scholarly journals Inserting small molecules across membrane mixtures: Insight from the potential of mean force

2019 ◽  
Author(s):  
Alessia Centi ◽  
Arghya Dutta ◽  
Sapun H. Parekh ◽  
Tristan Bereau
Keyword(s):  
Phase Separation ◽  
Small Molecules ◽  
Lipid Membrane ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Conformational Space ◽  
Coarse Grained ◽  
Computationally Efficient ◽  
Computational Screening ◽  
Wide Range

ABSTRACTSmall solutes have been shown to alter the lateral organization of cell membranes and reconstituted phospholipid bilayers; however, the mechanisms by which these changes happen are still largely unknown. Traditionally, both experiment and simulation studies have been restricted to testing only a few compounds at a time, failing to identify general molecular descriptors or chemical properties that would allow extrapolating beyond the subset of considered solutes. In this work, we probe the competing energetics of inserting a solute in different membrane environments by means of the potential of mean force. We show that these calculations can be used as a computationally-efficient proxy to establish whether a solute will stabilize or destabilize domain phase separation. Combined with umbrella sampling simulations and coarse-grained molecular dynamics simulations, we are able to screen solutes across a wide range of chemistries and polarities. Our results indicate that, for the system under consideration, preferential partitioning and therefore effectiveness in altering membrane phase separation are strictly linked to the location of insertion in the bilayer (i.e., midplane or interface). Our approach represents a fast and simple tool for obtaining structural and thermodynamic insight into the partitioning of small molecules between lipid domains and its relation to phase separation, ultimately providing a platform for identifying the key determinants of this process.SIGNIFICANCEIn this work we explore the relationship between solute chemistry and the thermodynamics of insertion in a mixed lipid membrane. By combining a coarse-grained resolution and umbrella-sampling simulations we efficiently sample conformational space to study the thermodynamics of phase separation. We demonstrate that measures of the potential of mean force—a computationally-efficient quantity—between different lipid environments can serve as a proxy to predict a compound’s ability to alter the thermodynamics of the lipid membrane. This efficiency allows us to set up a computational screening across many compound chemistries, thereby gaining insight beyond the study of a single or a handful of compounds.

scholarly journals Gelation Impairs Phase Separation and Small Molecule Migration in Polymer Mixtures

Polymers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1576
Author(s):  
Biswaroop Mukherjee ◽  
Buddhapriya Chakrabarti
Keyword(s):  
Phase Separation ◽  
Rational Design ◽  
Surface Segregation ◽  
Multiscale Methods ◽  
Coarse Grained ◽  
Polymer Gel ◽  
Polymer Mixtures ◽  
Separation Processes ◽  
Surface Migration ◽  
Wide Range

Surface segregation of the low molecular weight component of a polymeric mixture is a ubiquitous phenomenon that leads to degradation of industrial formulations. We report a simultaneous phase separation and surface migration phenomena in oligomer–polymer ( O P ) and oligomer–gel ( O G ) systems following a temperature quench that induces demixing of components. We compute equilibrium and time varying migrant (oligomer) density profiles and wetting layer thickness in these systems using coarse grained molecular dynamics (CGMD) and mesoscale hydrodynamics (MH) simulations. Such multiscale methods quantitatively describe the phenomena over a wide range of length and time scales. We show that surface migration in gel–oligomer systems is significantly reduced on account of network elasticity. Furthermore, the phase separation processes are significantly slowed in gels leading to the modification of the well known Lifshitz–Slyozov–Wagner (LSW) law ℓ ( τ ) ∼ τ 1 / 3 . Our work allows for rational design of polymer/gel–oligomer mixtures with predictable surface segregation characteristics that can be compared against experiments.

scholarly journals Identifying sequence perturbations to an intrinsically disordered protein that determine its phase-separation behavior

2020 ◽  
Vol 117 (21) ◽  
pp. 11421-11431 ◽  
Author(s):  
Benjamin S. Schuster ◽  
Gregory L. Dignon ◽  
Wai Shing Tang ◽  
Fleurie M. Kelley ◽  
Aishwarya Kanchi Ranganath ◽  
...  
Keyword(s):  
Phase Separation ◽  
Intrinsically Disordered Proteins ◽  
Lipid Membrane ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Sequence Features ◽  
Intrinsically Disordered ◽  
Arginine Residues

Phase separation of intrinsically disordered proteins (IDPs) commonly underlies the formation of membraneless organelles, which compartmentalize molecules intracellularly in the absence of a lipid membrane. Identifying the protein sequence features responsible for IDP phase separation is critical for understanding physiological roles and pathological consequences of biomolecular condensation, as well as for harnessing phase separation for applications in bioinspired materials design. To expand our knowledge of sequence determinants of IDP phase separation, we characterized variants of the intrinsically disordered RGG domain from LAF-1, a model protein involved in phase separation and a key component of P granules. Based on a predictive coarse-grained IDP model, we identified a region of the RGG domain that has high contact probability and is highly conserved between species; deletion of this region significantly disrupts phase separation in vitro and in vivo. We determined the effects of charge patterning on phase behavior through sequence shuffling. We designed sequences with significantly increased phase separation propensity by shuffling the wild-type sequence, which contains well-mixed charged residues, to increase charge segregation. This result indicates the natural sequence is under negative selection to moderate this mode of interaction. We measured the contributions of tyrosine and arginine residues to phase separation experimentally through mutagenesis studies and computationally through direct interrogation of different modes of interaction using all-atom simulations. Finally, we show that despite these sequence perturbations, the RGG-derived condensates remain liquid-like. Together, these studies advance our fundamental understanding of key biophysical principles and sequence features important to phase separation.

scholarly journals Coupling Bulk Phase Separation of Disordered Proteins to Membrane Domain Formation in Molecular Simulations on a Bespoke Compute Fabric

Membranes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 17
Author(s):  
Julian C. Shillcock ◽  
David B. Thomas ◽  
Jonathan R. Beaumont ◽  
Graeme M. Bragg ◽  
Mark L. Vousden ◽  
...  
Keyword(s):  
Phase Separation ◽  
Intrinsically Disordered Proteins ◽  
Lipid Membrane ◽  
Molecular Simulations ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Computational Techniques ◽  
Domain Formation ◽  
Intrinsically Disordered ◽  
Ideal Mixing

Phospholipid membranes surround the cell and its internal organelles, and their multicomponent nature allows the formation of domains that are important in cellular signalling, the immune system, and bacterial infection. Cytoplasmic compartments are also created by the phase separation of intrinsically disordered proteins into biomolecular condensates. The ubiquity of lipid membranes and protein condensates raises the question of how three-dimensional droplets might interact with two-dimensional domains, and whether this coupling has physiological or pathological importance. Here, we explore the equilibrium morphologies of a dilute phase of a model disordered protein interacting with an ideal-mixing, two-component lipid membrane using coarse-grained molecular simulations. We find that the proteins can wet the membrane with and without domain formation, and form phase separated droplets bound to membrane domains. Results from much larger simulations performed on a novel non-von-Neumann compute architecture called POETS, which greatly accelerates their execution compared to conventional hardware, confirm the observations. Reducing the wall clock time for such simulations requires new architectures and computational techniques. We demonstrate here an inter-disciplinary approach that uses real-world biophysical questions to drive the development of new computing hardware and simulation algorithms.

scholarly journals Structure of biomolecular condensates from dissipative particle dynamics simulations

2019 ◽  
Author(s):  
Julian C. Shillcock ◽  
Maelick Brochut ◽  
Etienne Chénais ◽  
John H. Ipsen
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Intrinsically Disordered Proteins ◽  
Liquid Phase Separation ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Wide Range ◽  
End Caps ◽  
Liquid Liquid Phase Separation

ABSTRACTPhase separation of immiscible fluids is a common phenomenon in polymer chemistry, and is recognized as an important mechanism by which cells compartmentalize their biochemical reactions. Biomolecular condensates are condensed fluid droplets in cells that form by liquid-liquid phase separation of intrinsically-disordered proteins. They have a wide range of functions and are associated with chronic neurodegenerative diseases in which they become pathologically rigid. Intrinsically-disordered proteins are conformationally flexible and possess multiple, distributed binding sites for each other or for RNA. However, it remains unclear how their material properties depend on the molecular structure of the proteins. Here we use coarse-grained simulations to explore the phase behavior and structure of a model biomolecular condensate composed of semi-flexible polymers with attractive end-caps in a good solvent. Although highly simplified, the model contains the minimal molecular features that are sufficient to observe liquid-liquid phase separation of soluble polymers. The polymers condense into a porous, three-dimensional network in which their end-caps reversibly bind at junctions. The spatial separation of connected junctions scales with the polymer backbone length as a self-avoiding random walk over a wide range of concentration with a weak affinity-dependent prefactor. By contrast, the average number of polymers that meet at the junctions depends strongly on the end-cap affinity but only weakly on the polymer length. The regularity and porosity of the condensed network suggests a mechanism for cells to regulate biomolecular condensates. Interaction sites along a protein may be turned on or off to modulate the condensate’s porosity and tune the diffusion and interaction of additional proteins.

scholarly journals Evaluating the accuracy of the umbrella sampling plots with different dissociation paths, conformational changes, and structure preparation

2017 ◽  
Author(s):  
Wanli You ◽  
Zhiye Tang ◽  
Chia-en A. Chang
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Conformational Changes ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Conformational Space ◽  
Drug Candidate ◽  
Energy Calculation ◽  
Dissociation Pathway ◽  
Collective Variables

AbstractThe kinetics of ligand dissociation has been found to be crucial for a good drug candidate. Therefore, examining the underlying free energy profile of the dissociation that governs the kinetics becomes important. Umbrella sampling (US), a widely used free energy calculation method, has long been used to explore the dissociation process of ligand-receptor systems. The potential of mean force (PMF) computed from US seems to always produce binding affinity and energy barriers that more or less agree with experiments. However, such PMFs are influenced by many practical aspects, like the method used to generate the initial dissociation pathway, collective variables (CVs) that used to describe the reaction coordinate (RC), and how intensive the sampling is in the conformational space restrained by the CVs. These critical factors were rarely studied. Here we applied US to study the dissociation processes of β-cyclodextrin (β-CD) and p38α complex systems. For β-CD, we used three different β-CD conformations to generate the dissociation path manually. For p38α, we generated the dissociation pathway using accelerated molecular dynamics (AMD) followed by conformational relaxing with short conventional molecular dynamics (MD), steered molecular dynamics (SMD) and manual pulling. We found that even for small β-CD complexes, different β-CD conformations will alter the height of the PMF and different dissociation directions result in appearance/disappearance of local minima. SMD poorly samples the residue sidechain movement, leading to overestimated height of PMF. On the other hand, the AMD pathway relaxed by short conventional MD sampled more accurate structures, resulting in reasonable PMF.

scholarly journals Identifying Sequence Perturbations to an Intrinsically Disordered Protein that Determine Its Phase Separation Behavior

2020 ◽  
Author(s):  
Benjamin S. Schuster ◽  
Gregory L. Dignon ◽  
Wai Shing Tang ◽  
Fleurie M. Kelley ◽  
Aishwarya Kanchi Ranganath ◽  
...  
Keyword(s):  
Phase Separation ◽  
Phase Behavior ◽  
Intrinsically Disordered Proteins ◽  
Lipid Membrane ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Sequence Features ◽  
Intrinsically Disordered ◽  
Model Protein ◽  
Arginine Residues

AbstractPhase separation of intrinsically disordered proteins (IDPs) commonly underlies the formation of membraneless organelles, which compartmentalize molecules intracellularly in the absence of a lipid membrane. Identifying the protein sequence features responsible for IDP phase separation is critical for understanding physiological roles and pathological consequences of biomolecular condensation, as well as for harnessing phase separation for applications in bio-inspired materials design. To expand our knowledge of sequence determinants of IDP phase separation, we characterized variants of the intrinsically disordered RGG domain from LAF-1, a model protein involved in phase separation and a key component of P granules. Based on a predictive coarse-grained IDP model, we identified a region of the RGG domain that has high contact probability and is highly conserved between species; deletion of this region significantly disrupts phase separation in vitro and in vivo. We determined the effects of charge patterning on phase behavior through sequence shuffling. By altering the wild-type sequence, which contains well-mixed charged residues, to increase charge segregation, we designed sequences with significantly increased phase separation propensity. This result indicates the natural sequence is under negative selection to moderate this mode of interaction. We measured the contributions of tyrosine and arginine residues to phase separation experimentally through mutagenesis studies and computationally through direct interrogation of different modes of interaction using all-atom simulations. Finally, we show that in spite of these sequence perturbations, the RGG-derived condensates remain liquid-like. Together, these studies advance a predictive framework and identify key biophysical principles of sequence features important to phase separation.Significance StatementMembraneless organelles are assemblies of highly concentrated biomolecules that form through a liquid-liquid phase separation process. These assemblies are often enriched in intrinsically disordered proteins, which play an important role in driving phase separation. Understanding the sequence-to-phase behavior relationship of these disordered proteins is important for understanding the biochemistry of membraneless organelles, as well as for designing synthetic organelles and biomaterials. In this work, we explore a model protein, the disordered N-terminal domain of LAF-1, and highlight how three key features of the sequence control the protein’s propensity to phase separate. Combining predictive simulations with experiments, we find that phase behavior of this model IDP is dictated by the presence of a short conserved domain, charge patterning, and arginine-tyrosine interactions.

Patterns in diversity and composition of the microbenthos of subarctic intertidal beaches with different morphodynamics

2020 ◽  
Vol 648 ◽  
pp. 19-38
Author(s):  
AI Azovsky ◽  
YA Mazei ◽  
MA Saburova ◽  
PV Sapozhnikov
Keyword(s):  
Species Abundance ◽  
Abundance Ratio ◽  
Wave Action ◽  
Coarse Grained ◽  
Sediment Properties ◽  
Β Diversity ◽  
Α Diversity ◽  
Wide Range ◽  
Similar Mode ◽  
Abundance And Diversity

Diversity and composition of benthic diatom algae and ciliates were studied at several beaches along the White and Barents seas: from highly exposed, reflective beaches with coarse-grained sands to sheltered, dissipative silty-sandy flats. For diatoms, the epipelic to epipsammic species abundance ratio was significantly correlated with the beach index and mean particle size, while neither α-diversity measures nor mean cell length were related to beach properties. In contrast, most of the characteristics of ciliate assemblages (diversity, total abundance and biomass, mean individual weight and percentage of karyorelictids) demonstrated a strong correlation to beach properties, remaining low at exposed beaches but increasing sharply in more sheltered conditions. β-diversity did not correlate with beach properties for either diatoms or ciliates. We suggest that wave action and sediment properties are the main drivers controlling the diversity and composition of the intertidal microbenthos. Diatoms and ciliates, however, demonstrated divergent response to these factors. Epipelic and epipsammic diatoms exhibited 2 different strategies to adapt to their environments and therefore were complementarily distributed along the environmental gradient and compensated for each other in diversity. Most ciliates demonstrated a similar mode of habitat selection but differed in their degree of tolerance. Euryporal (including mesoporal) species were relatively tolerant to wave action and therefore occurred under a wide range of beach conditions, though their abundance and diversity were highest in fine, relatively stable sediments on sheltered beaches, whereas the specific interstitial (i.e. genuine microporal) species were mostly restricted to only these habitats.

Understanding Conformational Entropy in Small Molecules

2020 ◽  
Author(s):  
Lucian Chan ◽  
Garrett Morris ◽  
Geoffrey Hutchison
Keyword(s):  
Small Molecules ◽  
Degrees Of Freedom ◽  
Absolute Error ◽  
Low Energy ◽  
Standard Entropy ◽  
Free Energies ◽  
Conformational Entropy ◽  
Wide Range ◽  
High Degree ◽  
Empirical Corrections

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning

2018 ◽  
Author(s):  
Sherif Tawfik ◽  
Olexandr Isayev ◽  
Catherine Stampfl ◽  
Joseph Shapter ◽  
David Winkler ◽  
...  
Keyword(s):  
Machine Learning ◽  
Band Gap ◽  
Density Functional ◽  
2D Materials ◽  
Van Der Waals ◽  
Building Blocks ◽  
Machine Learning Techniques ◽  
Interlayer Distance ◽  
Computational Screening ◽  
Wide Range

Materials constructed from different van der Waals two-dimensional (2D) heterostructures offer a wide range of benefits, but these systems have been little studied because of their experimental and computational complextiy, and because of the very large number of possible combinations of 2D building blocks. The simulation of the interface between two different 2D materials is computationally challenging due to the lattice mismatch problem, which sometimes necessitates the creation of very large simulation cells for performing density-functional theory (DFT) calculations. Here we use a combination of DFT, linear regression and machine learning techniques in order to rapidly determine the interlayer distance between two different 2D heterostructures that are stacked in a bilayer heterostructure, as well as the band gap of the bilayer. Our work provides an excellent proof of concept by quickly and accurately predicting a structural property (the interlayer distance) and an electronic property (the band gap) for a large number of hybrid 2D materials. This work paves the way for rapid computational screening of the vast parameter space of van der Waals heterostructures to identify new hybrid materials with useful and interesting properties.

In the Quest for a Stable Triplet State in Small Polyaromatic Hydrocarbons : An In-Silico Tool for Rational Design and Prediction

2019 ◽  
Author(s):  
Madhumita Rano ◽  
Sumanta K Ghosh ◽  
Debashree Ghosh
Keyword(s):  
Triplet State ◽  
Small Molecules ◽  
In Silico ◽  
Qualitative Agreement ◽  
Rational Design ◽  
Polyaromatic Hydrocarbons ◽  
Spin Hamiltonian ◽  
Spin Frustration ◽  
Computationally Efficient ◽  
High Level

<div>Combining the roles of spin frustration and geometry of odd and even numbered rings in polyaromatic hydrocarbons (PAHs), we design small molecules that show exceedingly small singlet-triplet gaps and stable triplet ground states. Furthermore, a computationally efficient protocol with a model spin Hamiltonian is shown to be capable of qualitative agreement with respect to high level multireference calculations and therefore, can be used for fast molecular discovery and screening.</div>

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