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At least 433 records · Page 24

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

Molecular Driving Force for Facet Selectivity of Sequence-Defined Amphiphilic Peptoids at Au–Water Interfaces

Shape-controlled colloidal nanocrystal syntheses often require facet-selective solution-phase chemical additives to regulate surface free energy, atom addition/migration fluxes or particle attachment rates. Because of their highly tunable properties and robustness to a wide range of experimental conditions, peptoids represent a very promising class of next generation functional additives for control over nanocrystal growth. However, understanding the origin of facet selectivity at the molecular level is critical to generalizing their design. In this work, we employ molecular dynamics simulations and biased sampling methods and report stronger selectivity to Au(111) than to Au(100) for Nce3Ncp6, a peptoid that has been shown to assist the formation of five-fold twinned Au nanostars. We find that facet-selectivity is achieved through synergistic effects of both peptoid-surface and solvent-surface interactions. Moreover, the amphiphilic nature of Nce3Ncp6 together with the order of peptoid-peptoid and peptoid-surface binding energies, i.e., peptoid-Au(100) < peptoid-peptoid < peptoid-Au(111), further amplifies its distinct collective behavior on different Au surfaces. Our studies provide a fundamental understanding of the molecular origin of facet-selective adsorption and highlight the possibility of future designs and uses of sequence-defined peptoids for predictive syntheses of nanocrystals with designed shapes and properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spin Dynamics of Quintet and Triplet States Resulting from Singlet Fission in Oriented Terrylenediimide and Quaterrylenediimide Films

Singlet fission in organic semiconductors provides an important opportunity to study high-spin states in electronically coupled chromophores. Photoexcitation of oriented, crystalline films of N,N-bis(pentadec-8-yl)terrylene-3,4:11,12-bis(dicarboximide) (TDI) and N,N-bis (pentadec-8-yl)quaterrylene-3,4:13,14-bis(dicarboximide) (QDI) result in the formation of the correlated triplet pair quintet state, 5 (T 1 T 1 ) and its subsequent dissociation into two triplet (T-1) excitons. Time-resolved electron paramagnetic resonance (TREPR) spectroscopy and X-ray crystallography are used to show that the orientation dependence of 5 (T 1 T 1 ) spin dynamics is retained as it dissociates into two T 1 excitons, while such information is lost in a randomly oriented sample. In addition, the spin dynamics depend on how the molecules are oriented relative to the external applied magnetic field. Dissociation of 5 (T 1 T 1 ) to form two T 1 excitons is more efficient in TDI and leads to a longer T-1 lifetime than in QDI, making TDI a more viable candidate for photovoltaic applications. Since QDI readily forms a highly oriented film, and the lifetime of its 5 (T 1 T 1 ) state is longer than that of TDI, it may be a good candidate for quantum information science applications that require the generation of a quantum- entangled, four-spin state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-Principles Grand-Canonical Simulations of Water Adsorption in Proton-Exchanged Zeolites

Water appears by design or as impurities in many important reactive systems. For those catalyzed by porous solid acids, such as widely used zeolites, experimentally quantifying the amount or elucidating the structure of adsorbed water clusters at reaction conditions is challenging, while computational studies (e.g., first-principles molecular dynamics simulations) often need to assume the loading to examine solvation effects. Furthermore, we perform first-principles grand-canonical simulations to predict water adsorption to H-ZSM-5 zeolites under specified experimental conditions. Presampling with inexpensive force fields and a pool-based parallelization algorithm are used to improve simulation efficiency, while molecular dynamics is used to sample configurations involving hydronium species. We observe that H + exchange dramatically increases the hydrophilicity of zeolite MFI and an appreciable amount of water is present at very low relative humidities. At all conditions examined, the zeolitic protons are found to dissociate readily from the surface basic sites and become mobile by participating in the hydrogen-bonded chains of adsorbed water molecules.

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Investigation of the Effect of Framework Flexibility on CO 2 Adsorption in SIFSIX-3-Cu Using a Machine-Learned Force Field

Metal–organic frameworks (MOFs) offer promise as selective CO 2 sorbents, but successful MOF sorbent materials need high CO 2 binding affinity and selectivity for CO 2 over water. This work focuses on the use of machine-learned force fields (MLFFs) to model CO 2 adsorption in flexible MOFs, with a focus on SIFSIX-3-Cu, an anion-pillared MOF known for its high CO 2 affinity. A preliminary high-throughput screening of over 900 anion-pillared MOFs was performed using rigid UFF+DDEC6 force fields to predict zero-loading heats of adsorption for CO 2 and H 2 O. SIFSIX-3-Cu was selected for further computational study due to its predicted CO 2 heat of adsorption and experimental relevance. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies and forces, with an iterative sampling scheme combining molecular dynamics, geometry optimization, random geometric insertion, and NVT Monte Carlo-based configuration generation to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included, contrasting with previous models that approximated the MOF as rigid. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations with the MLFF produced CO 2 adsorption isotherms in good agreement with experimental data at direct air capture (DAC) pressures (e.g., 40 Pa), in contrast to previous overestimations of CO 2 sorption by models with rigid structures. Bond and angle histogram analysis showed that MOF flexibility increased the variance of fluorine–fluorine diagonal distances at adsorption sites, resulting in a lower predicted sorption for flexible, asymmetric SIFSIX-3-Cu pore geometries compared to the rigid, symmetric DFT-optimized SIFSIX-3-Cu pore geometry. A detailed description of flexibility afforded by the MLFF resulted in an accurately predicted CO 2 uptake (0.88 mmol/g) at low pressure (40 Pa) compared to the experimentally measured value (1.24 mmol/g). In conclusion, these results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low-pressure applications.

adsorption↗

Accurate Binding Energies for Lithium Polysulfides and Assessment of Density Functionals for Lithium–Sulfur Battery Research

Lithium–sulfur batteries have high theoretical energy density, but a better knowledge of their intimate structural details will be helpful in improving their conductivity and long-term cycling behavior. In order to identify the stationary configurations of lithium polysulfides (Li 2 S n , 2 ≤ n ≤ 8) formed in the charging and discharging processes of the lithium–sulfur batteries, ab initio molecular dynamics was employed to sample the configuration space of Li 2 S n , followed by optimization of structures by CCSD(T)-F12b/aug-cc-pVDZ. Here, using the optimized stationary points, we have created the LiSAE38 benchmark database of atomization energies (AEs) of 38 lithium polysulfide isomers by using the higher-level WMS and W3X-L methods. In addition, the performances of 39 density functionals have been assessed against the benchmark AEs and the relative stabilities of Li 2 S n isomers. On the basis of the assessments with the def2-QZVP basis set, the PW6B95, B97-1, B3LYP-D3, TPSS, and DSD-PBEP86 density functionals are the most accurate for the AEs, whereas the mPW2-PLYP-D, DSD-PBEP86, PW6B95, HSE06, and PBEQIDH functionals are most accurate for the relative energies. Local functionals are of special interest because of their lower cost (faster timings in terms of computer resources) for large systems; among the tested local functionals, MN15-L and revM06-L are the most accurate for the calculations of relative stabilities.

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First-Principles Calculation of Water p K a Using the Newly Developed SCAN Functional

Acid/base chemistry is an intriguing topic that still constitutes a challenge for computational chemistry. While estimating the acid dissociation constant (or pK a ) could shed light on many chemistry processes, especially in the fields of biochemistry and geochemistry, evaluating the relative stability between protonated and nonprotonated species is often very difficult. Indeed, a prerequisite for calculating the pK a of any molecule is an accurate description of the energetics of water dissociation. In this study, we applied constrained molecular dynamics simulations, a noncanonical sampling technique, to investigate the water deprotonation process by selecting the OH distance as the reaction coordinate. The calculation is based on density functional theory and the newly developed SCAN functional, which has shown excellent performance in describing water structure. This first benchmark of SCAN on a chemical reaction shows that this functional accurately models the energetics of proton transfer reactions in an aqueous environment. After taking Coulomb long-range corrections and nuclear quantum effects into account, the estimated water pK a is only 1.0 pK a unit different from the target experimental value. Our results show that the combination of SCAN and constrained MD successfully reproduces the chemistry of water and constitutes a good framework for calculating the free energy of chemical reactions of interest.

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Emergent Properties of Antiagglomerant Films Control Methane Transport: Implications for Hydrate Management

The relationship between collective properties and performance of antiagglomerants (AAs) used in hydrate management is handled using molecular dynamics simulations and enhanced sampling techniques. A thin film of AAs adsorbed at the interface between one flat sII methane hydrate substrate and a fluid hydrocarbon mixture containing methane and $n$-dodecane is studied. The AA considered is a surface-active compound with a complex hydrophilic head that contains both amide and tertiary ammonium cation groups and hydrophobic tails. At a sufficiently high AA density, the interplay between the surfactant layer and the liquid hydrocarbon excludes methane from the interfacial region. In this scenario, we combine metadynamics and umbrella sampling frameworks to study accurately the free-energy landscape and the equilibrium rates associated with the transport of one methane molecule across the AA film. We observe that the local configurational changes of the liquid hydrocarbon packed within the AA film are associated with high free-energy barriers for methane transport. The time scales estimated for the transport of methane across the AA film can be, in some cases, comparable to those reported in the literature for the growth of hydrates, suggesting that one possible mechanism by which AAs delay the formation of hydrate plugs could be providing a barrier to methane transport. Considering the interplay between the structural design and collective properties of AAs might be of relevance to improve their performance in flow assurance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Perspective on Multiscale Modeling of Explicit Solvation-Enabled Simulations of Catalysis at Liquid–Solid Interfaces

Catalysis at liquid-solid interfaces is profoundly influenced by the interfacial solvent structure, which affects catalytic activity, selectivity, and reaction pathways. This perspective discusses state-of-the-art multiscale modeling methods that integrate quantum mechanics and molecular mechanics approaches to apply explicit solvent molecules to capture these interfacial phenomena. Specifically, the construction of multiscale models, the importance of capturing the interfacial solvent structure, and the computational strategies used to achieve this are explored, and the challenges in balancing chemical accuracy with computational expense are highlighted. Additionally, this perspective addresses the limitations of current methods. Opportunities for integrating machine learning are proposed. Here, by advancing the efficiency and user friendliness of multiscale modeling, it is argued that deeper insights into heterogeneous catalysis in liquid phases can be provided, which will ultimately contribute to the development of more efficient catalytic processes.

Ab initio molecular dynamics↗

Evaluating the Transport Mechanism for Lignocellulosic Inhibitors in Zymomonas mobilis

The conversion of lignocellulosic biomass to biofuels and bioproducts is limited by small inhibitory molecules generated during the pretreatment process. The diverse compounds within the cell wall hydrolysate including aldehydes, carboxylic acids, phenolics, and alcohols inhibit microbial growth by disrupting microbial membranes. Although Zymomonas mobilis combines high ethanol productivity with hopanoid-rich membranes that confer solvent tolerance, hydrolysate compounds still inhibit microbial growth. One proposed mitigation strategy is to pump these molecules out through active transport processes, reducing direct toxicity. However, if passive permeation rates are high, active transport would create a futile cycle where the exported molecules diffuse back in, creating a net drag on fitness. To investigate this hypothesis, we measure the passive permeation for thirty-three lignocellulose derived compounds using atomistic molecular dynamics simulations with enhanced sampling. Permeability coefficients determined spanned more than eight orders of magnitude driven largely by the balance between hydrophobicity and polarity. Hydrophobic inhibitors such as aromatic acids, aldehydes, and short chain alcohols readily partitioned into the membrane and showed high permeability consistent with rapid passive influx and strong toxicity. Most polar molecules have lower but still appreciable permeation rates, with only the most polar sugars having low permeabilities. By integrating these predictions together with hydrolysate composition information, we find that most of these molecules are so permeable that futile cycles where passive permeation overwhelms efflux is highly likely. These findings provide a predictive framework for strain engineering, highlighting that, for highly permeable inhibitors, reducing extracellular inhibitor concentrations through hydrolysate detoxification, pretreatment optimization, or dilution may be necessary to mitigate futile cycling and improve microbial productivity in industrial biorefineries.

Zymomonas mobilis↗

Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials

Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions.

36 MATERIALS SCIENCE↗

Probing flow-induced nanostructure of complex fluids in arbitrary 2D flows using a fluidic four-roll mill (FFoRM)

Abstract Engineering flow processes to direct the microscopic structure of soft materials represents a growing area of materials research. In situ small-angle neutron scattering under flow (flow-SANS) is an attractive probe of fluid microstructure under simulated processing conditions, but current capabilities require many different sample environments to fully interrogate the deformations a fluid experiences in a realistic processing flow. Inspired by recent advances in microfluidics, we present a fluidic four-roll mill (FFoRM) capable of producing tunable 2D flow fields for in situ SANS measurements, that is intended to allow characterization of complex fluid nanostructure under arbitrary complex flows within a single sample environment. Computational fluid dynamics simulations are used to design a FFoRM that produces spatially homogeneous and sufficiently strong deformation fields. Particle tracking velocimetry experiments are then used to characterize the flows produced in the FFoRM for several classes of non-Newtonian fluids. Finally, a putative FFoRM-SANS workflow is demonstrated and validated through the characterization of flow-induced orientation in a semi-dilute cellulose nanocrystal dispersion under a range of 2D deformations. These novel experiments confirm that, for steady state straining flows at moderate strain rates, the nanocrystals orient along the principal strain-rate axis, in agreement with theories for rigid, rod-like Brownian particles in a homogeneous flow.

36 MATERIALS SCIENCE↗

A bond-order potential for the Al–Cu–H ternary system

Al-Based Al–Cu alloys have a very high strength to density ratio, and are therefore important materials for transportation systems including vehicles and aircrafts. These alloys also appear to have a high resistance to hydrogen embrittlement, and as a result, are being explored for hydrogen related applications. To enable fundamental studies of mechanical behavior of Al–Cu alloys under hydrogen environments, we have developed an Al–Cu–H bond-order potential according to the formalism implemented in the molecular dynamics code LAMMPS. Our potential not only fits well to properties of a variety of elemental and compound configurations (with coordination varying from 1 to 12) including small clusters, bulk lattices, defects, and surfaces, but also passes stringent molecular dynamics simulation tests that sample chaotic configurations. Careful studies verified that this Al–Cu–H potential predicts structural property trends close to experimental results and quantum-mechanical calculations; in addition, it properly captures Al–Cu, Al–H, and Cu–H phase diagrams and enables simulations of H 2 dissociation, chemisorption, and absorption on Al–Cu surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selectivity of nitrate and chloride ions in microporous carbons: the role of anisotropic hydration and applied potentials

Understanding ion transport in porous carbons is critical for a wide range of technologies, including supercapacitors and capacitive deionization for water desalination, yet many details remain poorly understood. For instance, an atomistic understanding of how ion selectivity is influenced by the molecular shape of ions, morphology of the micropores and applied voltages is largely lacking. In this work, we combined molecular dynamics simulations with enhanced sampling methods to elucidate the mechanism of nitrate and chloride selectivity in subnanometer graphene slit-pores. We demonstrate that nitrate is preferentially adsorbed over chloride in the slit-like micropores. This preferential adsorption was found to stem from the weaker hydration energy and unique anisotropy of the ion solvation of nitrate. Beside the effects of ion dehydration, we found that applied potential plays an important role in determining the ion selectivity, leading to a lower selectivity of nitrate over chloride at a high applied potential. We conclude that the measured ion selectivity results from a complex interplay between voltage, confinement, and specific ion effects-including ion shape and local hydration structure.

36 MATERIALS SCIENCE↗

Probing remdesivir nucleotide analogue insertion to SARS-CoV-2 RNA dependent RNA polymerase in viral replication

Remdesivir (RDV) prodrug can be metabolized into a triphosphate form nucleotide analogue (RDV-TP) to bind and insert into the active site of viral RNA dependent RNA polymerase (RdRp) to further interfere with viral genome replication. Here in this work, we computationally studied how RDV-TP binds and inserts to the SARS-CoV-2 RdRp active site, in comparison with natural nucleotide substrate adenosine triphosphate (ATP). To do that, we first constructed atomic structural models of an initial binding complex (active site open) and a substrate insertion complex (active site closed), based on high-resolution cryo-EM structures determined recently for SARS-CoV-2 RdRp or non-structural protein (nsp) 12, in complex with accessory protein factors nsp7 and nsp8. By conducting all-atom molecular dynamics simulation with umbrella sampling strategies on the nucleotide insertion between the open and closed state RdRp complexes, our studies show that RDV-TP can initially bind in a comparatively stabilized state to the viral RdRp active site, as it primarily forms base stacking with the template uracil nucleotide (nt +1), which under freely fluctuations supports a low free energy barrier of the RDV-TP insertion (~1.5 kcal mol -1 ). In comparison, the corresponding natural substrate ATP binds initially to the RdRp active site in Watson–Crick base pairing with the template nt, and inserts into the active site with a medium low free energy barrier (~2.6 kcal mol -1 ), when the fluctuations of the template nt are well quenched. The simulations also show that the initial base stacking of RDV-TP with the template can be specifically stabilized by motif C-S759, S682 (near motif B) with the base, and motif G-K500 with the template backbone. Although the RDV-TP insertion can be hindered by motif F-R555/R553 interaction with the triphosphate, the ATP insertion seems to be facilitated by such interactions. The inserted RDV-TP and ATP can be further distinguished by specific sugar interaction with motif B-T687 and motif A-D623, respectively.

36 MATERIALS SCIENCE↗

Solvent effects on extractant conformational energetics in liquid–liquid extraction: a simulation study of molecular solvents and ionic liquids

Extractant design in liquid–liquid extraction (LLE) is a research frontier of metal ion separations that typically focuses on the direct extractant–metal interactions. However, a more detailed understanding of energetic drivers of separations beyond primary metal coordination is often lacking, including the role of solvent in the extractant phase. In this work, we propose a new mechanism for enhancing metal-complexant energetics with nanostructured solvents. Using molecular dynamics simulations with umbrella sampling, we find that the organic solvent can reshape the energetics of the extractant's intramolecular conformational landscape. Here, we calculate free energy profiles of different conformations of a representative bidentate extractant, n-octyl(phenyl)-N,N-diisobutyl carbamoyl methyl phosphinoxide (CMPO), in four different solvents: dodecane, tributyl phosphate (TBP), and dry and wet ionic liquid (IL) 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf 2 N]). By promoting reorganization of the extractant molecule into its binding conformation, our findings reveal how particular solvents can ameliorate this unfavorable step of the metal separation process. In particular, the charge alternating nanodomains formed in ILs substantially reduce the free energy penalty associated with extractant reorganization. Importantly, using alchemical free energy calculations, we find that this stabilization persists even when we explicitly include the extracted cation. These findings provide insight into the energetic drivers of metal ion separations and potentially suggest a new approach to designing effective separations using a molecular-level understanding of solvent effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the origin of high transient anisotropies: An exemplification in a Cd-porphyrin

Transient anisotropy is a widely used spectroscopic method to access the polarization dynamics of a molecular sample. In this contribution, we present results on 5,10,15,20-tetraphenyl-porphyrinato cadmium (II) in tetrahydrofuran which exhibits values exceeding the typical range between 0.4 and −0.2 in dependence of the probe wavelength. These findings are explained by varying contributions from excited state absorption and ground state bleaching/stimulated emission. Model calculations show that time zero values and time decays are complex values that often do not correlate with the underlying physical processes. As a consequence, the interpretation of anisotropy experiments necessitates extreme care.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗