design of a Nanoparticle-Polymer Conjugated Drug Delivery System for PD-166793 in Cardiovascular Repair Merina Jahan1, Stephen K. Roberts2, Andrew B. Greytak2, Mark J. Uline1. 1 Chemical Engineering, University of South Carolina, Columbia, SC, USA, 2 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA. Overexpression of matrix metalloproteinases (MMPs) following myocardial infarction (MI) is linked to deleterious left ventricle remodeling and heart failure. Current research has focused on introducing a therapeutically relevant concentration of effective MMP inhibitor to the MI site to mitigate the harmful tissue remodeling. Theoretical molecular level studies provide an effective platform for designing novel delivery systems for MMP inhibition that can provide valuable insights for experimental researchers. This study focuses on developing a drug delivery pathway using PD-166793 that has shown great promise as a broad spectrum MMP inhibitor in recent years. In this system, PD-166793 is bound to poly methyl acrylic acid (PMAA) polymer and one end of the polymer is tethered to a spherical silica nanoparticle surface to carry the drug to the desired site.
A molecular model using single chain mean field theory (SCMFT) is used to scan the wide range of possible design parameters. The molecular theory properly accounts for the highly non-additive coupling of molecular interactions among all the species. The size, shape, electrical properties and physical conformations of the polymer, drug and solvent are taken into account. The binding of PD-166793 with polymer is modeled by a ligand-receptor binding mechanism. The model is used to study the variation of this binding with changing pH, salt concentration, grafting density and length of the polymer. Experimental studies have shown that this system is capable of retaining PD-166793 at more than 100 times the inhibitory concentration against MMP-2 with a particle concentration of 2.5mg/mL. The model is used as a tool for continual improvements in binding of PD166793 by providing valuable feedback on how the variations of system parameters affect the binding efficiency. 234-Plat Systematic Analysis of Symmetry in Membrane Proteins Antoniya A. Aleksandrova. CSB, NINDS - NIH, Bethesda, MD, USA. Membrane proteins are encoded by around one third of a given genome, and play key roles in transmission of information and chemicals such as neurotransmitters into the cell. Available membrane protein structures have revealed an abundance of symmetry and pseudo-symmetry, which are observed not only in the formation of multi-subunit assemblies, but also in the repetition of internal structural elements. Secondary active transporters provide striking examples of the functional significance of symmetry. For instance, the structures of many transporters consist of two pseudo-symmetric repeats with opposite transmembrane orientations. These repeats can form asymmetric conformations to create a pathway to one side of the membrane, consistent with the so-called alternating access hypothesis. By having one repeat adopt the conformation of the second repeat and vice-versa, the protein can create a new asymmetric structure that is open to the opposite side of the membrane. This ‘‘asymmetry exchange’’ underlies rocking-bundle or elevator-like movements that result in the transport of a substrate. In this context, a systematic study of symmetry should provide a framework for a broader understanding of the mechanistic principles and evolutionary development of membrane proteins. However, existing analyses lack the detail and breadth required for such a systematic study. Therefore, in this project we aim to quantify both the extent and diversity of symmetry relationships in known structures of membrane proteins. To achieve this task, we combine the output of two programs for symmetry detection, namely SymD and CE-Symm, each of which has certain limitations. Our approach also allows us to explore the characteristics that discriminate symmetric from pseudo-symmetric or asymmetric structures. We anticipate that this analysis will provide a valuable foundation for addressing a wide range of questions relating to the function and evolution of these important proteins. 235-Plat Membrane Recruitment can Increase the Number of Protein Assemblies by Many Folds: Insights from Theory and Reaction-Diffusion Simulation Osman N. Yogurtcu, Margaret E. Johnson. Biophysics, Johns Hopkins University, Baltimore, MD, USA. A significant number of the cellular protein interaction networks, such as receptor-mediated signaling and vesicle trafficking pathways, includes reactions that involve membranes as a molecular assembly platform. Membranes both reduce the search space and induce a cooperative binding effect for stabilizing complexes with multiple membrane recruiter molecule binding sites. Mathematical models and computer simulations provide insight into the dynamics of complex formation and help identify general principles that govern successful recruitment and assembly on membranes. However, sufficiently long and physically accurate simulations of protein assemblies are quite challenging. In this work, using equilibrium theory and a very efficient in-lab developed single-molecule scale stochastic simulation software, we provide simple formulas for quantifying how the ratio of membrane-to-solution, both in vitro and in vivo, can change the observed protein-protein interaction strengths of peripheral membrane proteins by orders of magnitude. We show that the magnitude of complex formation enhancement has a simple functional form that applies whenever membrane recruiter concentrations are sufficiently high, and surprisingly, is independent of the protein binding strength. We propose that membrane localization works as a mechanism that ensures assembly only at specific times (after recruitment to surfaces) but does not precisely regulate the proteins involved since they benefit equally from surface restriction. This robust strategy is employed by adaptor proteins involved in clathrin-mediated endocytosis in both yeast and mammalian cells, where their relatively weak binding interactions with one another prevents protein coat assembly in solution, but transitions to a rapid assembly on the plasma membrane.
Sunday, February 12, 2017
Based on recent findings, there is growing evidence that many biological systems in the brain integrate biochemical information with mechanical signals making critical decisions about cell differentiation, synaptic regulation, axonal growth, neuronal migration or proliferation. These events seem to be controlled by the mechanical behavior of intervening proteins in addition to their well-studied biochemistry; and therefore to obtain a quantitative understanding of the mechanical events implicated in neurosignaling events is becoming increasingly important. We have developed to this aim the MechStiff module that we implemented in ProDy API (1), based on an earlier comparison (2) of anisotropic network model predictions with single molecule atomic force microscopy (smAFM) data. We further used MechStiff module to evaluate the effective resistance of individual domains in the neuronal adhesion protein, contactin, to uniaxial tension. Contactins play an important role in maintaining the mechanical integrity and signaling properties of chemical synapses in the brain. To validate the predictions on the the molecular-level stress-strain behavior of contactin, we compared MechStiff predictions with smAFM measurements as well as results from steered molecular dynamics simulations. The multiscale approach combining anisotropic network model with molecular simulations emerges as a useful tool for interpreting experimental data and characterizing contactin nanomechanics. It also helps reveal the stress-induced conformational changes being accommodated by cell adhesion proteins and can be readily extended to elucidating the stress-induced dynamics of multicomponent or modular proteins. 1.Bakan, A., A. Dutta, W. Mao, Y. Liu, C. Chennubhotla, T. R. Lezon, and I. Bahar. 2014. Evol and ProDy for bridging protein sequence evolution and structural dynamics. Bioinformatics 30:2681-2683. 2.Eyal, E., and I. Bahar. 2008. Toward a molecular understanding of the anisotropic response of proteins to external forces: insights from elastic network models. Biophys. J. 94:3424-3435. 232-Plat Optimal Temperature Set for Replica Exchange Sampling Dominik Gront. Faculty of Chemistry, University of Warsaw, Warsaw, Poland. Replica Exchange Monte Carlo method has been introduced to improve sampling of a rugged energy landscape for such systems as polymers, biopolymers and spin glasses. Efficiency of the method however critically depends on the set of replica temperatures used for simulations. A novel method selecting these parameters has been recently proposed1, which numerically evaluates the probability of replica swap between temperatures based on estimated density of states for a system under study. Here we extend this method and prove it provides the optimal set of temperatures i.e. temperatures that guarantee the fastest flow of replicas from the lowest to the highest temperature. During an initial phase of the protocol, energy distributions are collected at different temperatures. Based on these observations, the density of states for the system is computed by the multihistogram method. Knowing the density, improved temperature set is established by minimizing the mean first passage time of replicas in the temperature space. The procedure has been illustrated with a coarse-grained protein folding simulation and all-atom dynamics in AMBER force field. The method has been implemented in BioShell package.2,3 1 D. Gront and A. Kolinski ‘‘Efficient scheme for optimization of parallel tempering Monte Carlo method’’ Journal of Physics: Condensed Matter 2007 19(3) 036225 http://dx.doi.org/10.1088/0953-8984/19/3/036225 2 D. Gront and A. Kolinski ‘‘BioShell - a package of tools for structural biology computations’’ Bioinformatics 2006 22(5):621-622 3 D. Gront and A. Kolinski ‘‘Utility library for structural bioinformatics’’ Bioinformatics 2008 24(4):584-585 233-Plat Molecular Design of a Nanoparticle-Polymer Conjugated Drug Delivery System for PD-166793 in Cardiovascular Repair Merina Jahan1, Stephen K. Roberts2, Andrew B. Greytak2, Mark J. Uline1. 1 Chemical Engineering, University of South Carolina, Columbia, SC, USA, 2 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA. Overexpression of matrix metalloproteinases (MMPs) following myocardial infarction (MI) is linked to deleterious left ventricle remodeling and heart failure. Current research has focused on introducing a therapeutically relevant concentration of effective MMP inhibitor to the MI site to mitigate the harmful tissue remodeling. Theoretical molecular level studies provide an effective platform for designing novel delivery systems for MMP inhibition that can provide valuable insights for experimental researchers. This study focuses on developing a drug delivery pathway using PD-166793 that has shown great promise as a broad spectrum MMP inhibitor in recent years. In this system, PD-166793 is bound to poly methyl acrylic acid (PMAA) polymer and one end of the polymer is tethered to a spherical silica nanoparticle surface to carry the drug to the desired site.
A molecular model using single chain mean field theory (SCMFT) is used to scan the wide range of possible design parameters. The molecular theory properly accounts for the highly non-additive coupling of molecular interactions among all the species. The size, shape, electrical properties and physical conformations of the polymer, drug and solvent are taken into account. The binding of PD-166793 with polymer is modeled by a ligand-receptor binding mechanism. The model is used to study the variation of this binding with changing pH, salt concentration, grafting density and length of the polymer. Experimental studies have shown that this system is capable of retaining PD-166793 at more than 100 times the inhibitory concentration against MMP-2 with a particle concentration of 2.5mg/mL. The model is used as a tool for continual improvements in binding of PD166793 by providing valuable feedback on how the variations of system parameters affect the binding efficiency. 234-Plat Systematic Analysis of Symmetry in Membrane Proteins Antoniya A. Aleksandrova. CSB, NINDS - NIH, Bethesda, MD, USA. Membrane proteins are encoded by around one third of a given genome, and play key roles in transmission of information and chemicals such as neurotransmitters into the cell. Available membrane protein structures have revealed an abundance of symmetry and pseudo-symmetry, which are observed not only in the formation of multi-subunit assemblies, but also in the repetition of internal structural elements. Secondary active transporters provide striking examples of the functional significance of symmetry. For instance, the structures of many transporters consist of two pseudo-symmetric repeats with opposite transmembrane orientations. These repeats can form asymmetric conformations to create a pathway to one side of the membrane, consistent with the so-called alternating access hypothesis. By having one repeat adopt the conformation of the second repeat and vice-versa, the protein can create a new asymmetric structure that is open to the opposite side of the membrane. This ‘‘asymmetry exchange’’ underlies rocking-bundle or elevator-like movements that result in the transport of a substrate. In this context, a systematic study of symmetry should provide a framework for a broader understanding of the mechanistic principles and evolutionary development of membrane proteins. However, existing analyses lack the detail and breadth required for such a systematic study. Therefore, in this project we aim to quantify both the extent and diversity of symmetry relationships in known structures of membrane proteins. To achieve this task, we combine the output of two programs for symmetry detection, namely SymD and CE-Symm, each of which has certain limitations. Our approach also allows us to explore the characteristics that discriminate symmetric from pseudo-symmetric or asymmetric structures. We anticipate that this analysis will provide a valuable foundation for addressing a wide range of questions relating to the function and evolution of these important proteins. 235-Plat Membrane Recruitment can Increase the Number of Protein Assemblies by Many Folds: Insights from Theory and Reaction-Diffusion Simulation Osman N. Yogurtcu, Margaret E. Johnson. Biophysics, Johns Hopkins University, Baltimore, MD, USA. A significant number of the cellular protein interaction networks, such as receptor-mediated signaling and vesicle trafficking pathways, includes reactions that involve membranes as a molecular assembly platform. Membranes both reduce the search space and induce a cooperative binding effect for stabilizing complexes with multiple membrane recruiter molecule binding sites. Mathematical models and computer simulations provide insight into the dynamics of complex formation and help identify general principles that govern successful recruitment and assembly on membranes. However, sufficiently long and physically accurate simulations of protein assemblies are quite challenging. In this work, using equilibrium theory and a very efficient in-lab developed single-molecule scale stochastic simulation software, we provide simple formulas for quantifying how the ratio of membrane-to-solution, both in vitro and in vivo, can change the observed protein-protein interaction strengths of peripheral membrane proteins by orders of magnitude. We show that the magnitude of complex formation enhancement has a simple functional form that applies whenever membrane recruiter concentrations are sufficiently high, and surprisingly, is independent of the protein binding strength. We propose that membrane localization works as a mechanism that ensures assembly only at specific times (after recruitment to surfaces) but does not precisely regulate the proteins involved since they benefit equally from surface restriction. This robust strategy is employed by adaptor proteins involved in clathrin-mediated endocytosis in both yeast and mammalian cells, where their relatively weak binding interactions with one another prevents protein coat assembly in solution, but transitions to a rapid assembly on the plasma membrane.