Comparison of neutral and charged polyelectrolyte bottlebrush polymers in dilute salt-free conditions

MRS Advances ◽  
2020 ◽  
Vol 5 (17) ◽  
pp. 899-906
Author(s):  
Alexandros Chremos ◽  
Ferenc Horkay
Keyword(s):  
Coarse Grained ◽  
Side Chains ◽  
Spring Model ◽  
Static Structure ◽  
Polymer Swelling ◽  
Additional Peak ◽  
Structure Factors ◽  
Explicit Solvent ◽  
Dynamics Simulations ◽  
Repulsive Forces

ABSTRACTWe investigate the structure of neutral and charged bottlebrush polymers in salt-free solutions at different polymer concentrations. In particular, we use molecular dynamics simulations by utilizing a coarse-grained bead-spring model that includes an explicit solvent and complementary experiments made by small angle neutron scattering (SANS). We find that the charged groups along the side chains exert significant repulsive forces, resulting in polymer swelling and backbone stretching. In addition to the primary polyelectrolyte peak, we find that bottlebrush polymers exhibit an additional peak in the form and static structure factors, a feature that is absent in neutral polymers. We show that this additional peak describes the intra-molecular correlations between the charged side chains.

scholarly journals From residue coevolution to protein conformational ensembles and functional dynamics

2015 ◽  
Vol 112 (44) ◽  
pp. 13567-13572 ◽  
Author(s):  
Ludovico Sutto ◽  
Simone Marsili ◽  
Alfonso Valencia ◽  
Francesco Luigi Gervasio
Keyword(s):  
Protein Function ◽  
Structure Prediction ◽  
De Novo ◽  
Learning Algorithm ◽  
Coarse Grained ◽  
Static Structure ◽  
Biologically Relevant ◽  
Alternative Structures ◽  
Functional Dynamics ◽  
Dynamics Simulations

The analysis of evolutionary amino acid correlations has recently attracted a surge of renewed interest, also due to their successful use in de novo protein native structure prediction. However, many aspects of protein function, such as substrate binding and product release in enzymatic activity, can be fully understood only in terms of an equilibrium ensemble of alternative structures, rather than a single static structure. In this paper we combine coevolutionary data and molecular dynamics simulations to study protein conformational heterogeneity. To that end, we adapt the Boltzmann-learning algorithm to the analysis of homologous protein sequences and develop a coarse-grained protein model specifically tailored to convert the resulting contact predictions to a protein structural ensemble. By means of exhaustive sampling simulations, we analyze the set of conformations that are consistent with the observed residue correlations for a set of representative protein domains, showing that (i) the most representative structure is consistent with the experimental fold and (ii) the various regions of the sequence display different stability, related to multiple biologically relevant conformations and to the cooperativity of the coevolving pairs. Moreover, we show that the proposed protocol is able to reproduce the essential features of a protein folding mechanism as well as to account for regions involved in conformational transitions through the correct sampling of the involved conformers.

scholarly journals Pressure-Dependent Structure of Methanol–Water Mixtures up to 1.2 GPa: Neutron Diffraction Experiments and Molecular Dynamics Simulations

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1218
Author(s):  
László Temleitner ◽  
Takanori Hattori ◽  
Jun Abe ◽  
Yoichi Nakajima ◽  
László Pusztai
Keyword(s):  
Molecular Dynamics ◽  
Neutron Diffraction ◽  
Liquid Mixtures ◽  
Peak Position ◽  
Distribution Functions ◽  
Size Distributions ◽  
Structure Factors ◽  
Dynamics Simulations ◽  
Repulsive Forces ◽  
Hydrogen Bonded

Total scattering structure factors of per-deuterated methanol and heavy water, CD3OD and D2O, have been determined across the entire composition range as a function of pressure up to 1.2 GPa, by neutron diffraction. The largest variations due to increasing pressure were observed below a scattering variable value of 5 Å−1, mostly as shifts in terms of the positions of the first and second maxima. Molecular dynamics computer simulations, using combinations of all-atom potentials for methanol and various water force fields, were conducted at the experimental pressures with the aim of interpreting neutron diffraction results. The peak-position shifts mentioned above could be qualitatively reproduced by simulations, although in terms of peak intensities, the accord between neutron diffraction and molecular dynamics was much less satisfactory. However, bearing in mind that increasing pressure must have a profound effect on repulsive forces between neighboring molecules, the agreement between experiment and computer simulation can certainly be termed as satisfactory. In order to reveal the influence of changing pressure on local intermolecular structure in these “simplest of complex” hydrogen-bonded liquid mixtures, simulated structures were analyzed in terms of hydrogen bond-related partial radial distribution functions and size distributions of hydrogen-bonded cyclic entities. Distinct differences between pressure-dependent structures of water-rich and methanol-rich composition regions were revealed.

scholarly journals A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

2021 ◽  
Author(s):  
Riccardo Capelli ◽  
Andrea Gardin ◽  
Charly Empereur-mot ◽  
Giovanni Doni ◽  
Giovanni M. Pavan
Keyword(s):  
Phase Transition ◽  
Force Fields ◽  
Coarse Grained ◽  
High Dimensional ◽  
Crucial Point ◽  
Structure And Dynamics ◽  
Intrinsic Resolution ◽  
Explicit Solvent ◽  
Gel Phase ◽  
Dynamics Simulations

<div><div><div><p>Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain insights useful for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are non-trivial to catch. Here we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Positions (SOAP). We compare and classify a set of 13 force fields, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernels-based metrics allows us to compare, discriminate and correlate different force fields at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling non-average events (originating from local transitions), such as for example the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit vs. explicit solvent force fields.</p></div></div></div>

scholarly journals A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

2021 ◽  
Author(s):  
Riccardo Capelli ◽  
Andrea Gardin ◽  
Charly Empereur-mot ◽  
Giovanni Doni ◽  
Giovanni M. Pavan
Keyword(s):  
Phase Transition ◽  
Force Fields ◽  
Coarse Grained ◽  
High Dimensional ◽  
Crucial Point ◽  
Structure And Dynamics ◽  
Intrinsic Resolution ◽  
Explicit Solvent ◽  
Gel Phase ◽  
Dynamics Simulations

<div><div><div><p>Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain insights useful for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are non-trivial to catch. Here we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Positions (SOAP). We compare and classify a set of 13 force fields, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernels-based metrics allows us to compare, discriminate and correlate different force fields at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling non-average events (originating from local transitions), such as for example the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit vs. explicit solvent force fields.</p></div></div></div>

scholarly journals A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

2021 ◽  
Author(s):  
Riccardo Capelli ◽  
Andrea Gardin ◽  
Charly Empereur-mot ◽  
Giovanni Doni ◽  
Giovanni M. Pavan
Keyword(s):  
Phase Transition ◽  
Force Fields ◽  
Coarse Grained ◽  
High Dimensional ◽  
Crucial Point ◽  
Structure And Dynamics ◽  
Intrinsic Resolution ◽  
Explicit Solvent ◽  
Gel Phase ◽  
Dynamics Simulations

<div><div><div><p>Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain insights useful for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are non-trivial to catch. Here we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Positions (SOAP). We compare and classify a set of 13 force fields, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernels-based metrics allows us to compare, discriminate and correlate different force fields at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling non-average events (originating from local transitions), such as for example the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit vs. explicit solvent force fields.</p></div></div></div>

scholarly journals A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

2021 ◽  
Author(s):  
Riccardo Capelli ◽  
Andrea Gardin ◽  
Charly Empereur-mot ◽  
Giovanni Doni ◽  
Giovanni M. Pavan
Keyword(s):  
Phase Transition ◽  
Force Fields ◽  
Coarse Grained ◽  
High Dimensional ◽  
Crucial Point ◽  
Structure And Dynamics ◽  
Intrinsic Resolution ◽  
Explicit Solvent ◽  
Gel Phase ◽  
Dynamics Simulations

<div><div><div><p>Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain insights useful for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are non-trivial to catch. Here we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Positions (SOAP). We compare and classify a set of 13 force fields, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernels-based metrics allows us to compare, discriminate and correlate different force fields at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling non-average events (originating from local transitions), such as for example the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit vs. explicit solvent force fields.</p></div></div></div>

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