scholarly journals A multiscale analysis of DNA phase separation: From atomistic to mesoscale level

2018 ◽  
Author(s):  
Tiedong Sun ◽  
Alexander Mirzoev ◽  
Vishal Minhas ◽  
Nikolay Korolev ◽  
Alexander P. Lyubartsev ◽  
...  
Keyword(s):  
Phase Separation ◽  
Liquid Crystalline ◽  
Coarse Graining ◽  
Md Simulations ◽  
Coarse Grained ◽  
Effective Potentials ◽  
Dna Oligonucleotides ◽  
Hexagonally Ordered ◽  
Dna Packing

ABSTRACTDNA condensation and phase separation is of utmost importance for DNA packing in vivo with important applications in medicine, biotechnology and polymer physics. The presence of hexagonally ordered DNA is observed in virus capsids, sperm heads and in dinoflagellates. Rigorous modelling of this process in all-atom MD simulations is presently difficult to achieve due to size and time scale limitations. We used a hierarchical approach for systematic multiscale coarse-grained (CG) simulations of DNA phase separation induced by the three-valent cobalt(III)-hexammine (CoHex3+). Solvent-mediated effective potentials for a CG model of DNA were extracted from all-atom MD simulations. Simulations of several hundred 100-bp-long CG DNA oligonucleotides in the presence of explicit CoHex3+ ions demonstrated aggregation to a liquid crystalline hexagonally ordered phase. Following further coarse-graining and extraction of effective potentials, we conducted modelling at mesoscale level. In agreement with electron microscopy observations, simulations of an 10.2-kbp-long DNA molecule showed phase separation to either a toroid or a fibre with distinct hexagonal DNA packing. The mechanism of toroid formation is analysed in detail. The approach used here is based only on the underlying all-atom force field and uses no adjustable parameters and may be generalized to modelling chromatin up to chromosome size.

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 Liquid-liquid microphase separation leads to formation of membraneless organelles

2019 ◽  
Author(s):  
Srivastav Ranganathan ◽  
Eugene Shakhnovich
Keyword(s):  
Phase Separation ◽  
Rational Design ◽  
Microphase Separation ◽  
Morphological Changes ◽  
Specific Interaction ◽  
Coarse Grained ◽  
High Concentrations ◽  
Macrophase Separation

AbstractProteins and nucleic acids can spontaneously self-assemble into membraneless droplet-like compartments, both in vitro and in vivo. A key component of these droplets are multi-valent proteins that possess several adhesive domains with specific interaction partners (whose number determines total valency of the protein) separated by disordered regions. Here, using multi-scale simulations we show that such proteins self-organize into micro-phase separated droplets of various sizes as opposed to the Flory-like macro-phase separated equilibrium state of homopolymers or equilibrium physical gels. We show that the micro-phase separated state is a dynamic outcome of the interplay between two competing processes: a diffusion-limited encounter between proteins, and the dynamics within small clusters that results in exhaustion of available valencies whereby all specifically interacting domains find their interacting partners within smaller clusters, leading to arrested phase separation. We first model these multi-valent chains as bead-spring polymers with multiple adhesive domains separated by semi-flexible linkers and use Langevin Dynamics (LD) to assess how key timescales depend on the molecular properties of associating polymers. Using the time-scales from LD simulations, we develop a coarse-grained kinetic model to study this phenomenon at longer times. Consistent with LD simulations, the macro-phase separated state was only observed at high concentrations and large interaction valencies. Further, in the regime where cluster sizes approach macro-phase separation, the condensed phase becomes dynamically solid-like, suggesting that it might no longer be biologically functional. Therefore, the micro-phase separated state could be a hallmark of functional droplets formed by proteins with the sticker-spacer architecture.Significance statementMembraneless organells (MO) are ubiquitous in ‘healthy’ living cells, with an altered state in disease. Their formation is likened to liquid-liquid phase separation (LLPS) between MO-forming proteins. However most models of LLPS predict complete macrophase separation while in reality MO’s are small droplets of various sizes, which are malleable to rapid morphological changes. Here we present a microscopic multiscale theoretical study of thermodynamics and kinetics of formation of MO. We show that MO’s are long-living dynamic structures formed as a result of arrested macrophase separation. Our study provides a direct link beween the molecular properies of MO-forming proteins and the morphology and dynamics of MO paving a path to rational design and control of MO.

scholarly journals State-Dependent Lipid Interactions with the A2a Receptor Revealed by MD Simulations Using In Vivo-Mimetic Membranes

2018 ◽  
Author(s):  
Wanling Song ◽  
Hsin-Yung Yen ◽  
Carol V. Robinson ◽  
Mark S.P. Sansom
Keyword(s):  
Conformational Dynamics ◽  
Md Simulations ◽  
Receptor Activation ◽  
Active State ◽  
Coarse Grained ◽  
Lipid Interactions ◽  
A2a Receptor ◽  
The Impact ◽  
Specific Lipid

AbstractG protein-coupled receptors (GPCRs) are the largest family of integral membrane proteins and a major class of drug targets. Membranes are known to have modulatory effects on GPCRs via specific lipid interactions. However, the mechanisms of such modulations in cell membranes and how they influence GPCR functions remain unclear. Here we report coarse-grained MD simulations on the Adenosine A2a receptor embedded in an in vivo mimetic membrane model comprised of 10 different lipid species. Three conformational states of the receptor, i.e. the inactive state, the active state, and the active state with a mini-GS protein bound were simulated to study the impact of protein-lipid interactions on the receptor activation. The simulations revealed three specific lipids (GM3, cholesterol and PIP2) that form stable and preferential interactions with the receptor, differentiating these from bulk lipids such as PS, PE and PC. In total, nine specific lipid-binding sites were revealed. The strength of lipid interaction with these sites depends on the conformational state of the receptor, suggesting that these lipids may regulate the conformational dynamics of the receptor. In particular, we revealed a dual role of PIP2 in promoting A2aR activation, which involves stabilization of both the characteristic outward tilt of helix TM6 within receptor and also the association of A2aR and mini-Gs when the activated complex forms. Structural comparisons suggested that PIP2 may facilitate Gα activation. Our results reveal likely allosteric effects of bound lipids in regulating the functional behaviour of GPCRs, providing a springboard for design of allosteric modulators of these biomedically important receptors.

scholarly journals Coarse-graining molecular dynamics: stochastic models with non-Gaussian force distributions

2019 ◽  
Vol 80 (1-2) ◽  
pp. 457-479 ◽  
Author(s):  
Radek Erban
Keyword(s):  
Molecular Dynamics ◽  
Linear Models ◽  
Coarse Graining ◽  
Md Simulations ◽  
Coarse Grained ◽  
Spatial And Temporal Scales ◽  
Coarse Grained Model ◽  
Non Gaussian ◽  
Low Dimensional ◽  
Cellular Behaviour

Abstract Incorporating atomistic and molecular information into models of cellular behaviour is challenging because of a vast separation of spatial and temporal scales between processes happening at the atomic and cellular levels. Multiscale or multi-resolution methodologies address this difficulty by using molecular dynamics (MD) and coarse-grained models in different parts of the cell. Their applicability depends on the accuracy and properties of the coarse-grained model which approximates the detailed MD description. A family of stochastic coarse-grained (SCG) models, written as relatively low-dimensional systems of nonlinear stochastic differential equations, is presented. The nonlinear SCG model incorporates the non-Gaussian force distribution which is observed in MD simulations and which cannot be described by linear models. It is shown that the nonlinearities can be chosen in such a way that they do not complicate parametrization of the SCG description by detailed MD simulations. The solution of the SCG model is found in terms of gamma functions.

scholarly journals Unsupervised Machine Learning for Analysis of Coexisting Lipid Phases and Domain Growth in Biological Membranes

2019 ◽  
Author(s):  
Cesar A. López ◽  
Velimir V. Vesselinov ◽  
Sandrasegaram Gnanakaran ◽  
Boian S. Alexandrov
Keyword(s):  
Machine Learning ◽  
Phase Separation ◽  
Nonnegative Matrix ◽  
Md Simulations ◽  
Domain Growth ◽  
Coarse Grained ◽  
Unsupervised Machine Learning ◽  
Lipid Mixture ◽  
Spatial Changes ◽  
Machine Learning Approach

ABSTRACTPhase separation in mixed lipid systems has been extensively studied both experimentally and theoretically because of its biological importance. A detailed description of such complex systems undoubtedly requires novel mathematical frameworks that are capable to decompose and categorize the evolution of thousands if not millions of lipids involved in the phenomenon. The interpretation and analysis of Molecular Dynamics (MD) simulations representing temporal and spatial changes in such systems is still a challenging task. Here, we present a new unsupervised machine learning approach based on Nonnegative Matrix Factorization, called NMFk, that successfully extracts physically meaningful features from neighborhood profiles derived from coarse-grained MD simulations of ternary lipid mixture. Our results demonstrate that leveraging NMFk can (a) determine the role of different lipid molecules in phase separation, (b) characterize the formation of nano-domains of lipids, (c) determine the timescales of interest and (d) extract physically meaningful features that uniquely describe the phase separation with broad implications.

scholarly journals Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation

2020 ◽  
Author(s):  
Erik W. Martin ◽  
F. Emil Thomasen ◽  
Nicole M. Milkovic ◽  
Matthew J. Cuneo ◽  
Christy R. Grace ◽  
...  
Keyword(s):  
Phase Separation ◽  
Phase Behavior ◽  
Rna Binding ◽  
Mechanistic Explanation ◽  
Md Simulations ◽  
Low Complexity ◽  
Coarse Grained ◽  
Intrinsically Disordered ◽  
X Ray Scattering

AbstractLiquid-liquid phase separation underlies the membrane-less compartmentalization of cells. Intrinsically disordered low-complexity domains (LCDs) often mediate phase separation, but how their phase behavior is modulated by folded domains is incompletely understood. Here, we interrogate the interplay between folded and disordered domains of the RNA-binding protein hnRNPA1. The LCD of hnRNPA1 is sufficient for mediating phase separation in vitro. However, we show that the folded RRM domains and a folded solubility-tag modify the phase behavior, even in the absence of RNA. Notably, the presence of the folded domains reverses the salt dependence of the driving force for phase separation relative to the LCD alone. Small-angle X-ray scattering experiments and coarse-grained MD simulations show that the LCD interacts transiently with the RRMs and/or the solubility-tag in a salt-sensitive manner, providing a mechanistic explanation for the observed salt-dependent phase separation. These data point to two effects from the folded domains: (1) electrostatically mediated interactions that compact hnRNPA1 and contribute to phase separation, and (2) increased solubility at higher ionic strengths mediated by the folded domains. The interplay between disordered and folded domains can modify the dependence of phase behavior on solution conditions and can obscure signatures of physicochemical interactions underlying phase separation.Graphical abstracthnRNPA1 phase separation is highly salt sensitive.Phase separation of the low-complexity domain (LCD) of hnRNPA1 increases with NaCl. In contrast, phase separation of full-length hnRNPA1 is saltsensitive. At low NaCl concentrations, electrostatic RRM-LCD interactions occur and can contribute positively to phase separation, but they are screened at high NaCl concentrations. The folded domains solubilize hnRNPA1 under these conditions and prevent phase separation.

scholarly journals Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation

2021 ◽  
Author(s):  
Erik W Martin ◽  
F Emil Thomasen ◽  
Nicole M Milkovic ◽  
Matthew J Cuneo ◽  
Christy R Grace ◽  
...  
Keyword(s):  
Phase Separation ◽  
Phase Behavior ◽  
Rna Binding ◽  
Mechanistic Explanation ◽  
Md Simulations ◽  
Low Complexity ◽  
Coarse Grained ◽  
Intrinsically Disordered ◽  
X Ray Scattering

Abstract Liquid–liquid phase separation underlies the membrane-less compartmentalization of cells. Intrinsically disordered low-complexity domains (LCDs) often mediate phase separation, but how their phase behavior is modulated by folded domains is incompletely understood. Here, we interrogate the interplay between folded and disordered domains of the RNA-binding protein hnRNPA1. The LCD of hnRNPA1 is sufficient for mediating phase separation in vitro. However, we show that the folded RRM domains and a folded solubility-tag modify the phase behavior, even in the absence of RNA. Notably, the presence of the folded domains reverses the salt dependence of the driving force for phase separation relative to the LCD alone. Small-angle X-ray scattering experiments and coarse-grained MD simulations show that the LCD interacts transiently with the RRMs and/or the solubility-tag in a salt-sensitive manner, providing a mechanistic explanation for the observed salt-dependent phase separation. These data point to two effects from the folded domains: (i) electrostatically-mediated interactions that compact hnRNPA1 and contribute to phase separation and (ii) increased solubility at higher ionic strengths mediated by the folded domains. The interplay between disordered and folded domains can modify the dependence of phase behavior on solution conditions and can obscure signatures of physicochemical interactions underlying phase separation.

scholarly journals Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Stephan Thaler ◽  
Julija Zavadlav
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Coarse Graining ◽  
Md Simulations ◽  
Coarse Grained ◽  
Thermodynamic Perturbation Theory ◽  
Top Down ◽  
Bottom Up ◽  
Coarse Grained Model ◽  
Gradient Computation

AbstractIn molecular dynamics (MD), neural network (NN) potentials trained bottom-up on quantum mechanical data have seen tremendous success recently. Top-down approaches that learn NN potentials directly from experimental data have received less attention, typically facing numerical and computational challenges when backpropagating through MD simulations. We present the Differentiable Trajectory Reweighting (DiffTRe) method, which bypasses differentiation through the MD simulation for time-independent observables. Leveraging thermodynamic perturbation theory, we avoid exploding gradients and achieve around 2 orders of magnitude speed-up in gradient computation for top-down learning. We show effectiveness of DiffTRe in learning NN potentials for an atomistic model of diamond and a coarse-grained model of water based on diverse experimental observables including thermodynamic, structural and mechanical properties. Importantly, DiffTRe also generalizes bottom-up structural coarse-graining methods such as iterative Boltzmann inversion to arbitrary potentials. The presented method constitutes an important milestone towards enriching NN potentials with experimental data, particularly when accurate bottom-up data is unavailable.

scholarly journals Evaluating coarse-grained MARTINI force-fields for capturing the ripple phase of lipid membranes

2020 ◽  
Author(s):  
Pradyumn Sharma ◽  
Rajat Desikan ◽  
K. Ganapathy Ayappa
Keyword(s):  
Lipid Bilayers ◽  
Lipid Membranes ◽  
Liquid Crystalline ◽  
Intermediate Phase ◽  
Finite Size ◽  
Fluid Phase ◽  
Md Simulations ◽  
Coarse Grained ◽  
Lamellar Phases ◽  
Ripple Phase

AbstractPhospholipids, which are an integral component of cell membranes, exhibit a rich variety of lamellar phases modulated by temperature and composition. Molecular dynamics (MD) simulations have greatly enhanced our understanding of phospholipid membranes by capturing experimentally observed phases and phase transitions at molecular resolution. However, the ripple (Pβ′) membrane phase, observed as an intermediate phase below the main gel-to-liquid crystalline transition with some lipids, has been challenging to capture with MD simulations, both at all-atom and coarse-grained resolution. Here, we systematically assess the ability of five coarse-grained MARTINI 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) lipid force-field (FF) variants, parametrized to reproduce the DPPC gel and fluid phases, for their ability to capture the Pβ′ phase. Upon cooling from the fluid phase to below the phase transition temperature with smaller (380-lipid) and larger (> 2200-lipid) MARTINI and all-atom (CHARMM36 FF) DPPC lipid bilayers, we observed that smaller bilayers with both all-atom and MARTINI FFs sampled interdigitated Pβ′ and ripple-like states, respectively. However, while all-atom simulations of the larger DPPC membranes exhibited the formation of the Pβ′ phase, similar to previous studies, MARTINI membranes did not sample interdigitated ripple-like states at larger system sizes. We then demonstrated that the ripple-like states in smaller MARTINI membranes were kinetically-trapped structures caused by finite size effects rather than being representative of true Pβ′ phases. We showed that even a MARTINI FF variant that could capture the tilted Lβ′ gel phase, a prerequisite for stabilizing the Pβ′ phase, could not capture the rippled phase upon cooling. Our study reveals that the current MARTINI FFs may require specific re-parametrization of the interaction potentials to stabilize lipid interdigitation, a characteristic of the ripple phase.

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