Coarse-grained MD simulations reveal beta-amyloid fibrils of various sizes bind to interfacial liquid-ordered and liquid-disordered regions in phase separated lipid rafts with diverse membrane-bound conformational states.
Ontology highlight
ABSTRACT:
SUBMITTER: Cheng SY
PROVIDER: S-EPMC7254575 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The interaction of ?-helical peptides with lipid bilayers is central to our understanding of the physicochemical principles of biological membrane organization and stability. Mutations that alter the position or orientation of an ?-helix within a membrane, or that change the probability that the ?-helix will insert into the membrane, can alter a range of membrane protein functions. We describe a comparative coarse-grained molecular dynamics simulation methodology, based on self-assembly of a lipid bilayer in the presence of an ?-helical peptide, which allows us to model membrane transmembrane helix insertion. We validate this methodology against available experimental data for synthetic model peptides (WALP23 and LS3). Simulation-based estimates of apparent free energies of insertion into a bilayer of cystic fibrosis transmembrane regulator-derived helices correlate well with published data for translocon-mediated insertion. Comparison of values of the apparent free energy of insertion from self-assembly simulations with those from coarse-grained molecular dynamics potentials of mean force for model peptides, and with translocon-mediated insertion of cystic fibrosis transmembrane regulator-derived peptides suggests a nonequilibrium model of helix insertion into bilayers.
| S-EPMC3077683 | biostudies-literature
Project description:Elastin is the dominant building block of elastic fibers that impart structural integrity and elasticity to a range of important tissues, including the lungs, blood vessels, and skin. The elastic fiber assembly process begins with a coacervation stage where tropoelastin monomers reversibly self-assemble into coacervate aggregates that consist of multiple molecules. In this paper, an atomistically based coarse-grained model of tropoelastin assembly is developed. Using the previously determined atomistic structure of tropoelastin, the precursor molecule to elastic fibers, as the basis for coarse-graining, the atomistic model is mapped to a MARTINI-based coarse-grained framework to account for chemical details of protein-protein interactions, coupled to an elastic network model to stabilize the structure. We find that self-assembly of monomers generates up to ?70 ?nm of dense aggregates that are distinct at different temperatures, displaying high temperature sensitivity. Resulting assembled structures exhibit a combination of fibrillar and globular substructures within the bulk aggregates. The results suggest that the coalescence of tropoelastin assemblies into higher order structures may be reinforced in the initial stages of coacervation by directed assembly, supporting the experimentally observed presence of heterogeneous cross-linking. Self-assembly of tropoelastin is driven by interactions of specific hydrophobic domains and the reordering of water molecules in the system. Domain pair orientation analysis throughout the self-assembly process at different temperatures suggests coacervation is a driving force to orient domains for heterogeneous downstream cross-linking. The model provides a framework to characterize macromolecular self-assembly for elastin, and the formulation could easily be adapted to similar assembly systems.
| S-EPMC7061556 | biostudies-literature
Project description:The necessity for accurate and computationally efficient representations of water in atomistic simulations that can span biologically relevant timescales has born the necessity of coarse-grained (CG) modeling. Despite numerous advances, CG water models rely mostly on a-priori specified assumptions. How these assumptions affect the model accuracy, efficiency, and in particular transferability, has not been systematically investigated. Here we propose a data driven comparison and selection for CG water models through a Hierarchical Bayesian framework. We examine CG water models that differ in their level of coarse-graining, structure, and number of interaction sites. We find that the importance of electrostatic interactions for the physical system under consideration is a dominant criterion for the model selection. Multi-site models are favored, unless the effects of water in electrostatic screening are not relevant, in which case the single site model is preferred due to its computational savings. The charge distribution is found to play an important role in the multi-site model's accuracy while the flexibility of the bonds/angles may only slightly improve the models. Furthermore, we find significant variations in the computational cost of these models. We present a data informed rationale for the selection of CG water models and provide guidance for future water model designs.
| S-EPMC6331618 | biostudies-literature
Project description:The mechanosensitive channel of large conductance (MscL) has become a model system in which to understand mechanosensation, a process involved in osmoregulation and many other physiological functions. While a high resolution closed state structure is available, details of the open structure and the gating mechanism remain unknown. In this study we combine coarse grained simulations with restraints from EPR and FRET experiments to study the structural changes involved in gating with much greater level of conformational sampling than has previously been possible. We generated a set of plausible open pore structures that agree well with existing open pore structures and gating models. Most interestingly, we found that membrane thinning induces a kink in the upper part of TM1 that causes an outward motion of the periplasmic loop away from the pore centre. This previously unobserved structural change might present a new mechanism of tension sensing and might be related to a functional role in osmoregulation.
| S-EPMC3447979 | biostudies-literature
Project description:Self-assembly at a liquid-liquid interface is a powerful experimental route to novel nanomaterials. We report herein a computational study of peptide nanotube formation at an oil-water interface. We probe interfacial self-assembly and nanotube formation of the cyclic octapeptide, cyclo [(-L-Trp-D-Leu-)4] as an illustrative example. Individual peptide rings are rapidly adsorbed at the liquid-liquid interface where they self-assemble. Monomeric and dimeric peptide rings lie with their molecular planes mostly parallel to the interface. Longer oligomeric nanotubes are increasingly tilted at the interface and grow by an Oswald ripening mechanism to eventually align their tube axis parallel to the interface. The present results on nanotube assembly suggest that computation will be a useful complement to experiment in understanding the nature of self-assembly of nanomaterials at liquid-liquid interfaces.
| S-EPMC2696305 | biostudies-literature
Project description:Recent advances in coarse-grained (CG) computational models for DNA have enabled molecular-level insights into the behavior of DNA in complex multiscale systems. However, most existing CG DNA models are not compatible with CG protein models, limiting their applications for emerging topics such as protein-nucleic acid assemblies. Here, we present a new computationally efficient CG DNA model. We first use experimental data to establish the model's ability to predict various aspects of DNA behavior, including melting thermodynamics and relevant local structural properties such as the major and minor grooves. We then employ an all-atom hydropathy scale to define non-bonded interactions between protein and DNA sites, to make our DNA model compatible with an existing CG protein model (HPS-Urry), that is extensively used to study protein phase separation, and show that our new model reasonably reproduces the experimental binding affinity for a prototypical protein-DNA system. To further demonstrate the capabilities of this new model, we simulate a full nucleosome with and without histone tails, on a microsecond timescale, generating conformational ensembles and provide molecular insights into the role of histone tails in influencing the liquid-liquid phase separation (LLPS) of HP1α proteins. We find that histone tails interact favorably with DNA, influencing the conformational ensemble of the DNA and antagonizing the contacts between HP1α and DNA, thus affecting the ability of DNA to promote LLPS of HP1α. These findings shed light on the complex molecular framework that fine-tunes the phase transition properties of heterochromatin proteins and contributes to heterochromatin regulation and function. Overall, the CG DNA model presented here is suitable to facilitate micron-scale studies with sub-nm resolution in many biological and engineering applications and can be used to investigate protein-DNA complexes, such as nucleosomes, or LLPS of proteins with DNA, enabling a mechanistic understanding of how molecular information may be propagated at the genome level.
| S-EPMC10245785 | biostudies-literature
Project description:The associative memory, water mediated, structure and energy model (AWSEM) is a coarse-grained protein force field. AWSEM contains physically motivated terms, such as hydrogen bonding, as well as a bioinformatically based local structure biasing term, which efficiently takes into account many-body effects that are modulated by the local sequence. When combined with appropriate local or global alignments to choose memories, AWSEM can be used to perform de novo protein structure prediction. Herein we present structure prediction results for a particular choice of local sequence alignment method based on short residue sequences called fragments. We demonstrate the model's structure prediction capabilities for three levels of global homology between the target sequence and those proteins used for local structure biasing, all of which assume that the structure of the target sequence is not known. When there are no homologues in the database of structures used for local structure biasing, AWSEM calculations produce structural predictions that are somewhat improved compared with prior works using related approaches. The inclusion of a small number of structures from homologous sequences improves structure prediction only marginally, but when the fragment search is restricted to only homologous sequences, AWSEM can perform high resolution structure prediction and can be used for kinetics and dynamics studies.
| S-EPMC3406225 | biostudies-literature
Project description:The size of real nanoparticles (NPs) is polydisperse which can influence the electrical property of polymer nanocomposites (PNCs). Here, we explored the percolated network of mixed NPs with different sizes (small NPs and big NPs) by adopting a molecular dynamics simulation. The simulated results reveal that the big NPs are adverse to building the percolated network compared to the small NPs. Thus, the percolation threshold becomes higher along with increasing the mixing ratio, which denotes the concentration ratio of big NPs to the total NPs. For a better understanding of it, the dispersion state and the number and the size of clusters are employed to analyze the percolated network, which can explain the percolation threshold well. Furthermore, by adopting the Sun's theory (Macromolecules, 2009, 42, 459-463), small and big NPs exhibit a weak antagonistic effect in the simulation if their total concentration is fixed. On the one hand, the number of small NPs is larger than that of big NPs at the same concentration. In addition, one big NP can connect to more others than one small NP. These two contrast effects are responsible for it. Interestingly, the shear flow leads to more contact aggregation structure of NPs which is beneficial to build the new percolated networks. Especially, the big NPs play a more important role in forming the percolated network than small NPs. Consequently, the percolation threshold is reduced at a higher shear rate. In total, our research work provides a further understanding of how the mixed NPs with different sizes form the percolated network in polymer matrix.
| S-EPMC8232767 | biostudies-literature
Project description:Many free-energy sampling and quantum mechanics/molecular mechanics (QM/MM) computations on protein complexes have been performed where, by necessity, a single component is studied isolated in solution while its overall configuration is kept in the complex-like state by either rigid restraints or harmonic constraints. A drawback in these studies is that the system's native fluctuations are lost, both due to the change of environment and the imposition of the extra potential. Yet, we know that having both accurate structure and fluctuations is likely crucial to achieving correct simulation estimates for the subsystem within its native larger protein complex context. In this work, we provide a new approach to this problem by drawing on ideas developed to incorporate experimental information into a molecular simulation by relative entropy minimization to a target system. We show that by using linear biases on coarse-grained (CG) observables (such as distances or angles between large subdomains within a protein), we can maintain the protein in a particular target conformation while also preserving the correct equilibrium fluctuations of the subsystem within its larger biomolecular complex. As an application, we demonstrate this algorithm by training a bias that causes an actin monomer (and trimer) in solution to sample the same average structure and fluctuations as if it were embedded within a much larger actin filament. Additionally, we have developed a number of algorithmic improvements that accelerate convergence of the on-the-fly relative entropy minimization algorithms for this type of application. Finally, we have contributed these methods to the PLUMED open source free energy sampling software library.
| S-EPMC5649387 | biostudies-literature
Project description:Interfacial interactions within a multi-phase polymer solution play critical roles in processing control and mass transportation in chemical engineering. However, the understandings of these roles remain unexplored due to the complexity of the system. In this study, we used an efficient analytical method-a nonequilibrium molecular dynamics (NEMD) simulation-to unveil the molecular interactions and rheology of a multiphase solution containing cetyltrimethyl ammonium chloride (CTAC), polyacrylamide (PAM), and sodium salicylate (NaSal). The associated macroscopic rheological characteristics and shear viscosity of the polymer/surfactant solution were investigated, where the computational results agreed well with the experimental data. The relation between the characteristic time and shear rate was consistent with the power law. By simulating the shear viscosity of the polymer/surfactant solution, we found that the phase transition of micelles within the mixture led to a non-monotonic increase in the viscosity of the mixed solution with the increase in concentration of CTAC or PAM. We expect this optimized molecular dynamic approach to advance the current understanding on chemical-physical interactions within polymer/surfactant mixtures at the molecular level and enable emerging engineering solutions.
| S-EPMC7077399 | biostudies-literature