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1.  Validation of experimental molecular crystal structures with dispersion-corrected density functional theory calculations 
The accuracy of a dispersion-corrected density functional theory method is validated against 241 experimental organic crystal structures from Acta Cryst. Section E.
This paper describes the validation of a dispersion-corrected density functional theory (d-DFT) method for the purpose of assessing the correctness of experimental organic crystal structures and enhancing the information content of purely experimental data. 241 experimental organic crystal structures from the August 2008 issue of Acta Cryst. Section E were energy-minimized in full, including unit-cell parameters. The differences between the experimental and the minimized crystal structures were subjected to statistical analysis. The r.m.s. Cartesian displacement excluding H atoms upon energy minimization with flexible unit-cell parameters is selected as a pertinent indicator of the correctness of a crystal structure. All 241 experimental crystal structures are reproduced very well: the average r.m.s. Cartesian displacement for the 241 crystal structures, including 16 disordered structures, is only 0.095 Å (0.084 Å for the 225 ordered structures). R.m.s. Cartesian displacements above 0.25 Å either indicate incorrect experimental crystal structures or reveal interesting structural features such as exceptionally large temperature effects, incorrectly modelled disorder or symmetry breaking H atoms. After validation, the method is applied to nine examples that are known to be ambiguous or subtly incorrect.
doi:10.1107/S0108768110031873
PMCID: PMC2940256  PMID: 20841921
dispersion-corrected density functional theory; organic structures
2.  STEM Electron Diffraction and High Resolution Images Used in the Determination of the Crystal Structure of Au144(SR)60 Cluster 
Determination of the total structure of molecular nanocrystals is an outstanding experimental challenge that has been met, in only a few cases, by single-crystal X-ray diffraction. Described here is an alternative approach that is of most general applicability and does not require the fabrication of a single crystal. The method is based on rapid, time-resolved nanobeam electron diffraction (NBD) combined with high-angle annular dark field scanning/transmission electron microscopy (HAADF-STEM) images in a probe corrected STEM microscope, operated at reduced voltages. The results are compared with theoretical simulations of images and diffraction patterns obtained from atomistic structural models derived through first-principles density functional theory (DFT) calculations. The method is demonstrated by application to determination of the structure of the Au144(SCH2CH2Ph)60 cluster.
doi:10.1021/jz400111d
PMCID: PMC3655783  PMID: 23687562
aberration-corrected microscopy; metal nanoparticles; low voltages; first-principles density functional theory; structure determination
3.  Stereochemistry of Complex Marine Natural Products by Quantum Mechanical Calculations of NMR Chemical Shifts: Solvent and Conformational Effects on Okadaic Acid 
Marine Drugs  2014;12(1):176-192.
Marine organisms are an increasingly important source of novel metabolites, some of which have already inspired or become new drugs. In addition, many of these molecules show a high degree of novelty from a structural and/or pharmacological point of view. Structure determination is generally achieved by the use of a variety of spectroscopic methods, among which NMR (nuclear magnetic resonance) plays a major role and determination of the stereochemical relationships within every new molecule is generally the most challenging part in structural determination. In this communication, we have chosen okadaic acid as a model compound to perform a computational chemistry study to predict 1H and 13C NMR chemical shifts. The effect of two different solvents and conformation on the ability of DFT (density functional theory) calculations to predict the correct stereoisomer has been studied.
doi:10.3390/md12010176
PMCID: PMC3917268  PMID: 24402177
quantum mechanical calculations; nuclear magnetic resonance; chemical shifts; marine toxin; structure determination; stereochemistry
4.  Effects of Vacancy Cluster Defects on Electrical and Thermodynamic Properties of Silicon Crystals 
The Scientific World Journal  2014;2014:863404.
A first-principle plane-wave pseudopotential method based on the density function theory (DFT) was employed to investigate the effects of vacancy cluster (VC) defects on the band structure and thermoelectric properties of silicon (Si) crystals. Simulation results showed that various VC defects changed the energy band and localized electron density distribution of Si crystals and caused the band gap to decrease with increasing VC size. The results can be ascribed to the formation of a defect level produced by the dangling bonds, floating bonds, or high-strain atoms surrounding the VC defects. The appearance of imaginary frequencies in the phonon spectrum of defective Si crystals indicates that the defect-region structure is dynamically unstable and demonstrates phase changes. The phonon dispersion relation and phonon density of state were also investigated using density functional perturbation theory. The obtained Debye temperature (θD) for a perfect Si crystal had a minimum value of 448 K at T = 42 K and a maximum value of 671 K at the high-temperature limit, which is consistent with the experimental results reported by Flubacher. Moreover, the Debye temperature decreased with increases in the VC size. VC defects had minimal effects on the heat capacity (Cv) value when temperatures were below 150 K. As the temperature was higher than 150 K, the heat capacity gradually increased with increasing temperature until it achieved a constant value of 11.8 cal/cell·K. The heat capacity significantly decreased as the VC size increased. For a 2 × 2 × 2 superlattice Si crystal containing a hexagonal ring VC (HRVC10), the heat capacity decreased by approximately 17%.
doi:10.1155/2014/863404
PMCID: PMC3913515  PMID: 24526923
5.  Tunable Doping in Graphene by Light-Switchable Molecules 
Noncovalent functionalization provides an effective way to modulate the electronic properties of graphene. Recent experimental work has demonstrated that hybrids of dipolar phototransductive molecules tethered to graphene are reversibly tunable in doping. We have studied the electronic structure characteristics of chromophore/graphene hybrids using dispersion-corrected density functional theory. The Dirac point of noncovalently functionalized graphene shifts upward via cis–trans isomerism, which is attributed to a change in the chromophore’s dipole moment. Our calculation results reveal that the experimentally observed reversible doping of graphene is attributed to the change in charge transfer between the light-switchable chromophore and graphene via isomerization. Furthermore, we show that by varying the electric field perpendicular to the supramolecular functionalized graphene, additional tailoring of graphene doping can be accomplished.
doi:10.1021/jp311269c
PMCID: PMC3539810  PMID: 23316261
6.  B-DNA Structure and Stability as Function of Nucleic Acid Composition: Dispersion-Corrected DFT Study of Dinucleoside Monophosphate Single and Double Strands 
ChemistryOpen  2013;2(5-6):186-193.
We have computationally investigated the structure and stability of all 16 combinations of two out of the four natural DNA bases A, T, G and C in a di-2′-deoxyribonucleoside-monophosphate model DNA strand as well as in 10 double-strand model complexes thereof, using dispersion-corrected density functional theory (DFT-D). Optimized geometries with B-DNA conformation were obtained through the inclusion of implicit water solvent and, in the DNA models, of sodium counterions, to neutralize the negative charge of the phosphate groups. The results obtained allowed us to compare the relative stability of isomeric single and double strands. Moreover, the energy of the Watson–Crick pairing of complementary single strands to form double-helical structures was calculated. The latter furnished the following increasing stability trend of the double-helix formation energy: d(TpA)2
doi:10.1002/open.201300019
PMCID: PMC3892189  PMID: 24551565
density functional calculations; DNA structures; hydrogen bonds; stacking interactions; Watson–Crick base pairs
Scientific Reports  2013;3:2995.
NiS, exhibiting a text-book example of a first-order transition with many unusual properties at low temperatures, has been variously described in terms of conflicting descriptions of its ground state during the past several decades. We calculate these physical properties within first-principle approaches based on the density functional theory and conclusively establish that all experimental data can be understood in terms of a rather unusual ground state of NiS that is best described as a self-doped, nearly compensated, antiferromagnetic metal, resolving the age-old controversy. We trace the origin of this novel ground state to the specific details of the crystal structure, band dispersions and a sizable Coulomb interaction strength that is still sub-critical to drive the system in to an insulating state. We also show how the specific antiferromagnetic structure is a consequence of the less-discussed 90° and less than 90° superexchange interactions built in to such crystal structures.
doi:10.1038/srep02995
PMCID: PMC3801131  PMID: 24141233
PLoS ONE  2014;9(3):e91361.
A series of novel 1,4-dihydro-2,6- dimethyl-3,5-pyridinedicarboxamides were synthesized and characterized by infrared absorption spectrum (IR), proton nuclear magnetic resonance (1H NMR), elemental analysis, ultraviolet spectrum (UV), and fluorescence techniques, together with X-ray single crystal diffraction. The results of density functional theory (DFT) and time-dependent density functional theory (TDDFT) calculations provided a reasonable explanation on the molecular structures, the molecular frontier orbital, and the spectra of electronic absorption and emission. The present work will be helpful to systematically understanding of the structures and the optical properties of 1,4-dihydropyridines for studying the structure-activity relationship and to develop new drugs and their analytical methods.
doi:10.1371/journal.pone.0091361
PMCID: PMC3953339  PMID: 24625887
Background
The rapid access to intrinsic physicochemical properties of molecules is highly desired for large scale chemical data mining explorations such as mass spectrum prediction in metabolomics, toxicity risk assessment and drug discovery. Large volumes of data are being produced by quantum chemistry calculations, which provide increasing accurate estimations of several properties, e.g. by Density Functional Theory (DFT), but are still too computationally expensive for those large scale uses. This work explores the possibility of using large amounts of data generated by DFT methods for thousands of molecular structures, extracting relevant molecular properties and applying machine learning (ML) algorithms to learn from the data. Once trained, these ML models can be applied to new structures to produce ultra-fast predictions. An approach is presented for homolytic bond dissociation energy (BDE).
Results
Machine learning models were trained with a data set of >12,000 BDEs calculated by B3LYP/6-311++G(d,p)//DFTB. Descriptors were designed to encode atom types and connectivity in the 2D topological environment of the bonds. The best model, an Associative Neural Network (ASNN) based on 85 bond descriptors, was able to predict the BDE of 887 bonds in an independent test set (covering a range of 17.67–202.30 kcal/mol) with RMSD of 5.29 kcal/mol, mean absolute deviation of 3.35 kcal/mol, and R2 = 0.953. The predictions were compared with semi-empirical PM6 calculations, and were found to be superior for all types of bonds in the data set, except for O-H, N-H, and N-N bonds. The B3LYP/6-311++G(d,p)//DFTB calculations can approach the higher-level calculations B3LYP/6-311++G(3df,2p)//B3LYP/6-31G(d,p) with an RMSD of 3.04 kcal/mol, which is less than the RMSD of ASNN (against both DFT methods). An experimental web service for on-line prediction of BDEs is available at http://joao.airesdesousa.com/bde.
Conclusion
Knowledge could be automatically extracted by machine learning techniques from a data set of calculated BDEs, providing ultra-fast access to accurate estimations of DFT-calculated BDEs. This demonstrates how to extract value from large volumes of data currently being produced by quantum chemistry calculations at an increasing speed mostly without human intervention. In this way, high-level theoretical quantum calculations can be used in large-scale applications that otherwise would not afford the intrinsic computational cost.
doi:10.1186/1758-2946-5-34
PMCID: PMC3720218  PMID: 23849655
BDE; Bond dissociation energy; Neural network; Random forest; Machine learning; Chemoinformatics; DFT; DFTB; Big data
Ecology and Evolution  2012;2(3):525-537.
Although the dispersal of animals is influenced by a variety of factors, few studies have used a condition-dependent approach to assess it. The mechanisms underlying dispersal are thus poorly known in many species, especially in large mammals. We used 10 microsatellite loci to examine population density effects on sex-specific dispersal behavior in the American black bear, Ursus americanus. We tested whether dispersal increases with population density in both sexes. Fine-scale genetic structure was investigated in each of four sampling areas using Mantel tests and spatial autocorrelation analyses. Our results revealed male-biased dispersal pattern in low-density areas. As population density increased, females appeared to exhibit philopatry at smaller scales. Fine-scale genetic structure for males at higher densities may indicate reduced dispersal distances and delayed dispersal by subadults.
doi:10.1002/ece3.207
PMCID: PMC3399142  PMID: 22822432
Black bear; dispersal; inbreeding avoidance; philopatry; population density; Ursus americanus
PLoS Computational Biology  2014;10(1):e1003400.
Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor of vacuolar-type ATPase, from the myxobacterium Archangium gephyra as an example. Our model estimates energies of new conformations by exploiting information from previous calculations via Gaussian process regression. Predictive variance is used to assess whether a conformation is in the interpolation region, allowing a controlled trade-off between prediction accuracy and computational speed-up. For energies of relaxed conformations at the density functional level of theory (implicit solvent, DFT/BLYP-disp3/def2-TZVP), mean absolute errors of less than 1 kcal/mol were achieved. The study demonstrates that predictive machine learning models can be developed for structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of larger molecular structures.
Author Summary
Molecular dynamics simulations provide insight into the dynamic behavior of molecules, e.g., into the adopted spatial arrangements of its atoms over time. Methods differ in the approximations they employ, resulting in a trade-off between accuracy and speed that ranges from highly accurate but expensive quantum mechanical calculations to fast but more inaccurate molecular mechanics force fields. Machine learning, a sub-discipline of artificial intelligence, provides algorithms that learn from data, that is, make predictions based on previously seen examples. By starting with a few expensive quantum mechanical calculations, training a machine learning algorithm on them, and then using the resulting model to carry out the molecular dynamics simulation, one can improve the accuracy/speed trade-off. We have developed and applied such a hybrid quantum mechanics/machine learning approach to Archazolid A, a natural product from the myxobacterium Archangium gephyra and a potent inhibitor of vacuolar-type ATPase. By dynamically refining our model over the course of the simulation, we achieve errors of less than 1 kcal/mol while saving over 40% of the quantum mechanical calculations. Our study demonstrates the feasibility of predictive machine learning models for the dynamics of structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of even larger biomolecular structures.
doi:10.1371/journal.pcbi.1003400
PMCID: PMC3894151  PMID: 24453952
Background
Goethite is a common and reactive mineral in the environment. The transport of contaminants and anaerobic respiration of microbes are significantly affected by adsorption and reduction reactions involving goethite. An understanding of the mineral-water interface of goethite is critical for determining the molecular-scale mechanisms of adsorption and reduction reactions. In this study, periodic density functional theory (DFT) calculations were performed on the mineral goethite and its (010) surface, using the Vienna Ab Initio Simulation Package (VASP).
Results
Calculations of the bulk mineral structure accurately reproduced the observed crystal structure and vibrational frequencies, suggesting that this computational methodology was suitable for modeling the goethite-water interface. Energy-minimized structures of bare, hydrated (one H2O layer) and solvated (three H2O layers) (010) surfaces were calculated for 1 × 1 and 3 × 3 unit cell slabs. A good correlation between the calculated and observed vibrational frequencies was found for the 1 × 1 solvated surface. However, differences between the 1 × 1 and 3 × 3 slab calculations indicated that larger models may be necessary to simulate the relaxation of water at the interface. Comparison of two hydrated surfaces with molecularly and dissociatively adsorbed H2O showed a significantly lower potential energy for the former.
Conclusion
Surface Fe-O and (Fe)O-H bond lengths are reported that may be useful in surface complexation models (SCM) of the goethite (010) surface. These bond lengths were found to change significantly as a function of solvation (i.e., addition of two extra H2O layers above the surface), indicating that this parameter should be carefully considered in future SCM studies of metal oxide-water interfaces.
doi:10.1186/1467-4866-9-4
PMCID: PMC2409307  PMID: 18477389
The major objective of this paper is to address a controversial binding sequence between nucleic acid bases (NABs) and C60 by investigating adsorptions of NABs and their cations on C60 fullerene with a variety of density functional theories including two novel hybrid meta-GGA functionals, M05-2x and M06-2x, as well as a dispersion-corrected density functional, PBE-D. The M05-2x/6-311++G** provides the same binding sequence as previously reported, guanine(G) > cytosine(C) > adenine (A) > thymine (T); however, M06-2x switches the binding strengths of A and C, and PBE-D eventually results in the following sequence, G>A>T>C, which is the same as the widely accepted hierarchy for the stacking of NABs on other carbon nanomaterials such as single-walled carbon nanotube and graphite. The results indicate that the questionable relative binding strength is due to insufficient electron correlation treatment with the M05-2x or even the M06-2x method. The binding energy of G@C60 obtained with the M06-2x/6-311++G(d,p) and the PBE-D/cc-pVDZ is −7.10 and −8.07 kcal/mol, respectively, and the latter is only slightly weaker than that predicted by the MP2/6-31G(d,p) (−8.10kca/mol). Thus, the PDE-D performs better than the M06-2x for the observed NAB@C60 π-stacked complexes. To discuss whether C60 could prevent NABs from radiation-induced damage, ionization potentials of NABs and C60, and frontier molecular orbitals of the complexes NABs@C60 and (NABs@C60)+ are also extensively investigated. These results revealed that when an electron escapes from the complexes, a hole was preferentially created in C60 for T and C complexes, while for G and A the hole delocalizes over the entire complex, rather than a localization on the C60 moiety. The interesting finding might open a new strategy for protecting DNA from radiation-induced damage and offer a new idea for designing C60-based antiradiation drugs.
doi:10.1021/jp108812z
PMCID: PMC3101642  PMID: 21625361
radiation-induced damage; NAB; C60; dispersion-corrected DFT; binding sequence
In this work, we studied a copper complex-based dye, which is proposed for potential photovoltaic applications and is named Cu (I) biquinoline dye. Results of electron affinities and ionization potentials have been used for the correlation between different levels of calculation used in this study, which are based on The Density Functional Theory (DFT) and time-dependent (TD) DFT. Further, the maximum absorption wavelengths of our theoretical calculations were compared with the experimental data. It was found that the M06/LANL2DZ + DZVP level of calculation provides the best approximation. This level of calculation was used to find the optimized molecular structure and to predict the main molecular vibrations, the molecular orbitals energies, dipole moment, isotropic polarizability and the chemical reactivity parameters that arise from Conceptual DFT.
doi:10.3390/ijms131216005
PMCID: PMC3546675  PMID: 23443107
molecular structure; absorption spectra; polarizability; chemical reactivity; dipole moment; copper complex; dye-sensitized
The journal of physical chemistry. B  2006;110(26):13277-13282.
The normal mode spectrum for the four-coordinated heme compound Fe(II) octaethylporphyrin, Fe(OEP), has been determined by refining force constants to the experimental Fe vibrational density of states measured with nuclear resonance vibrational spectroscopy (NRVS). Convergence of the calculated spectrum to the data was achieved by first imposing D4 symmetry on the model structure as well as the force constants, progressively including different internal coordinates of motion, then allowing the true Ci (or S2) point group symmetry of the Ci1 Fe(OEP) crystal structure. The NRVS-refined normal modes are in good agreement with Raman and IR spectra at high frequencies. Prior density functional theory predictions for a model porphyrin are similar to the core modes computed with the best-fit force field, but significant differences between D4 and Ci modes underline the sensitivity of porphyrin Fe normal modes to structural details. Some differences between the Ci best fit and the NRVS data can be attributed to intermolecular contacts not included in the normal mode analysis.
doi:10.1021/jp060345p
PMCID: PMC1525052  PMID: 16805642
Journal of Applied Crystallography  2010;43(Pt 6):1426-1430.
Based on the minimum shear criterion, a direct and simple method is proposed to calculate twinning elements from the experimentally determined twinning plane for Type I twins or the twinning direction for Type II twins. It is generic and applicable to any crystal structure.
The fundamental theory of crystal twinning has been long established, leading to a significant advance in understanding the nature of this physical phenomenon. However, there remains a substantial gap between the elaborate theory and the practical determination of twinning elements. This paper proposes a direct and simple method – valid for any crystal structure and based on the minimum shear criterion – to calculate various twinning elements from the experimentally determined twinning plane for Type I twins or the twinning direction for Type II twins. Without additional efforts, it is generally applicable to identify and predict possible twinning modes occurring in a variety of crystalline solids. Therefore, the present method is a promising tool to characterize twinning elements, especially for those materials with complex crystal structure.
doi:10.1107/S0021889810037180
PMCID: PMC3253729  PMID: 22477779
twinning; minimum shear; interface structure; transmission electron microscopy; scanning electron microscopy/electron backscatter diffraction
The title compound, C13H10BrNO2, exists as an enol–imine form in the crystal and adopts an E configuration with respect to the C=N double bond. The mol­ecule is close to planar, with a dihedral angle of 6.88 (14)° between the aromatic rings. Intra­molecular O—H⋯N and O—H⋯O hydrogen bonds generate S(6) and S(5) ring motifs, respectively. The crystal structure is stabilized by inter­molecular O—H⋯O hydrogen-bond inter­actions, forming R 2 2(10) and R 2 2(20) chains along [100]. ab initio Hartree–Fock (HF), density-functional theory (DFT) and semi-empirical (AM1 and PM3) calculations and full-geometry optimizations were also performed. Although there are some discrepancies between the experimental and calculated parameters, caused presumably by the O—H⋯O hydrogen-bond inter­actions, there is an acceptable general agreement between them.
doi:10.1107/S1600536809035053
PMCID: PMC2970385  PMID: 21577870
PLoS ONE  2013;8(2):e56874.
Circular Dichroism (CD) spectroscopy is a powerful method for investigating conformational changes in proteins and therefore has numerous applications in structural and molecular biology. Here a computational investigation of the CD spectrum of the Human Carbonic Anhydrase II (HCAII), with main focus on the near-UV CD spectra of the wild-type enzyme and it seven tryptophan mutant forms, is presented and compared to experimental studies. Multilevel computational methods (Molecular Dynamics, Semiempirical Quantum Mechanics, Time-Dependent Density Functional Theory) were applied in order to gain insight into the mechanisms of interaction between the aromatic chromophores within the protein environment and understand how the conformational flexibility of the protein influences these mechanisms. The analysis suggests that combining CD semi empirical calculations, crystal structures and molecular dynamics (MD) could help in achieving a better agreement between the computed and experimental protein spectra and provide some unique insight into the dynamic nature of the mechanisms of chromophore interactions.
doi:10.1371/journal.pone.0056874
PMCID: PMC3582176  PMID: 23526922
The journal of physical chemistry. B  2009;113(15):5290-5300.
Dispersion is well known to be important in biological systems, but the effect of electron correlation in such systems remains unclear. In order to assess the relationship between the structure of a protein and its electron correlation energy, we employed both full system Hartree-Fock (HF) and second-order Møller-Plesset perturbation (MP2) calculations in conjunction with the Polarizable Continuum Model (PCM) on the native structures of two proteins and their corresponding computer-generated decoy sets. Due to the expense of the MP2 calculation, we have utilized the fragment molecular orbital method (FMO) in this study. We show that the sum of the Hartree-Fock (HF) energy and force field (LJ6) derived dispersion energy (HF + LJ6) is well correlated with the energies obtained using second-order Møller-Plesset perturbation (MP2) theory. In one of the two examples studied the correlation energy as well as the empirical dispersive energy term was able to discriminate between native and decoy structures. On the other hand, for the second protein we studied, neither the correlation energy nor dispersion energy showed discrimination capabilities; however, the ab initio MP2 energy and the HF+LJ6 both ranked the native structure correctly. Furthermore, when we randomly scrambled the Lennard-Jones parameters, the correlation between the MP2 energy and the sum of the HF energy and dispersive energy (HF+LJ6) significantly drops, which indicates that the choice of Lennard-Jones parameters is important.
doi:10.1021/jp8106952
PMCID: PMC2737261  PMID: 19320454
Summary
We present experimental results and theoretical simulations of the adsorption behavior of the metal–organic precursor Co2(CO)8 on SiO2 surfaces after application of two different pretreatment steps, namely by air plasma cleaning or a focused electron beam pre-irradiation. We observe a spontaneous dissociation of the precursor molecules as well as autodeposition of cobalt on the pretreated SiO2 surfaces. We also find that the differences in metal content and relative stability of these deposits depend on the pretreatment conditions of the substrate. Transport measurements of these deposits are also presented. We are led to assume that the degree of passivation of the SiO2 surface by hydroxyl groups is an important controlling factor in the dissociation process. Our calculations of various slab settings, using dispersion-corrected density functional theory, support this assumption. We observe physisorption of the precursor molecule on a fully hydroxylated SiO2 surface (untreated surface) and chemisorption on a partially hydroxylated SiO2 surface (pretreated surface) with a spontaneous dissociation of the precursor molecule. In view of these calculations, we discuss the origin of this dissociation and the subsequent autocatalysis.
doi:10.3762/bjnano.3.63
PMCID: PMC3458600  PMID: 23019550
Co2(CO)8; deposition; dissociation; EBID; FEBID; precursor; radiation-induced nanostructures
In this work we studied three dyes which are proposed for potential photovoltaic applications and named Dye7, Dye7-2t and Dye7-3t. The Density Functional Theory (DFT) was utilized, using the M05-2X hybrid meta-GGA functional and the 6–31+G(d,p) basis set. This level of calculation was used to find the optimized molecular structure and to predict the main molecular vibrations, the absorption and emission spectra, the molecular orbitals energies, dipole moment, isotropic polarizability and the chemical reactivity parameters that arise from Conceptual DFT. Also, the pKa values were calculated with the semi-empirical PM6 method.
doi:10.3390/ijms13044418
PMCID: PMC3344223  PMID: 22605987
molecular structure; absorption spectrum; polarizability; chemical reactivity; dipole moment; triphenylamine; dye sensitizers
We report self-assembly and phase transition behavior of lower diamondoid molecules and their primary derivatives using molecular dynamics (MD) simulation and density functional theory (DFT) calculations. Two lower diamondoids (adamantane and diamantane), three adamantane derivatives (amantadine, memantine and rimantadine) and two artificial molecules (ADM•Na and DIM•Na) are studied separately in 125-molecule simulation systems. We performed DFT calculations to optimize their molecular geometries and obtained atomic electronic charges for the corresponding MD simulation, by which we predicted self-assembly structures and simulation trajectories for the seven different diamondoids and derivatives. Our radial distribution function and structure factor studies showed clear phase transitions and self-assemblies for the seven diamondoids and derivatives.
doi:10.3390/ijms11010288
PMCID: PMC2821004  PMID: 20162016
adamantane; amantadine; density functional theory; diamantane; diamondoids; MD simulation; memantine; nanotechnology; RDF, rimantadine; self-assembly; simulation annealing; structure factor
The title compound, C13H10Cl2O2, is a mixed derivative of orthocarbonic acid. The non-crystallographic symmetry of the mol­ecule is close to C 2v. The aromatic residues are oriented in a syn conformation with respect to the Cl atoms. The least-squares planes through the phenyl rings enclose an angle of 36.11 (10)°. The C—O bonds at the central carbon are relatively short, and the O—C—O and Cl—C—Cl angles are smaller than the tetra­hedral angle. These metrical peculiarities including a mol­ecular symmetry close to C 2v are also observed in density functional theory (DFT) calculations, thus ruling out the decisive influence of inter­molecular forces in the crystal structure. Accordingly, only few and weak inter­molecular inter­actions are found. At distances smaller than the sum of the van der Waals radii, only two attractive inter­actions are detected: a weak C—H⋯O and a weak C—H⋯Cl hydrogen bond to one of the two potential acceptor atoms each.
doi:10.1107/S160053680706789X
PMCID: PMC2960455  PMID: 21201386
Bulletin of Mathematical Biology  2009;71(6):1366-1377.
A physical theory explaining the anisotropic dispersion of water and solutes in biological tissues is introduced based on the phenomena of Taylor dispersion, in which highly diffusive solutes cycle between flowing and stagnant regions in the tissue, enhancing dispersion in the direction of microvascular flow. An effective diffusion equation is derived, for which the coefficient of dispersion in the axial direction (direction of capillary orientation) depends on the molecular diffusion coefficient, tissue perfusion, and vessel density. This analysis provides a homogenization that represents three-dimensional transport in capillary beds as an effectively one-dimensional phenomenon. The derived dispersion equation may be used to simulate the transport of solutes in tissues, such as in pharmacokinetic modeling. In addition, the analysis provides a physically based hypothesis for explaining dispersion anisotropy observed in diffusion-weighted imaging (DWI) and diffusion-tensor magnetic resonance imaging (DTMRI) and suggests a means of obtaining quantitative functional information on capillary vessel density from measurements of dispersion coefficients. It is shown that a failure to account for flow-mediated dispersion in vascular tissues may lead to misinterpretations of imaging data and significant overestimates of directional bias in molecular diffusivity in biological tissues. Measurement of the ratio of axial to transverse diffusivity may be combined with an independent measurement of perfusion to provide an estimate of capillary vessel density in the tissue.
doi:10.1007/s11538-009-9405-y
PMCID: PMC3305791  PMID: 19234745
Potassium ion channels form pores in cell membranes, allowing potassium ions through while preventing the passage of sodium ions. Despite numerous high-resolution structures, it is not yet possible to relate their structure to their single molecule function other than at a qualitative level. Over the past decade, there has been a concerted effort using molecular dynamics to capture the thermodynamics and kinetics of conduction by calculating potentials of mean force (PMF). These can be used, in conjunction with the electro-diffusion theory, to predict the conductance of a specific ion channel. Here, we calculate seven independent PMFs, thereby studying the differences between two potassium ion channels, the effect of the CHARMM CMAP forcefield correction, and the sensitivity and reproducibility of the method. Thermodynamically stable ion–water configurations of the selectivity filter can be identified from all the free energy landscapes, but the heights of the kinetic barriers for potassium ions to move through the selectivity filter are, in nearly all cases, too high to predict conductances in line with experiment. This implies it is not currently feasible to predict the conductance of potassium ion channels, but other simpler channels may be more tractable.
doi:10.1021/ct4005933
PMCID: PMC3864263  PMID: 24353479

Results 1-25 (652278)