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Water is often the testing ground for new, advanced force fields. While advanced functional forms for intermolecular interactions have been integral to the development of accurate water models, less attention has been paid to a transferable model for intramolecular valence terms. In this work, we present a one-body energy and dipole moment surface model, named 1B-UCB, that is simple yet accurate and can be feasibly adapted for both standard and advanced potentials. 1B-UCB for water is comparable in accuracy to those with much more complex functional forms, despite having drastically fewer parameters. The parametrization protocol has been implemented as part of the Q-Force automated workflow and requires only a quantum mechanical Hessian calculation as reference data, hence allowing it to be easily extended to a variety of molecular systems beyond water, which we demonstrate on a selection of small molecules with different symmetries.

We developed and implemented a method-independent, fully numerical, finite difference approach to calculating nuclear magnetic resonance shieldings, using gauge-including atomic orbitals. The resulting capability can be used to explore non-standard methods, given only the energy as a function of finite-applied magnetic fields and nuclear spins. For example, standard second-order Møller-Plesset theory (MP2) has well-known efficacy for 1H and 13C shieldings and known limitations for other nuclei such as 15N and 17O. It is, therefore, interesting to seek methods that offer good accuracy for 15N and 17O shieldings without greatly increased compute costs, as well as exploring whether such methods can further improve 1H and 13C shieldings. Using a small molecule test set of 28 species, we assessed two alternatives: κ regularized MP2 (κ-MP2), which provides energy-dependent damping of large amplitudes, and MP2.X, which includes a variable fraction, X, of third-order correlation (MP3). The aug-cc-pVTZ basis was used, and coupled cluster with singles and doubles and perturbative triples [CCSD(T)] results were taken as reference values. Our κ-MP2 results reveal significant improvements over MP2 for 13C and 15N, with the optimal κ value being element-specific. κ-MP2 with κ = 2 offers a 30% rms error reduction over MP2. For 15N, κ-MP2 with κ = 1.1 provides a 90% error reduction vs MP2 and a 60% error reduction vs CCSD. On the other hand, MP2.X with a scaling factor of 0.6 outperformed CCSD for all heavy nuclei. These results can be understood as providing renormalization of doubles amplitudes to partially account for neglected triple and higher substitutions and offer promising opportunities for future applications.

The photo-induced radiolysis of water is an elementary reaction in biology and chemistry, forming solvated electrons, OH radicals, and hydronium cations on fast time scales. Here, we use an optical-pump terahertz-probe spectroscopy setup to trigger the photoionization of water molecules with optical laser pulses at ~400 nm and then time-resolve the transient solvent response with broadband terahertz (THz) fields with a ~90 fs time resolution. We observe three distinct spectral responses. The first is a positive broadband mode that can be attributed to an initial diffuse, delocalized electron with a radius of (22 ± 1) Å, which is short lived (

There is accumulating evidence that many chemical reactions are accelerated by several orders of magnitude in micrometer-sized aqueous or organic liquid droplets compared to their corresponding bulk liquid phase. However, the molecular origin of the enhanced rates remains unclear as in the case of spontaneous appearance of 1 μM hydrogen peroxide in water microdroplets. In this Letter, we consider the range of ionization energies and whether interfacial electric fields of a microdroplet can feasibly overcome the high energy step from hydroxide ions (OH-) to hydroxyl radicals (OH•) in a primary H2O2 mechanism. We find that the vertical ionization energies (VIEs) of partially solvated OH- ions are greatly lowered relative to the average VIE in the bulk liquid, unlike the case of the Cl- anion which shows no reduction in the VIEs regardless of solvation environment. Overall reduced hydrogen-bonding and undercoordination of OH- are structural features that are more readily present at the air-water interface, where the energy scale for ionization can be matched by statistically probable electric field values.

While experiments and continuum models have provided a relatively good understanding of the evaporation of macroscopic water droplets, elucidating how sessile nanodroplets evaporate is an open question critical for advancing nanotechnological applications where nanodroplets can play an essential role. Here, using molecular dynamics simulations, we find that evaporating nanodroplets, in contrast to their macroscopic counterparts, are not always in thermal equilibrium with the substrate and that the vapor concentration on the nanodroplet surface does not reach a steady state. As a result, the evaporative behavior of nanodroplets is significantly different. Regardless of hydrophobicity, nanodroplets do not follow conventional evaporation modes but instead exhibit dynamic wetting behavior characterized by huge, non-equilibrium, isovolumetric fluctuations in the contact angle and contact radius. For hydrophilic nanodroplets, the evaporation rate, controlled by the vapor concentration, decays exponentially over time. Hydrophobic nanodroplets follow stretched exponential kinetics arising from the slower thermalization with the substrate. The evaporative half-lifetime of the nanodroplets is directly related to the thermalization time scale and therefore increases monotonically with the hydrophobicity of the substrate. Finally, the evaporative flux profile along the nanodroplet surface is highly nonuniform but does not diverge at the contact line as the macroscopic continuum models predict.

Intrinsically disordered proteins and unfolded proteins have fluctuating conformational ensembles that are fundamental to their biological function and impact protein folding, stability, and misfolding. Despite the importance of protein dynamics and conformational sampling, time-dependent data types are not fully exploited when defining and refining disordered protein ensembles. Here we introduce a computational framework using an elastic network model and normal-mode displacements to generate a dynamic disordered ensemble consistent with NMR-derived dynamics parameters, including transverse R2 relaxation rates and Lipari-Szabo order parameters (S2 values). We illustrate our approach using the unfolded state of the drkN SH3 domain to show that the dynamical ensembles give better agreement than a static ensemble for a wide range of experimental validation data including NMR chemical shifts, J-couplings, nuclear Overhauser effects, paramagnetic relaxation enhancements, residual dipolar couplings, hydrodynamic radii, single-molecule fluorescence Förster resonance energy transfer, and small-angle X-ray scattering.

The generation of reference data for deep learning models is challenging for reactive systems, and more so for combustion reactions due to the extreme conditions that create radical species and alternative spin states during the combustion process. Here, we extend intrinsic reaction coordinate (IRC) calculations with ab initio MD simulations and normal mode displacement calculations to more extensively cover the potential energy surface for 19 reaction channels for hydrogen combustion. A total of ∼290,000 potential energies and ∼1,270,000 nuclear force vectors are evaluated with a high quality range-separated hybrid density functional, ωB97X-V, to construct the reference data set, including transition state ensembles, for the deep learning models to study hydrogen combustion reaction.

We report a linear combination of atomic dipole (LCAD) method for calculating the bond dipole moments of molecules. We show that the LCAD method reproduces the known molecular dipole moments of small to large molecules with a small error with respect to experimental and benchmark ab initio calculations, and molecular dipole distributions of bulk water that agree with maximally localized Wannier functions. The bond dipole moments derived from LCAD are also chemically interpretable in terms of the trend in bond ionicity in going from neutral to charged molecules. Moreover, the LCAD method accurately captures the influence of electric fields, supported by the correct trend in the change of the dipole moment under a uniform external electric field. The better grounding of bond dipole calculations indicates that it should also serve as a useful approach to bond dipole-field models used in catalysis or to reconstruct the small dipole of a H-terminated graphene flake.

The properties of bulk water and aqueous solutions are known to change in the vicinity of an interface and/or in a confined environment, including the thermodynamics of ion selectivity at interfaces, transition states and pathways of chemical reactions, and nucleation events and phase growth. Here we describe joint progress in identifying unifying concepts about how air, liquid, and solid interfaces can alter molecular properties and chemical reactivity compared to bulk water and multicomponent solutions. We also discuss progress made in interfacial chemistry through advancements in new theory, molecular simulation, and experiments.

Density Functional Theory (DFT) is currently the most tractable choice of theoretical model used to understand the mechanistic pathways for electrocatalytic processes such as CO2 or CO reduction. Here, we assess the performance of two DFT functionals designed specifically to describe surface interactions, RTPSS and RPBE, as well as two popular meta-GGA functionals, SCAN and B97M-rV, that have not been a priori optimized for better interfacial properties. We assess all four functionals against available experimental data for prediction of bulk and bare surface properties on four electrocatalytically relevant metals, Au, Ag, Cu, and Pt, and for binding CO to surfaces of these metals. To partially mitigate issues such as thermal and anharmonic corrections associated with comparing computations with experiments, molecular benchmarks against high level quantum chemistry are reported for CO complexes with Au, Ag, Cu and Pt atoms, as well as the CO-water complex and the water dimer. Overall, we find that the surface modified RPBE functional performs reliably for many of the benchmarks examined here, and the meta-GGA functionals also show promising results. Specifically B97M-rV predicts the correct site preference for CO binding on Ag and Au (the only functional tested here to do so), while RTPSS performs well for surface relaxations and binding of CO on Pt and Cu.

Water under nanoconfinement at ambient conditions has exhibited low-dimensional ice formation and liquid-solid phase transitions, but with structural and dynamical signatures that map onto known regions of water's phase diagram. Using terahertz (THz) absorption spectroscopy and ab initio molecular dynamics, we have investigated the ambient water confined in a supramolecular tetrahedral assembly, and determined that a dynamically distinct network of 9 ± 1 water molecules is present within the nanocavity of the host. The low-frequency absorption spectrum and theoretical analysis of the water in the Ga4L612- host demonstrate that the structure and dynamics of the encapsulated droplet is distinct from any known phase of water. A further inference is that the release of the highly unusual encapsulated water droplet creates a strong thermodynamic driver for the high-affinity binding of guests in aqueous solution for the Ga4L612- supramolecular construct.

Nonreactive force fields are defined by perturbations of electron density that are relatively small, whereas chemical reactivity involves wholesale electronic rearrangements that make and break bonds. Thus, reactive force fields are incredibly difficult to develop compared to nonreactive force fields, yet at the same time, they fill a critical need when ab initio molecular dynamics methods are not affordable. We introduce a new reactive force field model for water that combines modified nonbonded terms of the ReaxFF model and its embedding in the electrostatic interactions described by our recently introduced coarse-grained electron model (C-GeM). The ReaxFF/C-GeM force field is characterized for many energetic and dissociative water properties for water clusters, structure, and dynamical properties under ambient conditions in the condensed phase, as well as the temperature dependence of density and water diffusion, with very good agreement with experiment. The ReaxFF/C-GeM force field should be more transferable and more broadly applicable to a range of reactive systems involving both proton and electron transfer in the condensed phase.

We report the adiabatic energy decomposition analysis (EDA) of density functional theory (DFT) results, shedding light on the physical content of binding energies and carbon monoxide (CO) frequency (υCO) shifts in select first-row transition metal monocarbonyls (MCOs; M = Ti-, V-, Cr-, Co-, Ni-, Cu-, V, Cr, Mn, Ni, Cu, Zn, Cr+, Mn+, Fe+, Cu+, and Zn+). This approach allows for the direct decomposition of υCO, in contrast to previous studies of these systems. Neutral, anionic, and cationic systems are compared, and our results indicate that the relative importance of electrostatic interactions, intramolecular orbital polarization, and charge transfer can vary significantly with the charge and electron configuration of the metal participating in binding. Various anomalous systems are also discussed and incorporated into a general model of MCO binding. Electrostatic interactions and orbital polarization are found to promote blue shifts in υCO, while charge transfer effects encourage υCO red-shifting; previously reported values of υCO are found to be a result of a complex but quantifiable interplay between these physical components. Our computations indicate that CuCO- and ZnCO possess triplet ground states, and also that CrCO- exhibits a non-linear geometry, all in contrast to previous computational results. Advantages and limitations of this model as an approximation to more complicated systems, like those implicated in heterogeneous catalysis, are discussed. We also report benchmark results for MCO geometries, binding energies, and harmonic CO frequencies, and discuss the validity of single-reference wave function and DFT approaches to the study of these transition metal systems.

We have developed a deep learning algorithm for chemical shift prediction for atoms in molecular crystals that utilizes an atom-centered Gaussian density model for the 3D data representation of a molecule. We define multiple channels that describe different spatial resolutions for each atom type that utilizes cropping, pooling, and concatenation to create a multiresolution 3D-DenseNet architecture (MR-3D-DenseNet). Because the training and testing time scale linearly with the number of samples, the MR-3D-DenseNet can exploit data augmentation that takes into account the property of rotational invariance of the chemical shifts, thereby also increasing the size of the training data set by an order of magnitude without additional cost. We obtain very good agreement for 13C, 15N, and 17O chemical shifts when compared to ab initio quantum chemistry methods, with the highest accuracy found for 1H chemical shifts that is comparable to the error between the ab initio results and experimental measurements. Principal component analysis (PCA) is used to both understand these greatly improved predictions for 1H , as well as indicating that chemical shift prediction for 13C, 15N, and 17O, which have far fewer training environments than the 1H atom type, will improve once more unique training samples are made available to exploit the deep network architecture.

Molecular dynamics simulations of intrinsically disordered proteins (IDPs) can provide high resolution structural ensembles if the force field is accurate enough and if the simulation sufficiently samples the conformational space of the IDP with the correct weighting of sub-populations. Here, we investigate the combined force field-sampling problem by testing a standard force field as well as newer fixed charge force fields, the latter specifically motivated for better description of unfolded states and IDPs, and comparing them with a standard temperature replica exchange (TREx) protocol and a non-equilibrium Temperature Cool Walking (TCW) sampling algorithm. The force field and sampling combinations are used to characterize the structural ensembles of the amyloid-beta peptides Aβ42 and Aβ43, which both should be random coils as shown recently by experimental nuclear magnetic resonance (NMR) and 2D Förster resonance energy transfer (FRET) experiments. The results illustrate the key importance of the sampling algorithm: while the standard force field using TREx is in poor agreement with the NMR J-coupling and nuclear Overhauser effect and 2D FRET data, when using the TCW method, the standard and optimized protein-water force field combinations are in very good agreement with the same experimental data since the TCW sampling method produces qualitatively different ensembles than TREx. We also discuss the relative merit of the 2D FRET data when validating structural ensembles using the different force fields and sampling protocols investigated in this work for small IDPs such as the Aβ42 and Aβ43 peptides.

Developing accurate ab initio molecular dynamics (AIMD) models that capture both electronic reorganization and nuclear quantum effects associated with hydrogen bonding is key to quantitative understanding of bulk water and its anomalies as well as its role as a universal solvent. For condensed phase simulations, AIMD has typically relied on the generalized gradient approximation (GGA) of density functional theory (DFT) as the underlying model chemistry for the potential energy surface, with nuclear quantum effects (NQEs) sometimes modeled by performing classical molecular dynamics simulations at elevated temperatures. Here we show that the properties of liquid water obtained from the meta-GGA B97M-rV functional, when evaluated using accelerated path integral molecular dynamics simulations, display accuracy comparable to a computationally expensive dispersion-corrected hybrid functional, revPBE0-D3. We show that the meta-GGA DFT functional reproduces bulk water properties including radial distribution functions, self-diffusion coefficients, and infrared spectra with comparable accuracy of a much more expensive hybrid functional. This work demonstrates that the underlying quality of a good DFT functional requires evaluation with quantum nuclei and that high-temperature simulations are a poor proxy for properly treating NQEs.

Developing accurate ab initio molecular dynamics (AIMD) models that capture both electronic reorganization and nuclear quantum effects associated with hydrogen bonding is key to quantitative understanding of bulk water and its anomalies as well as its role as a universal solvent. For condensed phase simulations, AIMD has typically relied on the generalized gradient approximation (GGA) of density functional theory (DFT) as the underlying model chemistry for the potential energy surface, with nuclear quantum effects (NQEs) sometimes modeled by performing classical molecular dynamics simulations at elevated temperatures. Here we show that the properties of liquid water obtained from the meta-GGA B97M-rV functional, when evaluated using accelerated path integral molecular dynamics simulations, display accuracy comparable to a computationally expensive dispersion-corrected hybrid functional, revPBE0-D3. We show that the meta-GGA DFT functional reproduces bulk water properties including radial distribution functions, self-diffusion coefficients, and infrared spectra with comparable accuracy of a much more expensive hybrid functional. This work demonstrates that the underlying quality of a good DFT functional requires evaluation with quantum nuclei and that high-temperature simulations are a poor proxy for properly treating NQEs.

Tetrahedral assemblies of stoichiometry M4L6 have been proven to catalyze a range of chemical reactions including the carbon-carbon reductive elimination reaction from transition metals such as gold. Here, we perform quantum chemical calculations of Gold(III) transition metal complexes in vacuum, and encapsulated in Ga4L612- or Si4L68- assemblies within both a reaction field continuum solvent and in an aqueous molecular environment with counterions, to rationalize the rate enhancements observed experimentally for the reductive elimination reaction. We find that the Ga4L612- assembly lowers the energy barrier of the reaction compared to Si4L68-, which is consistent with kinetic trends observed experimentally. We have determined that the primary factor for catalytic rate acceleration stems from the electrostatic environment emanating from the Ga4L612- capsule as opposed to the water or counterions.

Tetrahedral assemblies of stoichiometry M4L6 have been proven to catalyze a range of chemical reactions including the carbon-carbon reductive elimination reaction from transition metals such as gold. Here, we perform quantum chemical calculations of Gold(III) transition metal complexes in vacuum, and encapsulated in Ga4L612- or Si4L68- assemblies within both a reaction field continuum solvent and in an aqueous molecular environment with counterions, to rationalize the rate enhancements observed experimentally for the reductive elimination reaction. We find that the Ga4L612- assembly lowers the energy barrier of the reaction compared to Si4L68-, which is consistent with kinetic trends observed experimentally. We have determined that the primary factor for catalytic rate acceleration stems from the electrostatic environment emanating from the Ga4L612- capsule as opposed to the water or counterions.

Cesium-137 is a major byproduct of nuclear energy generation and is environmentally threatening due to its long half-life and affinity for naturally occurring micaceous clays. Recent experimental observations of illite and phlogopite mica indicate that Cs+ is capable of exchanging with K+ bound in the anhydrous interlayers of layered silicates, forming sharp exchange fronts, leading to interstratification of Cs- and K-illite. We present here a coarse-grained (CG) model of the anhydrous illite interlayer developed using iterative Boltzmann inversion that qualitatively and quantitatively reproduces features of a previously proposed feedback mechanism of ion exchange. The CG model represents a 70-fold speedup over all-atom models of clay systems and predicts interlayer expansion for K-illite near ion exchange fronts. Contrary to the longstanding theory that ion exchange in a neighboring layer increases the binding of K in lattice counterion sites leading to interstratification, we find that the presence of neighboring exchanged layers leads to short-range structural relaxations that increase basal spacing and decrease cohesion of the neighboring K-illite layers. We also provide evidence that the formation of alternating Cs- and K-illite interlayers (i.e., ordered interstratification) is both thermodynamically and mechanically favorable compared to exchange in adjacent interlayers.

We analyze the role of solvation for enzymatic catalysis in two distinct, artificially designed Kemp Eliminases, KE07 and KE70, and mutated variants that were optimized by laboratory directed evolution. Using a spatially resolved analysis of hydration patterns, intermolecular vibrations, and local solvent entropies, we identify distinct classes of hydration water and follow their changes upon substrate binding and transition state formation for the designed KE07 and KE70 enzymes and their evolved variants. We observe that differences in hydration of the enzymatic systems are concentrated in the active site and undergo significant changes during substrate recruitment. For KE07, directed evolution reduces variations in the hydration of the polar catalytic center upon substrate binding, preserving strong protein-water interactions, while the evolved enzyme variant of KE70 features a more hydrophobic reaction center for which the expulsion of low-entropy water molecules upon substrate binding is substantially enhanced. While our analysis indicates a system-dependent role of solvation for the substrate binding process, we identify more subtle changes in solvation for the transition state formation, which are less affected by directed evolution.

Flexible nanoscale confinement is critical to understanding the role that bending fluctuations play on biological processes where soft interfaces are ubiquitous or to exploit confinement effects in engineered systems where inherently flexible 2D materials are pervasively employed. Here, using molecular dynamics simulations, we compare the phase behavior of water confined between flexible and rigid graphene sheets as a function of the in-plane density, ρ2D. We find that both cases show commensurate mono-, bi-, and trilayered states; however, the water phase in those states and the transitions between them are qualitatively different for the rigid and flexible cases. The rigid systems exhibit discontinuous transitions between an (n)-layer and an (n+1)-layer state at particular values of ρ2D, whereas under flexible confinement, the graphene sheets bend to accommodate an (n)-layer and an (n+1)-layer state coexisting in equilibrium at the same density. We show that the flexible walls introduce a very different sequence of ice phases and their phase coexistence with vapor and liquid phases than that observed with rigid walls. We discuss the applicability of these results to real experimental systems to shed light on the role of flexible confinement and its interplay with commensurability effects.

In this work, we evaluate the accuracy of the classical AMOEBA model for representing many-body interactions, such as polarization, charge transfer, and Pauli repulsion and dispersion, through comparison against an energy decomposition method based on absolutely localized molecular orbitals (ALMO-EDA) for the water trimer and a variety of ion-water systems. When the 2- and 3-body contributions according to the many-body expansion are analyzed for the ion-water trimer systems examined here, the 3-body contributions to Pauli repulsion and dispersion are found to be negligible under ALMO-EDA, thereby supporting the validity of the pairwise-additive approximation in AMOEBA's 14-7 van der Waals term. However AMOEBA shows imperfect cancellation of errors for the missing effects of charge transfer and incorrectness in the distance dependence for polarization when compared with the corresponding ALMO-EDA terms. We trace the larger 2-body followed by 3-body polarization errors to the Thole damping scheme used in AMOEBA, and although the width parameter in Thole damping can be changed to improve agreement with the ALMO-EDA polarization for points about equilibrium, the correct profile of polarization as a function of intermolecular distance cannot be reproduced. The results suggest that there is a need for re-examining the damping and polarization model used in the AMOEBA force field and provide further insights into the formulations of polarizable force fields in general.

Paramagnetic relaxation enhancement is an NMR technique that has yielded important insight into the structure of folded proteins, although the perturbation introduced by the large spin probe might be thought to diminish its usefulness when applied to characterizing the structural ensembles of intrinsically disordered proteins (IDPs). We compare the computationally generated structural ensembles of the IDP amyloid-β42 (Aβ42) to an alternative sequence in which a nitroxide spin label attached to cysteine has been introduced at its N-terminus. Based on this internally consistent computational comparison, we find that the spin label does not perturb the signature population of the β-hairpin formed by residues 16-21 and 29-36 that is dominant in the Aβ42 reference ensemble. However, the presence of the tag induces a strong population shift in a subset of the original Aβ42 structural sub-populations, including a sevenfold enhancement of the β-hairpin formed by residues 27-31 and 33-38. Through back-calculation of NMR observables from the computational structural ensembles, we show that the structural differences between the labeled and unlabeled peptide would be evident in local residual dipolar couplings, and possibly differences in homonuclear 1H-1H nuclear Overhauser effects (NOEs) and heteronuclear 1H-15N NOEs if the paramagnetic contribution to the longitudinal relaxation does not suppress the NOE intensities in the real experiment. This work shows that molecular simulation provides a complementary approach to resolving the potential structural perturbations introduced by reporter tags that can aid in the interpretation of paramagnetic relaxation enhancement, double electron-electron resonance, and fluorescence resonance energy transfer experiments applied to IDPs.

The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.

We present a new solution for classical polarization that does not require any self-consistent field iterations, the aspect of classical polarization that makes it computationally expensive. The new method builds upon our iEL/SCF Lagrangian scheme that defines a set of auxiliary induced dipoles whose original purpose was to serve as a time-reversible initial guess to the SCF solution of the set of real induced dipoles. In the new iEL/0-SCF approach the auxiliary dipoles now drive the time evolution of the real induced dipoles such that they stay close to the Born-Oppenheimer surface in order to achieve a truly SCF-less method. We show that the iEL/0-SCF exhibits no loss of simulation accuracy when analyzed across bulk water, low to high concentration salt solutions, and small solutes to large proteins in water. In addition, iEL/0-SCF offers significant computational savings over more expensive SCF calculations based on traditional 1 fs time step integration using symplectic integrators and is as fast as reversible reference system propagator algorithms with an outer 2 fs time step.

We present a molecular dynamics study of the effect of core chemistry on star polymer structural and kinetic properties. This work serves to validate the choice of a model adamantane core used in previous simulations to represent larger star polymeric systems in an aqueous environment, as well as to explore how the choice of size and core chemistry using a dendrimer or nanogel core may affect these polymeric nanoparticle systems, particularly with respect to thermosensitivity and solvation properties that are relevant for applications in drug loading and delivery.

Iterative energy minimization with the aim of achieving self-consistency is a common feature of Born-Oppenheimer molecular dynamics (BOMD) and classical molecular dynamics with polarizable force fields. In the former, the electronic degrees of freedom are optimized, while the latter often involves an iterative determination of induced point dipoles. The computational effort of the self-consistency procedure can be reduced by re-using converged solutions from previous time steps. However, this must be done carefully, as not to break time-reversal symmetry, which negatively impacts energy conservation. Self-consistent schemes based on the extended Lagrangian formalism, where the initial guesses for the optimized quantities are treated as auxiliary degrees of freedom, constitute one elegant solution. We report on the performance of two integration schemes with the same underlying extended Lagrangian structure, which we both employ in two radically distinct regimes-in classical molecular dynamics simulations with the AMOEBA polarizable force field and in BOMD simulations with the Onetep linear-scaling density functional theory (LS-DFT) approach. Both integration schemes are found to offer significant improvements over the standard (unpropagated) molecular dynamics formulation in both the classical and LS-DFT regimes.

We have used the AMOEBA model to simulate the THz spectra of two zwitterionic amino acids in aqueous solution, which is compared to the results on these same systems using ab initio molecular dynamics (AIMD) simulations. Overall we find that the polarizable force field shows promising agreement with AIMD data for both glycine and valine in water. This includes the THz spectral assignments and the mode-specific spectral decomposition into intramolecular solute motions as well as distinct solute-water cross-correlation modes some of which cannot be captured by non-polarizable force fields that rely on fixed partial charges. This bodes well for future studies for simulating and decomposing the THz spectra for larger solutes such as proteins or polymers for which AIMD studies are presently intractable. Furthermore, we believe that the current study on rather simple aqueous solutions offers a way to systematically investigate the importance of charge transfer, nuclear quantum effects, and the validity of computationally practical density functionals, all of which are needed to fully quantitatively capture complex dynamical motions in the condensed phase.

The VV10 and rVV10 nonlocal correlation functionals are consistently implemented and assessed, with the goal of determining if the rVV10 nonlocal correlation functional can replace the VV10 nonlocal correlation functional in the recently developed B97M-V density functional, to give the B97M-rV density functional. Along the way, four density functionals are simultaneously tested: VV10, rVV10, B97M-V, and B97M-rV. An initial assessment is carried out across the S22 data set, and the short-range damping variable, b, is varied for all four density functionals in order to determine the sensitivity of the functionals to the empirical parameter. The results of this test indicate that a value of b = 6 (fortuitously the same as that in B97M-V) is suitable for B97M-rV. The functionals are then compared across an extensive database of interaction energies, and it is demonstrated that B97M-rV either matches or outperforms B97M-V for all of the tests considered. Finally, the optimization of b across the S22 data set is extended to two range-separated hybrid density functionals, ωB97X-V and ωB97M-V, and a value of b = 6.2 is recommended for both ωB97X-rV and ωB97M-rV.

In this work, we characterize the nucleation and elongation mechanisms of the "diseased" polymorph of the amyloid-β 40 (Aβ40) fibril using an off-lattice coarse-grained (CG) protein model. After determining the nucleation size and subsequent stable protofibrillar structure from the CG model, validated with all-atom simulations, we consider the "lock and dock" and "activated monomer" fibril elongation mechanisms for the protofibril by statistical additions of a monomer drawn from four different ensembles of the free Aβ40 peptide to grow the fibril. Our CG model shows that the dominant mechanism for fibril elongation is the lock and dock mechanism across all monomer ensembles, even when the monomer is in the activated form. Although our CG model finds no thermodynamic difference between the two fibril elongation mechanisms, the activated monomer is found to be kinetically faster by a factor of 2 for the "locking" step compared with all other structured or unstructured monomer ensembles.

We compare two standard replica exchange methods using temperature and dielectric constant as the scaling variables for independent replicas against two new corresponding enhanced sampling methods based on non-equilibrium statistical cooling (temperature) or descreening (dielectric). We test the four methods on a rough 1D potential as well as for alanine dipeptide in water, for which their relatively small phase space allows for the ability to define quantitative convergence metrics. We show that both dielectric methods are inferior to the temperature enhanced sampling methods, and in turn show that temperature cool walking (TCW) systematically outperforms the standard temperature replica exchange (TREx) method. We extend our comparisons of the TCW and TREx methods to the 5 residue met-enkephalin peptide, in which we evaluate the Kullback-Leibler divergence metric to show that the rate of convergence between two independent trajectories is faster for TCW compared to TREx. Finally we apply the temperature methods to the 42 residue amyloid-β peptide in which we find non-negligible differences in the disordered ensemble using TCW compared to the standard TREx. All four methods have been made available as software through the OpenMM Omnia software consortium (http://www.omnia.md/).

In this work we present a replicated data hybrid OpenMP/MPI implementation of a hierarchical progression of approximate classical polarizable models that yields speedups of up to ∼10 compared to the standard OpenMP implementation of the exact parent AMOEBA polarizable model. In addition, our parallel implementation exhibits reasonable weak and strong scaling. The resulting parallel software will prove useful for those who are interested in how molecular properties converge in the condensed phase with respect to the MBE, it provides a fruitful test bed for exploring different electrostatic embedding schemes, and offers an interesting possibility for future exascale computing paradigms.

We present a novel quantum mechanical/molecular mechanics (QM/MM) approach in which a quantum subsystem is coupled to a classical subsystem described by the AMOEBA polarizable force field. Our approach permits mutual polarization between the QM and MM subsystems, effected through multipolar electrostatics. Self-consistency is achieved for both the QM and MM subsystems through a total energy minimization scheme. We provide an expression for the Hamiltonian of the coupled QM/MM system, which we minimize using gradient methods. The QM subsystem is described by the onetep linear-scaling DFT approach, which makes use of strictly localized orbitals expressed in a set of periodic sinc basis functions equivalent to plane waves. The MM subsystem is described by the multipolar, polarizable force field AMOEBA, as implemented in tinker. Distributed multipole analysis is used to obtain, on the fly, a classical representation of the QM subsystem in terms of atom-centered multipoles. This auxiliary representation is used for all polarization interactions between QM and MM, allowing us to treat them on the same footing as in AMOEBA. We validate our method in tests of solute-solvent interaction energies, for neutral and charged molecules, demonstrating the simultaneous optimization of the quantum and classical degrees of freedom. Encouragingly, we find that the inclusion of explicit polarization in the MM part of QM/MM improves the agreement with fully QM calculations.

Advanced potential energy surfaces are defined as theoretical models that explicitly include many-body effects that transcend the standard fixed-charge, pairwise-additive paradigm typically used in molecular simulation. However, several factors relating to their software implementation have precluded their widespread use in condensed-phase simulations: the computational cost of the theoretical models, a paucity of approximate models and algorithmic improvements that can ameliorate their cost, underdeveloped interfaces and limited dissemination in computational code bases that are widely used in the computational chemistry community, and software implementations that have not kept pace with modern high-performance computing (HPC) architectures, such as multicore CPUs and modern graphics processing units (GPUs). In this Feature Article we review recent progress made in these areas, including well-defined polarization approximations and new multipole electrostatic formulations, novel methods for solving the mutual polarization equations and increasing the MD time step, combining linear-scaling electronic structure methods with new QM/MM methods that account for mutual polarization between the two regions, and the greatly improved software deployment of these models and methods onto GPU and CPU hardware platforms. We have now approached an era where multipole-based polarizable force fields can be routinely used to obtain computational results comparable to state-of-the-art density functional theory while reaching sampling statistics that are acceptable when compared to that obtained from simpler fixed partial charge force fields.

Recently developed density functionals have good accuracy for both thermochemistry (TC) and non-covalent interactions (NC) if very large atomic orbital basis sets are used. To approach the basis set limit with potentially lower computational cost, a new self-consistent field (SCF) scheme is presented that employs minimal adaptive basis (MAB) functions. The MAB functions are optimized on each atomic site by minimizing a surrogate function. High accuracy is obtained by applying a perturbative correction (PC) to the MAB calculation, similar to dual basis approaches. Compared to exact SCF results, using this MAB-SCF (PC) approach with the same large target basis set produces

Side chain entropy and mutual entropy information between residue pairs have been calculated for two de novo designed Kemp eliminase enzymes, KE07 and KE70, and for their most improved versions at the end of laboratory directed evolution (LDE). We find that entropy, not just enthalpy, helped to destabilize the preference for the reactant state complex of the designed enzyme as well as favoring stabilization of the transition state complex for the best LDE enzymes. Furthermore, residues with the highest side chain couplings as measured by mutual information, when experimentally mutated, were found to diminish or annihilate catalytic activity, some of which were far from the active site. In summary, our findings demonstrate how side chain fluctuations and their coupling can be an important design feature for de novo enzymes, and furthermore could be utilized in the computational steps in lieu of or in addition to the LDE steps in future enzyme design projects.

We have adapted a hybrid extended Lagrangian self-consistent field (EL/SCF) approach, developed for time reversible Born Oppenheimer molecular dynamics for quantum electronic degrees of freedom, to the problem of classical polarization. In this context, the initial guess for the mutual induction calculation is treated by auxiliary induced dipole variables evolved via a time-reversible velocity Verlet scheme. However, we find numerical instability, which is manifested as an accumulation in the auxiliary velocity variables, that in turn results in an unacceptable increase in the number of SCF cycles to meet even loose convergence tolerances for the real induced dipoles over the course of a 1 ns trajectory of the AMOEBA14 water model. By diagnosing the numerical instability as a problem of resonances that corrupt the dynamics, we introduce a simple thermostating scheme, illustrated using Berendsen weak coupling and Nose-Hoover chain thermostats, applied to the auxiliary dipole velocities. We find that the inertial EL/SCF (iEL/SCF) method provides superior energy conservation with less stringent convergence thresholds and a correspondingly small number of SCF cycles, to reproduce all properties of the polarization model in the NVT and NVE ensembles accurately. Our iEL/SCF approach is a clear improvement over standard SCF approaches to classical mutual induction calculations and would be worth investigating for application to ab initio molecular dynamics as well.

In a typical X-ray diffraction experiment, the elastically scattered intensity, I(Q), is the experimental observable. I(Q) contains contributions from both intramolecular as well as intermolecular correlations embodied in the scattering factors, HOO(Q) and HOH(Q), with negligible contributions from HHH(Q). Thus, to accurately define the oxygen-oxygen radial distribution function, gOO(r), a model of the electron density is required to accurately weigh the HOO(Q) component relative to the intramolecular and oxygen-hydrogen correlations from the total intensity observable. In this work, we carefully define the electron density model and its underlying assumptions and more explicitly utilize two restraints on the allowable gOO(r) functions, which must conform to both very low experimental errors at high Q and the need to satisfy the isothermal compressibility at low Q. Although highly restrained by these conditions, the underdetermined nature of the problem is such that we present a family of gOO(r) values that provide equally good agreement with the high-Q intensity and compressibility restraints and with physically correct behavior at small r.

A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient, and dielectric constant. The viscosity, self-diffusion constant, and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2-20 water molecules, the AMOEBA14 model yields results similar to AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model.

We present a molecular simulation study of star polymers consisting of 16 diblock copolymer arms bound to a small adamantane core by varying both arm length and the outer hydrophilic block when attached to the same hydrophobic block of poly-δ-valerolactone. Here we consider two biocompatible star polymers in which the hydrophilic block is composed of polyethylene glycol (PEG) or polymethyloxazoline (POXA) in addition to a polycarbonate-based polymer with a pendant hydrophilic group (PC1). We find that the different hydrophilic blocks of the star polymers show qualitatively different trends in their interactions with aqueous solvent, orientational time correlation functions, and orientational correlation between pairs of monomers of their polymeric arms in solution, in which we find that the PEG polymers are more thermosensitive compared with the POXA and PC1 star polymers over the physiological temperature range we have investigated.

Vasopressin and oxytocin are intrinsically disordered cyclic nonapeptides belonging to a family of neurohypophysial hormones. Although unique in their functions, these peptides differ only by two residues and both feature a tocin ring formed by the disulfide bridge between first and sixth cysteine residues. This sequence and structural similarity are experimentally linked to oxytocin agonism at vasopressin receptors and vasopressin antagonism at oxytocin receptors. Yet single- or double-residue mutations in both peptides have been shown to have drastic impacts on their activities at either receptor, and possibly the ability to bind to their neurophysin carrier protein. In this study we perform molecular dynamics simulations of the unbound native and mutant sequences of the oxytocin and vasopressin hormones to characterize their structural ensembles. We classify the subpopulations of these structural ensembles on the basis of the distributions of radius of gyration and secondary structure and hydrogen-bonding features of the canonical tocin ring and disordered tail region. We then relate the structural changes observed in the unbound form of the different hormone sequences to experimental information about peptide receptor binding, and more indirectly, carrier protein binding affinity, receptor activity, and protease degradation. This study supports the hypothesis that the structural characteristics of the unbound form of an IDP can be used to predict structural or functional preferences of its functional bound form.

Intrinsically disordered proteins (IDPs) represent a new frontier in structural biology since the primary characteristic of IDPs is that structures need to be characterized as diverse ensembles of conformational substates. We compare two general but very different ways of combining NMR spectroscopy with theoretical methods to derive structural ensembles for the disease IDPs amyloid-β 1-40 and amyloid-β 1-42, which are associated with Alzheimer's Disease. We analyze the performance of de novo molecular dynamics and knowledge-based approaches for generating structural ensembles by assessing their ability to reproduce a range of NMR experimental observables. In addition to the comparison of computational methods, we also evaluate the relative value of different types of NMR data for refining or validating the IDP structural ensembles for these important disease peptides.

Using a coarse-grained lipid and peptide model, we show that the free energy stabilization of amyloid-β in heterogeneous lipid membranes is predicted to have a dependence on asymmetric distributions of cholesterol compositions across the membrane leaflets. We find that a highly asymmetric cholesterol distribution that is depleted on the exofacial leaflet but enhanced on the cytofacial leaflet of the model lipid membrane thermodynamically favors membrane retention of a fully embedded Aβ peptide. However, in the case of cholesterol redistribution that increases concentration of cholesterol on the exofacial layer, typical of aging or Alzheimer's disease, the free energy favors peptide extrusion of the highly reactive N-terminus into the extracellular space that may be vulnerable to aggregation, oligomerization, or deleterious oxidative reactivity.

Using homonuclear (1)H NOESY spectra, with chemical shifts, (3)JH(N)H(α) scalar couplings, residual dipolar couplings, and (1)H-(15)N NOEs, we have optimized and validated the conformational ensembles of the amyloid-β 1-40 (Aβ40) and amyloid-β 1-42 (Aβ42) peptides generated by molecular dynamics simulations. We find that both peptides have a diverse set of secondary structure elements including turns, helices, and antiparallel and parallel β-strands. The most significant difference in the structural ensembles of the two peptides is the type of β-hairpins and β-strands they populate. We find that Aβ42 forms a major antiparallel β-hairpin involving the central hydrophobic cluster residues (16-21) with residues 29-36, compatible with known amyloid fibril forming regions, whereas Aβ40 forms an alternative but less populated antiparallel β-hairpin between the central hydrophobic cluster and residues 9-13, that sometimes forms a β-sheet by association with residues 35-37. Furthermore, we show that the two additional C-terminal residues of Aβ42, in particular Ile-41, directly control the differences in the β-strand content found between the Aβ40 and Aβ42 structural ensembles. Integrating the experimental and theoretical evidence accumulated over the last decade, it is now possible to present monomeric structural ensembles of Aβ40 and Aβ42 consistent with available information that produce a plausible molecular basis for why Aβ42 exhibits greater fibrillization rates than Aβ40.

The energy landscape is analyzed for off-lattice bead models of protein L and protein G as a function of a static pulling force. Two different pairs of attachment points (pulling directions) are compared in each case, namely, residues 1/56 and 10/32. For the terminal residue pulling direction 1/56, the distinct global minimum structures are all extended, aside from the compact geometry that correlates with zero force. The helical turns finally disappear at the highest pulling forces considered. For the 10/32 pulling direction, the changes are more complicated, with a variety of competing arrangements for beads outside the region where the force is directly applied. These alternatives produce frustrated energy landscapes, with low-lying minima separated by high barriers. The calculated folding pathways in the absence of force are in good agreement with previous work. The N-terminal hairpin folds first for protein L and the C-terminal hairpin for protein G, which exhibits an intermediate. However, for a relatively low static force, where the global minimum retains its structure, the folding mechanisms change, sometimes dramatically, depending on the protein and the attachment points. The scaling relations predicted by catastrophe theory are found to hold in the limit of short path lengths.

An accurate representation of solute-water interactions is necessary for molecular dynamics simulations of biomolecules that reside in aqueous environments. Modern force fields and advanced water models describe solute-solute and water-water interactions reasonably accurately but have known shortcomings in describing solute-water interactions, demonstrated by the large differences between calculated and experimental solvation free energies across a range of peptide and drug chemistries. In this work, we introduce a method for optimizing solute-water van der Waals interactions to reproduce experimental solvation free energy data and apply it to the optimization of a fixed charge force field (AMBER ff99SB/GAFF) and advanced water model (TIP4P-Ew). We show that, with these optimizations, the combination of AMBER ff99SB/GAFF and TIP4P-Ew is able to reproduce the solvation free energies of a variety of biologically relevant small molecules to within 1.0 k(B)T. We further validate these optimizations by examining the aggregation propensities of dipeptide-water solutions, the conformational preferences of short disordered peptides, and the native state stability and dynamics of a folded protein.