			Home About us Contact

Reference Set (reference + set)

Distribution by Scientific Domains

Chemistry	80%

Selected Abstracts

Soft Coulomb hole method applied to molecules

INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 5 2007
J. Ortega-Castro
Abstract The soft Coulomb hole method introduces a perturbation operator, defined by ,e/r12 to take into account electron correlation effects, where , represents the width of the Coulomb hole. A new parametrization for the soft Coulomb hole operator is presented with the purpose of obtaining better molecular geometries than those resulting from Hartree,Fock calculations, as well as correlation energies. The 12 parameters included in , were determined for a reference set of 12 molecules and applied to a large set of molecules (38 homo- and heteronuclear diatomic molecules, and 37 small and medium-size molecules). For these systems, the optimized geometries were compared with experimental values; correlation energies were compared with results of the MP2, B3LYP, and Gaussian 3 approach. On average, molecular geometries are better than the Hartree,Fock values, and correlation energies yield results halfway between MP2 and B3LYP. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007 [source]

Theoretical studies on empirical structure,reactivity relationship: the Yukawa,Tsuno equation

JOURNAL OF PHYSICAL ORGANIC CHEMISTRY, Issue 6 2003
Kazuhide Nakata
Abstract The substituent-dependent stabilization energies (,X,E) of a series of ,,,-R1R2 benzyl cations were determined by means of ab initio calculation at the MP2/6,31G*//RHF/6,31G*,+,ZPE (scaled 0.8929) level, based on the isodesmic hydride transfer reactions between ring X-substituted and unsubstituted R1R2 benzyl cations. Substituent stabilities (,X,E) of ,,,-dimethylbenzyl cations were determined in the same way, to define a reference set of the ab initio ,+ values. The (,X,E) of ,,,-dimethylbenzyl cations of which the cation center is set orthogonal to the benzene ,-system were correlated linearly with ,0 (solution). Based on this correlation, a set of ab initio ,0 constants [(,0)ab] was determined. The ab initio resonance substituent constants were defined as (,+)ab,,,(,0)ab. Employing the present ab initio set of (,0)ab and constants, the ab initio Yukawa,Tsuno (Y,T) equation was applied to 18 sets of cation stabilities ,X,E associated with hydride transfer reaction systems. Successful applications of the ab initio Y,T equation confirm the theoretical validity of the empirical Y,T relationship; in practice, the Y,T equation makes it possible to divide the electronic substituent effect into the non-resonance and resonance contributions. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Neuro-fuzzy structural classification of proteins for improved protein secondary structure prediction

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 8 2003
Joachim A. Hering
Abstract Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins. [source]

APOE is not Associated with Alzheimer Disease: a Cautionary tale of Genotype Imputation

ANNALS OF HUMAN GENETICS, Issue 3 2010
Gary W. Beecham
Summary With the advent of publicly available genome-wide genotyping data, the use of genotype imputation methods is becoming increasingly common. These methods are of particular use in joint analyses, where data from different genotyping platforms are imputed to a reference set and combined in a single analysis. We show here that such an analysis can miss strong genetic association signals, such as that of the apolipoprotein-e gene in late-onset Alzheimer disease. This can occur in regions of weak to moderate LD; unobserved SNPs are not imputed with confidence so there is no consensus SNP set on which to perform association tests. Both IMPUTE and Mach software are tested, with similar results. Additionally, we show that a meta-analysis that properly accounts for the genotype uncertainty can recover association signals that were lost under a joint analysis. This shows that joint analyses of imputed genotypes, particularly failure to replicate strong signals, should be considered critically and examined on a case-by-case basis. [source]

Crystallographic model quality at a glance

ACTA CRYSTALLOGRAPHICA SECTION D, Issue 3 2009
Ludmila Urzhumtseva
A crystallographic macromolecular model is typically characterized by a list of quality criteria, such as R factors, deviations from ideal stereochemistry and average B factors, which are usually provided as tables in publications or in structural databases. In order to facilitate a quick model-quality evaluation, a graphical representation is proposed. Each key parameter such as R factor or bond-length deviation from `ideal values' is shown graphically as a point on a `ruler'. These rulers are plotted as a set of lines with the same origin, forming a hub and spokes. Different parts of the rulers are coloured differently to reflect the frequency (red for a low frequency, blue for a high frequency) with which the corresponding values are observed in a reference set of structures determined previously. The points for a given model marked on these lines are connected to form a polygon. A polygon that is strongly compressed or dilated along some axes reveals unusually low or high values of the corresponding characteristics. Polygon vertices in `red zones' indicate parameters which lie outside typical values. [source]