Re-examination of the anion derivatives of isoflavones by radical fragmentation in negative electrospray ionization tandem mass spectrometry: experimental and computational studies

This paper reports theoretical and experimental studies of gas-phase fragmentation reactions of four naturally occurring isoflavones. The samples were analyzed in negative ion mode by direct infusion in ESI-QqQ, ESI-QqTOF and ESI-Orbitrap systems. The MS/MS and MS(n) spectra are in agreement with the fragmentation proposals and high-resolution analyses have confirmed the formulae for each ion observed. As expected, compounds with methoxyl aromatic substitution have showed a radical elimination of center dot CH(3) as the main fragmentation pathway. A second radical loss (center dot H) occurs as previously observed for compounds which exhibit a previous homolytic center dot CH(3) cleavage (radical anion) and involves radical resonance to stabilize the anion formed. However, in this study we suggest another mechanism for the formation of the main ions, on the basis of the enthalpies for each species. Compounds without methoxy substituent dissociate at the highest energies and exhibit the deprotonated molecule as the most intense ion. Finally, energy-resolved experiments were carried out to give more details about the gas-phase dissociation reaction of the isoflavones and the results are in agreement with the theoretical approaches. Copyright (C) 2011 John Wiley & Sons, Ltd.

Ca(2+) binding to c-state of adenine nucleotide translocase (ANT)-surrounding cardiolipins enhances (ANT)-Cys(56) relative mobility: A computational-based mitochondrial permeability transition study

The oxidation of critical cysteines/related thiols of adenine nucleotide translocase (ANT) is believed to be an important event of the Ca(2+)-induced mitochondrial permeability transition (MPT), a process mediated by a cyclosporine A/ADP-sensitive permeability transition pores (PTP) opening. We addressed the ANT-Cys(56) relative mobility status resulting from the interaction of ANT/surrounding cardiolipins with Ca(2+) and/or ADP by means of computational chemistry analysis (Molecular Interaction Fields and Molecular Dynamics studies), supported by classic mitochondrial swelling assays. The following events were predicted: (i) Ca(2+) interacts preferentially with the ANT surrounding cardiolipins bound to the H4 helix of translocase, (ii) weakens the cardiolipins/ANT interactions and (iii) destabilizes the initial ANT-Cys(56) residue increasing its relative mobility. The binding of ADP that stabilizes the conformation ""m"" of ANT and/or cardiolipin, respectively to H5 and H4 helices, could stabilize their contacts with the short helix h56 that includes Cys(56), accounting for reducing its relative mobility. The results suggest that Ca(2+) binding to adenine nucleotide translocase (ANT)-surrounding cardiolipins in c-state of the translocase enhances (ANT)-Cys(56) relative mobility and that this may constitute a potential critical step of Ca(2+)-induced PTP opening. (C) 2009 Elsevier B.V. All rights reserved.

A Computational Framework for Institutional Agency

This paper provides a computational framework, based on Defeasible Logic, to capture some aspects of institutional agency. Our background is Kanger-Lindahl-P\"orn account of organised interaction, which describes this interaction within a multi-modal logical setting. This work focuses in particular on the notions of counts-as link and on those of attempt and of personal and direct action to realise states of affairs. We show how standard Defeasible Logic can be extended to represent these concepts: the resulting system preserves some basic properties commonly attributed to them. In addition, the framework enjoys nice computational properties, as it turns out that the extension of any theory can be computed in time linear to the size of the theory itself.

Two dimensional computational fluid dynamic models for waste stabilisation ponds

Traditional waste stabilisation pond (WSP) models encounter problems predicting pond performance because they cannot account for the influence of pond features, such as inlet structure or pond geometry, on fluid hydrodynamics. In this study, two dimensional (2-D) computational fluid dynamics (CFD) models were compared to experimental residence time distributions (RTD) from literature. In one of the-three geometries simulated, the 2-D CFD model successfully predicted the experimental RTD. However, flow patterns in the other two geometries were not well described due to the difficulty of representing the three dimensional (3-D) experimental inlet in the 2-D CFD model, and the sensitivity of the model results to the assumptions used to characterise the inlet. Neither a velocity similarity nor geometric similarity approach to inlet representation in 2-D gave results correlating with experimental data. However. it was shown that 2-D CFD models were not affected by changes in values of model parameters which are difficult to predict, particularly the turbulent inlet conditions. This work suggests that 2-D CFD models cannot be used a priori to give an adequate description of the hydrodynamic patterns in WSP. (C) 1998 Elsevier Science Ltd. All rights reserved.

A computational study of shock speeds in high-performance shock tubes

This paper describes U2DE, a finite-volume code that numerically solves the Euler equations. The code was used to perform multi-dimensional simulations of the gradual opening of a primary diaphragm in a shock tube. From the simulations, the speed of the developing shock wave was recorded and compared with other estimates. The ability of U2DE to compute shock speed was confirmed by comparing numerical results with the analytic solution for an ideal shock tube. For high initial pressure ratios across the diaphragm, previous experiments have shown that the measured shock speed can exceed the shock speed predicted by one-dimensional models. The shock speeds computed with the present multi-dimensional simulation were higher than those estimated by previous one-dimensional models and, thus, were closer to the experimental measurements. This indicates that multi-dimensional flow effects were partly responsible for the relatively high shock speeds measured in the experiments.

Computational binding assays of antigenic peptides

Computer models can be combined with laboratory experiments for the efficient determination of (i) peptides that bind MHC molecules and (ii) T-cell epitopes. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures. This requires the definition of standards and experimental protocols for model application. We describe the requirements for validation and assessment of computer models. The utility of combining accurate predictions with a limited number of laboratory experiments is illustrated by practical examples. These include the identification of T-cell epitopes from IDDM-, melanoma- and malaria-related antigens by combining computational and conventional laboratory assays. The success rate in determining antigenic peptides, each in the context of a specific HLA molecule, ranged from 27 to 71%, while the natural prevalence of MHC-binding peptides is 0.1-5%.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

A computational analysis of substrate binding strength by phosphorylase kinase and protein kinase A

Protein kinases exhibit various degrees of substrate specificity. The large number of different protein kinases in the eukaryotic proteomes makes it impractical to determine the specificity of each enzyme experimentally. To test if it were possible to discriminate potential substrates from non-substrates by simple computational techniques, we analysed the binding enthalpies of modelled enzyme-substrate complexes and attempted to correlate it with experimental enzyme kinetics measurements. The crystal structures of phosphorylase kinase and cAMP-dependent protein kinase were used to generate models of the enzyme with a series of known peptide substrates and non-substrates, and the approximate enthalpy of binding assessed following energy minimization. We show that the computed enthalpies do not correlate closely with kinetic measurements, but the method can distinguish good substrates from weak substrates and non-substrates. Copyright (C) 2002 John Wiley Sons, Ltd.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advancesin information technology has the potential to radically transformimmunology in the postgenomics era. Not only do we now have readyaccess to vast quantities of existing data, but new data with relevanceto immunology are being accumulated at an exponential rate. Resourcesfor computational immunology include biological databases and methodsfor data extraction, comparison, analysis and interpretation. Publiclyaccessible biological databases of relevance to immunologists numberin the hundreds and are growing daily. The ability to efficientlyextract and analyse information from these databases is vital forefficient immunology research. Most importantly, a new generationof computational immunology tools enables modelling of peptide transportby the transporter associated with antigen processing (TAP), modellingof antibody binding sites, identification of allergenic motifs andmodelling of T-cell receptor serial triggering.

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.

Thermal Characteristics of Polybia scutellaris Nests (Hymenoptera: Vespidae) Using Computational Fluid Dynamics: A Possible Adaptation to Tropical Climates

Polybia scutellaris constructs huge nests characterized by numerous spinal projections on the surface. We investigated the thermal characteristics of P scutellaris nests in order to determine whether their nest temperature is homeothermically maintained and whether the spines play a role in the thermoregulation of the nests. In order to examine these hypotheses, we measured the nest temperature in a active nest and in an abandoned nest. The temperature in the active nest was almost stable at 27 degrees C, whereas that of the abandoned nest varied with changes in the ambient temperature, suggesting that nest temperature was maintained by the thermogenesis of colony individuals. In order to predict the thermal properties of the spines, a numerical simulation was employed. To construct a 3D-model of a P scutellaris nest, the nest architecture was simplified into an outer envelope and the surface spines, for both of which the initial temperature was set at 27 degrees C. The physical properties of the simulated nest were regarded to be those of wood since the nest of this species is constructed from plant materials. When the model was exposed to cool air (12 degrees C), the temperature was lower in the models with more spines. On the other hand, when the nest was heated (42 degrees C), the temperature increase was smaller in models with more spines. It is suggested that the spines act as a heat radiator, not as an insulator, against the changes in ambient temperature.

Generation of Naphthoquinone Radical Anions by Electrospray Ionization: Solution, Gas-Phase, and Computational Chemistry Studies

Radical anions are present in several chemical processes, and understanding the reactivity of these species may be described by their thermodynamic properties. Over the last years, the formation of radical ions in the gas phase has been an important issue concerning electrospray ionization mass spectrometry studies. In this work, we report on the generation of radical anions of quinonoid compounds (Q) by electrospray ionization mass spectrometry. The balance between radical anion formation and the deprotonated molecule is also analyzed by influence of the experimental parameters (gas-phase acidity, electron affinity, and reduction potential) and solvent system employed. The gas-phase parameters for formation of radical species and deprotonated species were achieved on the basis of computational thermochemistry. The solution effects on the formation of radical anion (Q(center dot-)) and dianion (Q(2-)) were evaluated on the basis of cyclic voltammetry analysis and the reduction potentials compared with calculated electron affinities. The occurrence of unexpected ions [Q + 15](-) was described as being a reaction between the solvent system and the radical anion, Q(center dot-).The gas-phase chemistry of the electrosprayed radical anions was obtained by collisional-induced dissociation and compared to the relative energy calculations. These results are important for understanding the formation and reactivity of radical anions and to establish their correlation with the reducing properties by electrospray ionization analyses.

A Computational Study of Tetrafluoro-[2.2]Cyclophanes

A computational study of the isomers of tetrafluorinated [2.2]cyclophanes persubstituted in one ring, namely F-4-[2.2]paracyclophane (4), F-4-anti-[2.2]metacyclophane (5a), F-4-syn-[2.2]metacyclophane (5b), and F-4-[2.2]metaparacyclophane (6a and 6b), was carried out. The effects of fluorination on the geometries, relative energies, local and global aromaticity, and strain energies of the bridges and rings were investigated. An analysis of the electron density by B3PW91/6-31+G(d,p), B3LYP/6-31+G(d,p), and MP2/6-31+G(d,p) was carried out using the natural bond orbitals (NBO), natural steric analysis (NSA), and atoms in molecules (AIM) methods. The analysis of frontier molecular orbitals (MOs) was also employed. The results indicated that the molecular structure of [2.2]paracyclophane is the most affected by the fluorination. Isodesmic reactions showed that the fluorinated rings are more strained than the nonfluorinated ones. The NICS, HOMA, and PDI criteria evidenced that the fluorination affects the aromaticity of both the fluorinated and the nonfluorinated rings. The NBO and NSA analyses gave an indication that the fluorination increases not only the number of through-space interactions but also their magnitude. The AIM analysis suggested that the through-space interactions are restricted to the F-4-[2.2]metacyclophanes. In addition, the atomic properties, computed over the atomic basins, shave evidence that not only the substitution, but also the position of the bridges could affect the atomic charges. the first atomic moments, and the atomic volumes.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Evaluation of computational methods for the reconstruction of HLA haplotypes

Human leukocyte antigen (HLA) haplotypes are frequently evaluated for population history inferences and association studies. However, the available typing techniques for the main HLA loci usually do not allow the determination of the allele phase and the constitution of a haplotype, which may be obtained by a very time-consuming and expensive family-based segregation study. Without the family-based study, computational inference by probabilistic models is necessary to obtain haplotypes. Several authors have used the expectation-maximization (EM) algorithm to determine HLA haplotypes, but high levels of erroneous inferences are expected because of the genetic distance among the main HLA loci and the presence of several recombination hotspots. In order to evaluate the efficiency of computational inference methods, 763 unrelated individuals stratified into three different datasets had their haplotypes manually defined in a family-based study of HLA-A, -B, -DRB1 and -DQB1 segregation, and these haplotypes were compared with the data obtained by the following three methods: the Expectation-Maximization (EM) and Excoffier-Laval-Balding (ELB) algorithms using the arlequin 3.11 software, and the PHASE method. When comparing the methods, we observed that all algorithms showed a poor performance for haplotype reconstruction with distant loci, estimating incorrect haplotypes for 38%-57% of the samples considering all algorithms and datasets. We suggest that computational haplotype inferences involving low-resolution HLA-A, HLA-B, HLA-DRB1 and HLA-DQB1 haplotypes should be considered with caution.