Long-Time Oxygen and Superoxide Localization in Arabidopsis thaliana Cryptochrome.

Cryptochromes are proteins that are highly conserved across species and in many instances bind the flavin adenine dinucleotide (FAD) cofactor within their photolyase-homology region (PHR) domain. The FAD cofactor has multiple redox states that help catalyze reactions, and absorbs photons at about 450 nm, a feature linked to the light-related functions of cryptochrome proteins. Reactive oxygen species (ROS) are produced from redox reactions involving molecular oxygen and are involved in a myriad of biological processes. Superoxide O2•- is an exemplary ROS that may be formed through electron transfer from FAD to O2, generating an electron radical pair. Although the formation of a superoxide-FAD radical pair has been speculated, it is still unclear if the required process steps could be realized in cryptochrome. Here, we present results from molecular dynamics (MD) simulations of oxygen interacting with the PHR domain of Arabidopsis thaliana cryptochrome 1 (AtCRY1). Using MD simulation trajectories, oxygen binding locations are characterized through both the O2-FAD intermolecular distance and the local protein environment. Oxygen unbinding times are characterized through replica simulations of the bound oxygen. Simulations reveal that oxygen molecules can localize at certain sites within the cryptochrome protein for tens of nanoseconds, and superoxide molecules can localize for significantly longer. This relatively long-duration molecule binding suggests the possibility of an electron-transfer reaction leading to superoxide formation. Estimates of electron-transfer rates using the Marcus theory are performed for the identified potential binding sites. Molecular oxygen binding results are compared with recent results demonstrating long-time oxygen binding within the electron-transfer flavoprotein (ETF), another FAD binding protein.

Long-Time Oxygen Localization in Electron Transfer Flavoprotein.

Reactive oxygen species (ROS) exert a wide range of biological effects from beneficial regulatory function to deleterious oxidative stress. The electron transfer flavoprotein (ETF) is ubiquitous to life and is associated with aerobic metabolism and ROS production due to its location in the mitochondria. Quantifying oxygen localization within the ETF complex is critical for understanding the potential for electron transfer and radical pair formation between flavin adenine dinucleotide (FAD) cofactor and superoxide during ROS formation. Our study employed all-atom molecular dynamics simulations and identified several novel, long-lived oxygen binding sites within the ETF complex that appear near the FAD cofactor. Site locations, the local electrostatic environment, and characteristic oxygen binding times for each site were evaluated to establish factors that may lead to possible charge transfer reactions and superoxide formation within the ETF complex. The study revealed that some oxygen binding sites are naturally linked to protein domain features, suggesting opportunities to engineer and control ROS production and subsequent dynamics.

Criticality in sheared, disordered solids. I. Rate effects in stress and diffusion.

Rate effects in sheared disordered solids are studied using molecular dynamics simulations of binary Lennard-Jones glasses in two and three dimensions. In the quasistatic (QS) regime, systems exhibit critical behavior: the magnitudes of avalanches are power-law distributed with a maximum cutoff that diverges with increasing system size L. With increasing rate, systems move away from the critical yielding point and the average flow stress rises as a power of the strain rate with exponent 1/ß, the Herschel-Bulkley exponent. Finite-size scaling collapses of the stress are used to measure ß as well as the exponent ν which characterizes the divergence of the correlation length. The stress and kinetic energy per particle experience fluctuations with strain that scale as L^{-d/2}. As the largest avalanche in a system scales as L^{α}, this implies α

Criticality in sheared, disordered solids. II. Correlations in avalanche dynamics.

Disordered solids respond to quasistatic shear with intermittent avalanches of plastic activity, an example of the crackling noise observed in many nonequilibrium critical systems. The temporal power spectrum of activity within disordered solids consists of three distinct domains: a novel power-law rise with frequency at low frequencies indicating anticorrelation, white-noise at intermediate frequencies, and a power-law decay at high frequencies. As the strain rate increases, the white-noise regime shrinks and ultimately disappears as the finite strain rate restricts the maximum size of an avalanche. A new strain-rate- and system-size-dependent theory is derived for power spectra in both the quasistatic and finite-strain-rate regimes. This theory is validated using data from overdamped two- and three-dimensional molecular dynamics simulations. We identify important exponents in the yielding transition including the dynamic exponent z which relates the size of an avalanche to its duration, the fractal dimension of avalanches, and the exponent characterizing the divergence in correlations with strain rate. Results are related to temporal correlations within a single avalanche and between multiple avalanches.

Vapor-Deposited Glasses Highlight the Role of Density in Photostability.

Photoresponsive molecules can be integrated into glassy materials to probe the local environment and invoke responsive changes in polymer behavior. For example, recent experiments and simulations have studied increased stability in vapor-deposited glasses by examining the photoisomerization rate of a probe molecule. At the theoretical level, past work relied on coarse-grained simulations to explain the role of photoisomerization on glass behavior. In order to effectively exploit these molecular probes, an ability to quantify how the local environment influences the photoisomerization rate is needed. In this work, we present all-atom molecular-dynamics (MD) simulations of molecular glasses of photoresponsive azobenzene (AB) molecules. The stability of these in-silico samples is probed using photoisomerization, where AB molecules can undergo trans → cis transition upon light exposure. Vapor-deposited and bulk-cooled glasses of AB are simulated using a classical dihedral-switching potential developed by Böckmann et al. (J. Phys. Chem. A 2010, 114, 745-754) to model the photoisomerization process. The MD simulations include thousands of molecules and run for tens of nanoseconds. These size and time scales allow us to explore the broad distribution of photoisomerization wait times, which yields two results. First, the wait-time distributions for both physical vapor deposition and bulk-cooled glasses depend strongly on sample and local density, showing that density or local packing is a primary factor in glass stability against photoisomerization and the experimentally measured photoresponse. Second, the distribution follows a power-law with exponent b ≈ 1.25-1.3 that extends to longer times with increasing density. The power-law distribution suggests a connection with previous experiments that related barriers to photoisomerization with an effective photoisomerization temperature.

Role of many-body interactions in the structure of coarse-grained polymers.

In developing coarse-grained (CG) polymer models it is important to reproduce both local and molecule-scale structure. We develop a procedure for fast calculation of the bond-orientation correlation and the internal squared distance 〈R^{2}(M)〉 through evaluation of the probability distribution functions that represent a CG model. Different CG models inherently contain or omit correlations between CG variables. Here, we construct CG models that contain specific correlations between CG variables. The importance of different correlations is tested on CG models of polyethylene, polytetrafluoroethylene, and poly-L-lactic acid. The chain stiffness and 〈R^{2}(M)〉 are calculated using both analytic evaluation and Monte Carlo sampling, and approximate model results are compared with exact results from all-atom simulations. For polymers with an exponential correlation decay, the bond-orientation correlation and 〈R^{2}(M)〉 indicate which CG variable correlations are most important to reproduce molecule-scale structure. Analysis of the bond-orientation correlation and internal-squared distance indicates that for poly-L-lactic acid the bond-orientation correlation requires qualitatively different additional terms in CG models and quantifies the error in neglecting this important behavior.

Effect of Chain Length Dispersity on the Mobility of Entangled Polymers.

While nearly all theoretical and computational studies of entangled polymer melts have focused on uniform samples, polymer synthesis routes always result in some dispersity, albeit narrow, of distribution of molecular weights (D_{M}=M_{w}/M_{n}∼1.02-1.04). Here, the effects of dispersity on chain mobility are studied for entangled, disperse melts using a coarse-grained model for polyethylene. Polymer melts with chain lengths set to follow a Schulz-Zimm distribution for the same average M_{w}=36 kg/mol with D_{M}=1.0 to 1.16, were studied for times of 600-800 µs using molecular dynamics simulations. This time frame is longer than the time required to reach the diffusive regime. We find that dispersity in this range does not affect the entanglement time or tube diameter. However, while there is negligible difference in the average mobility of chains for the uniform distribution D_{M}=1.0 and D_{M}=1.02, the shortest chains move significantly faster than the longest ones offering a constraint release pathway for the melts for larger D_{M}.

Persistence Length, End-to-End Distance, and Structure of Coarse-Grained Polymers.

Coarse-grained (CG) polymer simulations can access longer times and larger lengths than all-atom (AA) molecular dynamics simulations; however, not all CG models correctly reproduce polymer properties on all length scales. Here we coarse-grain atomistic position data from polyethylene (PE) and polytetrafluoroethylene (PTFE) melt simulations by combining λ backbone carbon atoms in a single CG bead. Resulting CG variables have correlations along the chain backbone that depend on the coarse-graining scale λ and are generally not reproduced by independent bond-length, bond-angle and torsion-angle distributions. By constructing distributions of CG variables equivalent to those from simulated CG potentials we are able to evaluate the bond-orientation correlation for different CG models at reduced computational cost. CG models and potentials that include only nonbonded, bond-length, and bond-angle interactions computed by Boltzmann inversion correctly reproduce the CG variable distributions but do not necessarily reproduce the chain stiffness, overestimating the persistence length Lp and end-to-end distance ⟨ R2⟩1/2 with increasing λ. While CG models that include an independent torsion angle match the bond-orientation correlation and ⟨ R2⟩1/2 better, only approximate models that include correlations between bond and torsion angles match the true bond-orientation correlation.

Corrigendum: Superfast assembly and synthesis of gold nanostructures using nanosecond low-temperature compression via magnetic pulsed power.

This corrects the article DOI: 10.1038/ncomms14778.

Coarse-Grained Modeling of Polyethylene Melts: Effect on Dynamics.

The distinctive viscoelastic behavior of polymers results from a coupled interplay of motion on multiple length and time scales. Capturing the broad time and length scales of polymer motion remains a challenge. Using polyethylene (PE) as a model macromolecule, we construct coarse-grained (CG) models of PE with three to six methyl groups per CG bead and probe two critical aspects of the technique: pressure corrections required after iterative Boltzmann inversion (IBI) to generate CG potentials that match the pressure of reference fully atomistic melt simulations and the transferability of CG potentials across temperatures. While IBI produces nonbonded pair potentials that give excellent agreement between the atomistic and CG pair correlation functions, the resulting pressure for the CG models is large compared with the pressure of the atomistic system. We find that correcting the potential to match the reference pressure leads to nonbonded interactions with much deeper minima and slightly smaller effective bead diameter. However, simulations with potentials generated by IBI and pressure-corrected IBI result in similar mean-square displacements (MSDs) and stress autocorrelation functions G(t) for PE melts. While the time rescaling factor required to match CG and atomistic models is the same for pressure- and non-pressure-corrected CG models, it strongly depends on temperature. Transferability was investigated by comparing the MSDs and stress autocorrelation functions for potentials developed at different temperatures.

Superfast assembly and synthesis of gold nanostructures using nanosecond low-temperature compression via magnetic pulsed power.

Gold nanostructured materials exhibit important size- and shape-dependent properties that enable a wide variety of applications in photocatalysis, nanoelectronics and phototherapy. Here we show the use of superfast dynamic compression to synthesize extended gold nanostructures, such as nanorods, nanowires and nanosheets, with nanosecond coalescence times. Using a pulsed power generator, we ramp compress spherical gold nanoparticle arrays to pressures of tens of GPa, demonstrating pressure-driven assembly beyond the quasi-static regime of the diamond anvil cell. Our dynamic magnetic ramp compression approach produces smooth, shockless (that is, isentropic) one-dimensional loading with low-temperature states suitable for nanostructure synthesis. Transmission electron microscopy clearly establishes that various gold architectures are formed through compressive mesoscale coalescences of spherical gold nanoparticles, which is further confirmed by in-situ synchrotron X-ray studies and large-scale simulation. This nanofabrication approach applies magnetically driven uniaxial ramp compression to mimic established embossing and imprinting processes, but at ultra-short (nanosecond) timescales.

Constant-pressure nested sampling with atomistic dynamics.

The nested sampling algorithm has been shown to be a general method for calculating the pressure-temperature-composition phase diagrams of materials. While the previous implementation used single-particle Monte Carlo moves, these are inefficient for condensed systems with general interactions where single-particle moves cannot be evaluated faster than the energy of the whole system. Here we enhance the method by using all-particle moves: either Galilean Monte Carlo or the total enthalpy Hamiltonian Monte Carlo algorithm, introduced in this paper. We show that these algorithms enable the determination of phase transition temperatures with equivalent accuracy to the previous method at 1/N of the cost for an N-particle system with general interactions, or at equal cost when single-particle moves can be done in 1/N of the cost of a full N-particle energy evaluation. We demonstrate this speed-up for the freezing and condensation transitions of the Lennard-Jones system and show the utility of the algorithms by calculating the order-disorder phase transition of a binary Lennard-Jones model alloy, the eutectic of copper-gold, the density anomaly of water, and the condensation and solidification of bead-spring polymers. The nested sampling method with all three algorithms is implemented in the pymatnest software.

Charged Nanoparticle Attraction in Multivalent Salt Solution: A Classical-Fluids Density Functional Theory and Molecular Dynamics Study.

Negatively charged nanoparticles (NPs) in 1:1, 1:2, and 1:3 electrolyte solutions are studied in a primitive ion model using molecular dynamics (MD) simulations and classical density functional theory (DFT). We determine the conditions for attractive interactions between the like-charged NPs. Ion density profiles and NP-NP interaction free energies are compared between the two methods and are found to be in qualitative agreement. The NP interaction free energy is purely repulsive for monovalent counterions, but can be attractive for divalent and trivalent counterions. Using DFT, the NP interaction free energy for different NP diameters and charges is calculated. The depth and location of the minimum in the interaction depend strongly on the NPs' charge. For certain parameters, the depth of the attractive well can reach 8-10 kBT, indicating that kinetic arrest and aggregation of the NPs due to electrostatic interactions is possible. Rich behavior arises from the geometric constraints of counterion packing at the NP surface. Layering of counterions around the NPs is observed and, as secondary counterion layers form the minimum of the NP-NP interaction free energy shifts to larger separation, and the depth of the free energy minimum varies dramatically. We find that attractive interactions occur with and without NP overcharging.

Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies.

Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. Here we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion is used to derive coarse-grained potentials with 2-6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Using these models we simulate polyethylene melts for times over 500 µs to study the viscoelastic properties of well-entangled polymer melts.

Ligand structure and mechanical properties of single-nanoparticle-thick membranes.

The high mechanical stiffness of single-nanoparticle-thick membranes is believed to result from the local structure of ligand coatings that mediate interactions between nanoparticles. These ligand structures are not directly observable experimentally. We use molecular dynamics simulations to observe variations in ligand structure and simultaneously measure variations in membrane mechanical properties. We have shown previously that ligand end group has a large impact on ligand structure and membrane mechanical properties. Here we introduce and apply quantitative molecular structure measures to these membranes and extend analysis to multiple nanoparticle core sizes and ligand lengths. Simulations of nanoparticle membranes with a nanoparticle core diameter of 4 or 6 nm, a ligand length of 11 or 17 methylenes, and either carboxyl (COOH) or methyl (CH(3)) ligand end groups are presented. In carboxyl-terminated ligand systems, structure and interactions are dominated by an end-to-end orientation of ligands. In methyl-terminated ligand systems large ordered ligand structures form, but nanoparticle interactions are dominated by disordered, partially interdigitated ligands. Core size and ligand length also affect both ligand arrangement within the membrane and the membrane's macroscopic mechanical response, but are secondary to the role of the ligand end group. Moreover, the particular end group (COOH or CH(3)) alters the nature of how ligand length, in turn, affects the membrane properties. The effect of core size does not depend on the ligand end group, with larger cores always leading to stiffer membranes. Asymmetry in the stress and ligand density is observed in membranes during preparation at a water-vapor interface, with the stress asymmetry persisting in all membranes after drying.

Temperature effects on nanostructure and mechanical properties of single-nanoparticle thick membranes.

The properties of mechanically stable single-nanoparticle (NP)-thick membranes have largely been studied at room temperature. How these membranes soften as nanoparticle ligands disorder with increasing temperature is unknown. Molecular dynamics simulations are used to probe the temperature dependence of the mechanical and nanostructural properties of nanoparticle membranes made of 6 nm diameter Au nanoparticles coated with dodecanethiol ligands and terminated with either methyl (CH3) or carboxyl (COOH) terminal groups. For methyl-terminated ligands, interactions along the alkane chain provide mechanical stiffness, with a Young's modulus of 1.7 GPa at 300 K. For carboxyl-terminated chains, end-group interactions are significant, producing stiffer membranes at all temperatures, with a Young's modulus of 3.8 GPa at 300 K. For both end-group types, membrane stiffness is reduced to zero at about 400 K. Ligand structure and mechanical properties of membranes at 300 K that have been annealed at 400 K are comparable to samples that do not undergo thermal annealing.

Coating thickness and coverage effects on the forces between silica nanoparticles in water.

The structure and interactions of coated silica nanoparticles have been studied in water using molecular dynamics simulations. For 5 nm diameter amorphous silica nanoparticles, we studied the effects of varying the chain length and grafting density of polyethylene oxide on the nanoparticle coating's shape and on nanoparticle-nanoparticle effective forces. For short ligands of length n = 6 and n = 20 repeat units, the coatings are radially symmetric while for longer chains (n = 100) the coatings are highly anisotropic. This anisotropy appears to be governed primarily by chain length, with coverage playing a secondary role. For the largest chain lengths considered, the strongly anisotropic shape makes fitting to a simple radial force model impossible. For shorter ligands, where the coatings are isotropic, we found that the force between pairs of nanoparticles is purely repulsive and can be fit to the form (R/2r(core) - 1)(-b) where R is the separation between the center of the nanoparticles, r(core) is the radius of the silica core, and b is measured to be between 2.3 and 4.1.

High strength, molecularly thin nanoparticle membranes.

The unique strength observed in molecular thin films consisting of assemblies of nanoparticles encoded with short organic chains opens an intriguing new realm of controllable materials. Here the fundamental mechanisms underlying this unique mechanical strength are probed by molecular dynamics simulations. Using nanoparticles encoded with short hydrocarbon chains, we show that the mechanical response and failure of single nanoparticle thick membranes depend on subtle changes of the coating. Extremely high moduli were observed in agreement with experiment. We calculate Young's modulus for the membrane system based on properties of the individual components and find that ligand end-group interactions explain the observed changes in mechanical properties. Specifically, for dodecanethiol chains on 6 nm diameter gold cores, Young's modulus is 2.5 GPa for CH_{3} terminated chains and increases by 50% when end groups are replaced by COOH.