The bulk structure, the relative stability, and the electronic properties of monoclinic, tetragonal, and cubic ZrO_{2} have been studied from a theoretical point of view, through periodic *ab initio* calculations using different Gaussian basis sets together with Hartree–Fock (HF), pure Density Functional Theory (DFT), and mixed HF/DFT schemes as found in hybrid functionals. The role of a *posteriori* empirical correction for dispersion, according to the Grimme D2 scheme, has also been investigated. The obtained results show that, among the tested functionals, PBE0 not only provides the best structural description of the three polymorphs, but it also represents the best compromise to accurately describe both the geometric and electronic features of the oxide. The relative stability of the three phases can also be qualitatively reproduced, as long as thermal contributions to the energy are taken into account. Four low-index ZrO_{2} surfaces [monoclinic (−111), tetragonal (101 and 111), and cubic (111)] have then been studied at this latter level of theory. Surface energies, atomic relaxations, and electronic properties of these surfaces have been computed. The most stable surface is the cubic one, which is associated to small relaxations confined to the outermost layers. It is followed by the monoclinic (−111) and the tetragonal (101), which have very similar surface energies and atomic displacements. The tetragonal (111) was instead found to be, by far, the less stable with large displacements not only for the outermost but also for deeper layers. Through the comparison of different methods and basis sets, this study allowed us to find a reliable and accurate computational protocol for the investigation of zirconia, both in its bulk and surfaces forms, in view of more complex technological applications, such as ZrO_{2} doped with aliovalent oxides as found in solid oxide fuel cells. © 2014 Wiley Periodicals, Inc.

Zirconia is one of the most studied ceramic materials, because of the wide range of its technological applications, including Solid Oxide Fuel Cells (SOFCs). Indeed, yttria-stabilized zirconia is the most used electrolyte in high-temperature SOFC. Density functional theory (DFT) calculations are presented on the bulk structures of three ambient pressure polymorphs of zirconia. Calculations were carried out with different DFT models, from which a computational protocol is applied to selected low-index surfaces.

Aqueous p*K*_{A} values for 15 hexa-aqua transition metal complexes were computed using a combination of quantum chemical and electrostatic methods. Two different structure models were considered optimizing the isolated complexes in vacuum or in presence of explicit solvent using a QM/MM approach. They yield very good agreement with experimentally measured p*K*_{A} values with an overall root mean square deviation of about 1 pH unit, excluding a single but different outlier for each of the two structure models. These outliers are hexa-aqua Cr(III) for the vacuum and hexa-aqua Mn(III) for the QM/MM structure model. Reasons leading to the deviations of the outlier complexes are partially explained. Compared to previous approaches from the same lab the precision of the method was systematically improved as discussed in this study. The refined methods to obtain the appropriate geometries of the complexes, developed in this work, may allow also the computation of accurate p*K*_{A} values for multicore transition metal complexes in different oxidation states. © 2014 Wiley Periodicals, Inc.

Aqueous p*K*_{A} values for hexa-aqua complexes of first and second row transition metals were computed using a combination of quantum chemical and electrostatic methods. Computed p*K*_{A} values show very good agreement with measured p*K*_{A} values with a root mean square deviation of 1 pH unit. Compared to previous approaches from the same lab, the precision of the method was systematically improved.

In this work, we report a detailed theoretical investigation of the phase transition of ammonia borane (NH_{3}BH_{3}; AB), from a tetragonal *I*4*mm* (
) phase with disordered orientation of hydrogen to an orthorhombic phase with *Pmn*2_{1} (
) symmetry, as a function of temperature based on Density Functional Theory calculations with semiempirical dispersion potential correction. We define a series of substructures with the NH_{3}BH_{3} moiety always in *C*_{3}* _{v}* symmetry and the partially occupied high temperature state can be described as a continuous transformation between these substructures. To understand the role of the van de Waals corrections to the physical properties, we use the empirical Grimme's dispersion potential correction (PBE-D2). Both Perdew–Burke–Emzerhof (PBE) and PBE-D2 functional yield almost the same energy sequence along the transition path. However, PBE-D2 functional shows obvious advantage in describing the lattice parameters of AB. The rigid rotor harmonic oscillator approximation is used to compute the free energy and the entropies contribution along the transition pathway. With knowledge of free energy surfaces along rotations of the [NH

The phase transition of ammonia borane (NH_{3}BH_{3}), from a tetragonal *I*4*mm* (
) phase with disordered orientation of hydrogen to an orthorhombic phase with *Pmn*2_{1} (
) symmetry, is investigated as a function of temperature, based on density functional theory calculations with semi-empirical dispersion potential correction. A series of substructures are defined and the partially occupied high temperature state can be described as a continuous transformation between these substructures. The total energies with phonon spectrum of each substructure allow the minimal free energy structure at each temperature to be determined explicitly.

LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development. © 2014 Wiley Periodicals, Inc.

LOOS is a software library designed to facilitate making novel tools for analyzing molecular dynamics simulations using C++ or Python. LOOS supports reading the native file formats of most common biomolecular simulation packages. A dynamic atom selection language is included and is easily accessible to the tool-writer. LOOS is bundled with over 140 tools. Through modern C++ design, LOOS is both simple to develop with and is easily extensible

Olfactory receptors (ORs) represent the largest subfamily of the superfamily G protein-coupled receptors (GPCRs). This family of membrane receptors functions as essential gateway for activation of many cellular signaling pathways. Finding universal principles underlying GPCR activation by studying ORs is important for the design of new therapeutics that target olfaction-related and other GPCR-malfunctioning diseases. In addition, gaining knowledge regarding the interactions between ORs and their cognate ligands (odorants) may contribute to solve the puzzle of how odor perception is encoded in humans. As no crystal structure of an OR is available yet, homology modeling can be applied to generate a three-dimensional OR model. Molecular docking, molecular dynamics simulations and qualitative structure-activity-relationship can further guide experimental research by investigating interactions at the atomic level. This article will review these computational techniques as well as present databases and popular software suites, which can support researchers in the OR research field. © 2014 Wiley Periodicals, Inc.

G protein-coupled receptors (GPCRs) compose one of the largest protein membrane family in our body. These refined receptors have a critical function in many essential regulation pathways and thus are involved in several severe diseases. Therefore, many studies are focus to gain insight in their functioning. In this review, Olfactory receptors (ORs), the largest GPCR subfamily, are discussed with main focus on their structural characteristics and the computational techniques that can be used to broaden our current knowledge regarding both GPCRs-malfunctioning diseases and human odor perception.

The semiexperimental (SE) technique, whereby equilibrium rotational constants are derived from experimental ground-state rotational constants and corrections based on an *ab initio* cubic force field, has the reputation to be one of the most accurate methods to determine an equilibrium structure (
). However, in some cases, it cannot determine accurately the position of the hydrogen. To investigate the origins of this difficulty, the SE structures of several molecules containing either the OH or the CH_{3} group are determined and compared to their best *ab initio* counterparts. It appears that an important factor is the accuracy of the geometry used to calculate the force field, in particular when the least-squares system is not well conditioned. In this case, the mixed regression method is often an easy way to circumvent this difficulty. © 2014 Wiley Periodicals, Inc.

The semiexperimental (SE) technique has the reputation to be one of the most accurate methods to determine an equilibrium structure. However, in some cases, it cannot accurately determine the position of the hydrogen atoms in a methyl or hydroxyl group. To investigate the origins of this difficulty, the SE structures of several molecules containing either the OH or the CH3 group are determined and compared to their best *ab initio* counterparts.

A novel approach for the selection of step parameters as reaction coordinates in enhanced sampling simulations of DNA is presented. The method uses three atoms per base and does not require coordinate overlays or idealized base pairs. This allowed for a highly efficient implementation of the calculation of all step parameters and their Cartesian derivatives in molecular dynamics simulations. Good correlation between the calculated and actual twist, roll, tilt, shift, and slide parameters is obtained, while the correlation with rise is modest. The method is illustrated by its application to the methylated and unmethylated 5′-CATGTGACGTCACATG-3′ double stranded DNA sequence. One-dimensional umbrella simulations indicate that the flexibility of the central CG step is only marginally affected by methylation. © 2014 Wiley Periodicals, Inc.

A simplified method for the calculation of DNA step parameters and their Cartesian derivatives is introduced. Using three atoms per base and no structure overlays, the method is highly efficient for use in free energy simulations while retaining good accuracy. The method is illustrated by calculating the flexibility of the central CG step in methylated and unmethylated DNA strands.

We investigate the performance of several van der Waals (vdW) functionals at calculating the interactions between benzene and the copper (111) surface, using the local orbital approach in the SIESTA code. We demonstrate the importance of using surface optimized basis sets to calculate properties of pure surfaces, including surface energies and the work function. We quantify the errors created using (3 × 3) supercells to study adsorbate interactions using much larger supercells, and show non-negligible errors in the binding energies and separation distances. We examine the eight high-symmetry orientations of benzene on the Cu (111) surface, reporting the binding energies, separation distance, and change in work function. The optimized vdW-DF(optB88-vdW) functional provides superior results to the vdW-DF(revPBE) and vdW-DF2(rPW86) functionals, and closely matches the experimental and experimentally deduced values. This work demonstrates that local orbital methods using appropriate basis sets combined with a vdW functional can model adsorption between metal surfaces and organic molecules.

The performance of several van der Waals (vdW) functionals at calculating the interactions between benzene and the copper (111) surface was investigated. Local orbital methods using appropriate basis sets combined with a vdW functional can successfully model adsorption between metal surfaces and organic molecules.

The potential energy surfaces (PES) of a series of gold–boron clusters with formula Au* _{n}*B (

The potential energy surfaces of gold clusters doped with one and two boron atoms have been explored in detail using a stochastic search algorithm. DFT computations show that these gold-boron clusters have well-defined growth patterns.

An important task of biomolecular simulation is the calculation of relative binding free energies upon chemical modification of partner molecules in a biomolecular complex. The potential of mean force (PMF) along a reaction coordinate for association or dissociation of the complex can be used to estimate binding affinities. A free energy perturbation approach, termed umbrella sampling (US) perturbation, has been designed that allows an efficient calculation of the change of the PMF upon modification of a binding partner based on the trajectories obtained for the wild type reference complex. The approach was tested on the interaction of modified water molecules in aqueous solution and applied to *in silico* alanine scanning of a peptide-protein complex. For the water interaction test case, excellent agreement with an explicit PMF calculation for each modification was obtained as long as no long range electrostatic perturbations were considered. For the alanine scanning, the experimentally determined ranking and binding affinity changes upon alanine substitutions could be reproduced within 0.1–2.0 kcal/mol. In addition, good agreement with explicitly calculated PMFs was obtained mostly within the sampling uncertainty. The combined US and perturbation approach yields, under the condition of sufficiently small system modifications, rigorously derived changes in free energy and is applicable to any PMF calculation. © 2014 Wiley Periodicals, Inc.

The change of a potential of mean force upon the modification of a system can be estimated by an umbrella sampling perturbation method that does not require additional simulations. Application to computational alanine-scanning of a peptide-protein complex by means of relative separation PMFs resulted in accurate free energy estimates for a series of peptide modifications. The method yields rigorously derived free energy changes under the condition of sufficiently small perturbations.

The generalized Newton–Euler inverse mass operator (GNEIMO) method is an advanced method for internal coordinates molecular dynamics (ICMD). GNEIMO includes several theoretical and algorithmic advancements that address longstanding challenges with ICMD simulations. In this article, we describe the GneimoSim ICMD software package that implements the GNEIMO method. We believe that GneimoSim is the first software package to include advanced features such as the equipartition principle derived for internal coordinates, and a method for including the Fixman potential to eliminate systematic statistical biases introduced by the use of hard constraints. Moreover, by design, GneimoSim is extensible and can be easily interfaced with third party force field packages for ICMD simulations. Currently, GneimoSim includes interfaces to LAMMPS, OpenMM, and Rosetta force field calculation packages. The availability of a comprehensive Python interface to the underlying C++ classes and their methods provides a powerful and versatile mechanism for users to develop simulation scripts to configure the simulation and control the simulation flow. GneimoSim has been used extensively for studying the dynamics of protein structures, refinement of protein homology models, and for simulating large scale protein conformational changes with enhanced sampling methods. GneimoSim is not limited to proteins and can also be used for the simulation of polymeric materials.

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The generalized Newton–Euler inverse mass operator (GNEIMO) method is an advanced method for internal coordinates molecular dynamics (ICMD). GNEIMO includes several theoretical and algorithmic advancements that address longstanding challenges with ICMD simulations. In this article, we describe the GneimoSim ICMD software package that implements the GNEIMO method. We believe that GneimoSim is the first software package to include advanced features such as the equipartition principle derived for internal coordinates, and a method for including the Fixman potential to eliminate systematic statistical biases introduced by the use of hard constraints. Moreover, by design, GneimoSim is extensible and can be easily interfaced with third party force field packages for ICMD simulations. Currently, GneimoSim includes interfaces to LAMMPS, OpenMM, and Rosetta force field calculation packages. The availability of a comprehensive Python interface to the underlying C++ classes and their methods provides a powerful and versatile mechanism for users to develop simulation scripts to configure the simulation and control the simulation flow. GneimoSim has been used extensively for studying the dynamics of protein structures, refinement of protein homology models, and for simulating large scale protein conformational changes with enhanced sampling methods. GneimoSim is not limited to proteins and can also be used for the simulation of polymeric materials.
Impact of Mn on the solution enthalpy of hydrogen in austenitic Fe-Mn alloys: A first-principles study http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1002%2Fjcc.23742Impact of Mn on the solution enthalpy of hydrogen in austenitic Fe-Mn alloys: A first-principles study Jörg Appen, Richard Dronskowski, Aurab Chakrabarty, Tilmann Hickel, Robert Spatschek, Jörg Neugebauer 2014-09-24T07:43:13.048179-05:00 doi:10.1002/jcc.23742 John Wiley & Sons, Inc. 10.1002/jcc.23742 http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1002%2Fjcc.23742 Full Paper n/a n/a

Hydrogen interstitials in austenitic Fe-Mn alloys were studied using density-functional theory to gain insights into the mechanisms of hydrogen embrittlement in high-strength Mn steels. The investigations reveal that H atoms at octahedral interstitial sites prefer a local environment containing Mn atoms rather than Fe atoms. This phenomenon is closely examined combining total energy calculations and crystal orbital Hamilton population analysis. Contributions from various electronic phenomena such as elastic, chemical, and magnetic effects are characterized. The primary reason for the environmental preference is a volumetric effect, which causes a linear dependence on the number of nearest-neighbour Mn atoms. A secondary electronic/magnetic effect explains the deviations from this linearity. © 2014 Wiley Periodicals, Inc.

Adding a substantial amount of manganese to steels yields a material with extraordinary mechanical properties. A tiny amount of hydrogen in high-Mn steels, however, is already suffcient for the onset of devastating embrittlement effects. Using first-principles methods, an attraction of both elements is revealed, providing a complete analysis of the elastic, chemical, and magnetic origin of this phenomenon. These insights contribute to strategies to better control the hydrogen distribution in steels.

The thermal stabilities and melting behavior of icosahedral nickel clusters under hydrostatic pressure have been studied by constant-pressure molecular dynamics simulation. The potential energy and Lindemann index are calculated. The overall melting temperature exhibits a strong dependence on pressure. The Lindemann index of solid structure before melting varies slowly and is almost independent of pressure. However, after the clusters melt completely, the Lindemann index at the overall melting point strongly depends on pressure. The overall melting temperature is found to be increasing nonlinearly with increasing pressure, while the volume change during melting decreases linearly with increasing pressure. Under a high pressure and temperature environment, similar angular distributions were found between liquid and solid structures, indicating the existence of a converging local structure. © 2014 Wiley Periodicals, Inc.

Since nickel–iron mixture is one kind of dominant components in terrestrial planet lower mantle, melting of nickel under hydrostatic pressure is always an interesting topic. In this work, the melting behaviors of icosahedral nickel clusters under hydrostatic pressure have been studied by constant-pressure molecular dynamic simulation. This work is intended to provide a better understanding for the thermal properties of nickel cluster and will help to develop new nanomaterials under hydrostatic pressure.

On page 2225 (DOI: 10.1002/jcc.23741), Berco Dan and Chin-Kun Hu perform an analysis of the localized surface plasmon of a gold nano shell using the discrete dipole approximation. A two dimensional projection of the near field intensity is then used at the surface to perform a spectral analysis of the localized surface plasmon by a discrete spherical harmonic transform. The spherical intensity pattern is wrapped on a sphere for illustrative purposes.

A structure-based function-prediction technique SPOT for carbohydrate-binding proteins is reported on page 2177 (DOI: 10.1002/jcc.23730) by Huiying Zhao, Yuedong Yang, Mark von Itzstein, and Yaoqi Zhou. The method first predicts a complex structure between a target protein and a template carbohydrate based on a structural alignment program SPalign and subsequently validates the binding by using a knowledge-based potential with a DFIRE reference state. The leave-one-out cross-validation confirms that the method has high precision and reasonable sensitivity in predicting binding function and binding residues.

The efficiency and accuracy of the perturbation-selection used in the symmetry-adapted cluster-configuration interaction (SAC-CI) calculations are investigated for several low-lying valence excited states of 21 medium-size molecules, including typical chromophores with heterocyclic macrocycles (free-base porphine, coumarin, indole, and BODIPY), nucleobases, amino acids (tyrosine and tryptophan), polycyclic aromatic hydrocarbons, and organometallics (ferrocene and Re(bpy) ). Benchmark SAC-CI calculations with up to 110 million operators are performed. The efficiency of the perturbation-selection depends on the molecular orbitals (MOs); therefore, the canonical MO and localized MO (LMO) obtained by Pipek-Mezey's method are examined. Except for the highly symmetric molecules, using LMOs improves the efficiency and accuracy of the perturbation-selection. With using LMOs and perturbation-selection, sufficiently reliable results can be obtained in less than 10% of the computational costs required for the full-dimensional calculations. The perturbation-selection with LMOs is suggested to be a promising method for excited states in larger molecular systems. Copyright © 2014 Wiley Periodicals, Inc.

The efficiency and accuracy of the perturbation-selection for the SAC-CI calculations are investigated for excited states of 21 medium-size molecules. Benchmark SAC-CI calculations with up to 110 million operators are performed. The efficiency of the selection using the canonical and localized MO (LMO) is also examined. Except for highly symmetric molecules, using LMOs improves the efficiency and accuracy. The perturbation-selection with LMOs is a promising method for excited states in larger molecules.

Carbohydrate-binding proteins (CBPs) are potential biomarkers and drug targets. However, the interactions between carbohydrates and proteins are challenging to study experimentally and computationally because of their low binding affinity, high flexibility, and the lack of a linear sequence in carbohydrates as exists in RNA, DNA, and proteins. Here, we describe a structure-based function-prediction technique called SPOT-Struc that identifies carbohydrate-recognizing proteins and their binding amino acid residues by structural alignment program SPalign and binding affinity scoring according to a knowledge-based statistical potential based on the distance-scaled finite-ideal gas reference state (DFIRE). The leave-one-out cross-validation of the method on 113 carbohydrate-binding domains and 3442 noncarbohydrate binding proteins yields a Matthews correlation coefficient of 0.56 for SPalign alone and 0.63 for SPOT-Struc (SPalign + binding affinity scoring) for CBP prediction. SPOT-Struc is a technique with high positive predictive value (79% correct predictions in all positive CBP predictions) with a reasonable sensitivity (52% positive predictions in all CBPs). The sensitivity of the method was changed slightly when applied to 31 APO (unbound) structures found in the protein databank (14/31 for APO versus 15/31 for HOLO). The result of SPOT-Struc will not change significantly if highly homologous templates were used. SPOT-Struc predicted 19 out of 2076 structural genome targets as CBPs. In particular, one uncharacterized protein in *Bacillus subtilis* (1oq1A) was matched to galectin-9 from *Mus musculus*. Thus, SPOT-Struc is useful for uncovering novel carbohydrate-binding proteins. SPOT-Struc is available at http://sparks-lab.org. © 2014 Wiley Periodicals, Inc.

Discovering new carbohydrate-binding proteins (CBPs) is important as they are potential biomarkers and drug targets. A template-based technique is developed to predict CBPs by structural alignment and binding affinity scoring. Its application to structural genome targets yields several novel CBPs.

Although recent years have seen much progress in the elucidation of the mechanisms underlying the bioluminescence of fireflies, there is to date no consensus on the precise contributions to the light emission from the different possible forms of the chemiexcited oxyluciferin (OxyLH_{2}) cofactor. Here, this problem is investigated by the calculation of excited-state equilibrium constants in aqueous solution for keto–enol and acid–base reactions connecting six neutral, monoanionic and dianionic forms of OxyLH_{2}. Particularly, rather than relying on the standard Förster equation and the associated assumption that entropic effects are negligible, these equilibrium constants are for the first time calculated in terms of excited-state free energies of a Born–Haber cycle. Performing quantum chemical calculations with density functional theory methods and using a hybrid cluster-continuum approach to describe solvent effects, a suitable protocol for the modeling is first defined from benchmark calculations on phenol. Applying this protocol to the various OxyLH_{2} species and verifying that available experimental data (absorption shifts and ground-state equilibrium constants) are accurately reproduced, it is then found that the phenolate-keto-OxyLH^{–} monoanion is intrinsically the preferred form of OxyLH_{2} in the excited state, which suggests a potential key role for this species in the bioluminescence of fireflies. © 2014 Wiley Periodicals, Inc.

Aqueous keto–enol and acid–base excited-state equilibrium constants between six neutral, monoanionic, and dianionic forms of oxyluciferin—the cofactor responsible for the bioluminescence of firefly luciferase—are for the first time calculated from free energies of a Born–Haber cycle rather than using the Förster equation. It is found that the phenolate-keto-OxyLH^{–} monoanion is the preferred excited-state form of oxyluciferin in aqueous solution, attributing a potential key role to this species in the bioluminescence of fireflies.

B3LYP calculations were carried out on hydrolysis reactions of monosubstituted(R) phosphate dianion and sulfate monoanion. In the reacting system, water clusters (H_{2}O)_{22} and (H_{2}O)_{35} are included to trace reaction paths. For both P and S substrates with R = methyl group, elementary processes were calculated. While the phosphate undergoes the substitution at the phosphorus, the sulfate does at the methyl carbon. For the S substrate with R = neopentyl group, the product tert-amyl alcohol was found to be formed via a dyotropic rearrangement from the neopentyl alcohol intermediate. For R = aryl groups, transition-state geometries were calculated to be similar between P and S substrates. Calculated activation energies are in good agreement with experimental values. After the rate-determining transition state of the substitution, the hydronium ion H_{3}O^{+} is formed at the third water molecule. It was suggested that alkyl and aryl substrates are of the different reactivity of the hydrolysis. © 2014 Wiley Periodicals, Inc.

DFT calculations were carried out on hydrolysis reactions of monosubstituted (R) phosphate dianion and sulfate monoanion with water clusters (H_{2}O)_{22} and (H_{2}O)_{33}. For P and S substrates with R = methyl different substitution paths were obtained. In contrast, for R = aryl transition-state geometries are similar, and activation energies are in good agreement with experimental values. Kinetic isotope effects were examined for R = 4-nitrophenyl.

Recent developments in fragment-based methods make it increasingly feasible to use high-level *ab initio* electronic structure techniques to molecular crystals. Such studies remain computationally demanding, however. Here, we describe a straightforward algorithm for exploiting space-group symmetry in fragment-based methods which often provides computational speed-ups of several fold or more. This algorithm does not require *a priori* specification of the space group or symmetry operators. Rather, the symmetrically equivalent fragments are identified automatically by aligning the individual fragments along their principle axes of inertia and testing for equivalence with other fragments. The symmetry operators relating equivalent fragments can then be worked out easily. Implementation of this algorithm for computing energies, nuclear gradients with respect to both atomic coordinates and lattice parameters, and the nuclear hessian is described. © 2014 Wiley Periodicals, Inc.

A simple algorithm for exploiting space group symmetry in fragment-based molecular crystal calculations that does not require *a priori* knowledge or implementation of the space group tables is described. It relies on rotating each monomer or dimer fragment to a common frame of reference for straightforward identification of symmetrically equivalent fragments. Exploiting space group symmetry often provides significant computational savings in accurate molecular crystal modeling.

We present a Bayesian inference approach to estimating conformational state populations from a combination of molecular modeling and sparse experimental data. Unlike alternative approaches, our method is designed for use with small molecules and emphasizes high-resolution structural models, using inferential structure determination with reference potentials, and Markov Chain Monte Carlo to sample the posterior distribution of conformational states. As an application of the method, we determine solution-state conformational populations of the 14-membered macrocycle cineromycin B, using a combination of previously published sparse Nuclear Magnetic Resonance (NMR) observables and replica-exchange molecular dynamic/Quantum Mechanical (QM)-refined conformational ensembles. Our results agree better with experimental data compared to previous modeling efforts. Bayes factors are calculated to quantify the consistency of computational modeling with experiment, and the relative importance of reference potentials and other model parameters. © 2014 Wiley Periodicals, Inc.

A Bayesian inference approach to estimating conformational state populations is presented from a combination of molecular modeling and sparse experimental data. The method is designed for use with small molecules and emphasizes high-resolution structural models, using inferential structure determination with reference potentials, and MCMC to sample the posterior distribution of conformational states. Results agree better with experimental data compared to previous modeling efforts. Bayes factors are calculated to quantify the consistency of computational modeling with experiment, and the relative importance of reference potentials and other model parameters.

We perform a study of the localized surface plasmon (LSP) modes of a gold nano shell having a silica core by means of discrete dipole approximation (DDA) and spherical harmonics transform for selected wavelengths. We demonstrate an efficient solution for the near and intermediate field terms by the dyadic Green function approach and determine the optical extinction efficiency by the far field term. Using this approach, we combine the advantages of a spectral analysis along with a DDA flexibility to solve an arbitrary shaped model and demonstrate the LSP dominant mode wavelength dependency. Our approach provides a metric which may be used to quantify the effects of minor changes in the model structure, or the external dielectric environment, in optical experiments. © 2014 Wiley Periodicals, Inc.

The localized surface plasmon (LSP) modes of a gold nano shell (AuNS) having a silica core by means of discrete dipole approximation (DDA) and spherical harmonics transform for selected wavelengths is studied. An efficient solution is demonstrated for the near and intermediate field terms by the dyadic green function approach and determine the optical extinction efficiency by the far field term. The advantages of a spectral analysis are combined with DDA flexibility to solve an arbitrary-shaped model and demonstrate the LSP dominant mode wavelength dependency.