Finite element modelling of reactive mass transport problems in fluid-saturated porous media

We use the finite element method to solve reactive mass transport problems in fluid-saturated porous media. In particular, we discuss the mathematical expression of the chemical reaction terms involved in the mass transport equations for an isothermal, non-equilibrium chemical reaction. It has turned out that the Arrhenius law in chemistry is a good mathematical expression for such non-equilibrium chemical reactions especially from the computational point of view. Using the finite element method and the Arrhenius law, we investigate the distributions of PH (i.e. the concentration of H+) and the relevant reactive species in a groundwater system. Although the main focus of this study is on the contaminant transport problems in groundwater systems, the related numerical techniques and principles are equally applicable to the orebody formation problems in the geosciences. Copyright (C) 1999 John Wiley & Sons, Ltd.

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%.

The role of carbon surface chemistry in N2O conversion to N2 over Ni catalyst supported on activated carbon

The effect of acidic treatments on N2O reduction over Ni catalysts supported on activated carbon was systematically studied. The catalysts were characterized by N-2 adsorption, mass titration, temperature-programmed desorption (TPD), and X-ray photoelectron spectrometry (XPS). It is found that surface chemistry plays an important role in N2O-carbon reaction catalyzed by Ni catalyst. HNO3 treatment produces more active acidic surface groups such as carboxyl and lactone, resulting in a more uniform catalyst dispersion and higher catalytic activity. However, HCl treatment decreases active acidic groups and increases the inactive groups, playing an opposite role in the catalyst dispersion and catalytic activity. A thorough discussion of the mechanism of the N2O catalytic reduction is made based upon results from isothermal reactions, temperature-programmed reactions (TPR) and characterization of catalysts. The effect of acidic treatment on pore structure is also discussed. (C) 1999 Elsevier Science B.V. All rights reserved.

Influence of Mg content on the microstructure and solid solution chemistry of Al-7%Si-Mg casting alloys during solution treatment

The solution treatment stage of the T6 heat-treatment of Al-7%Si-Mg foundry alloys influences microstructural features such as Mg2Si dissolution, and eutectic silicon spheroidisation and coarsening. Microstructural and microanalytical studies have been conducted across a range of Sr-modified Al-7%Si alloys, with an Fe content of 0.12% and Mg contents ranging from 0.3-0.7wt%. Qualitative and quantitative metallography have shown that, in addition to the above changes, solution treatment also results in changes to the relative proportions of iron-containing intermetallic particles and that these changes are composition-dependent. While solution treatment causes a substantial transformation of pi phase to beta phase in low Mg alloys (0.3-0.4%), this change is not readily apparent at higher Mg levels (0.6-0.7%). The pi to beta transformation is accompanied by a release of Mg into the aluminum matrix over and above that which arises from the rapid dissolution of Mg2Si. Since the level of matrix Mg retained after quenching controls an alloy's subsequent precipitation hardening response, a proper understanding of this phase transformation is crucial if tensile properties are to be maximised.

The radiation chemistry of poly(dimethylsiloxane)

The radiation chemistry of poly(dimethyl siloxane) has been investigated with respect to identification of the nature of the small molecule chain scission products. Low molecular weight linear and cyclic products have been identified through the use of Si-29 solution NMR, GPC and MALDI-TOF mass spectrometry. It has been suggested that the low molecular weight cyclic products are formed by back-biting depolymerization reactions.

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.

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 the enthalpy of formation, proton affinity, and gas-phase basicity of gamma-butyrolactone and 2-pyrrolidinone by isodesmic reactions

The knowledge of thermochemical parameters such as the enthalpy of formation, gas-phase basicity, and proton affinity may be the key to understanding molecular reactivity. The obtention of these thermochemical parameters by theoretical chemical models may be advantageous when experimental measurements are difficult to accomplish. The development of ab initio composite models represents a major advance in the obtention of these thermochemical parameters,. but these methods do not always lead to accurate values. Aiming at achieving a comparison between the ab initio models and the hybrid models based on the density functional theory (DFT), we have studied gamma-butyrolactone and 2-pyrrolidinone with a goal of obtaining high-quality thermochemical parameters using the composite chemical models G2, G2MP2, MP2, G3, CBS-Q, CBS-4, and CBS-QB3; the DFT methods B3LYP, B3P86, PW91PW91, mPW1PW, and B98; and the basis sets 6-31G(d), 6-31+G(d), 6-31G(d,p), 6-31+G(d,p), 6-31++G(d,p), 6-311G(d), 6-311+G(d), 6-311G(d,p), 6-311+G(d,p), 6-311++G(d,p), aug-cc-pVDZ, and aug-cc-pVTZ. Values obtained for the enthalpies of formation, proton affinity, and gas-phase basicity of the two target molecules were compared to the experimental data reported in the literature. The best results were achieved with the use of DFT models, and the B3LYP method led to the most accurate data.

Protein crystallography and examples of its applications in medicinal chemistry

The field of protein crystallography inspires and enthrals, whether it be for the beauty and symmetry of a perfectly formed protein crystal, the unlocked secrets of a novel protein fold, or the precise atomic-level detail yielded from a protein-ligand complex. Since 1958, when the first protein structure was solved, there have been tremendous advances in all aspects of protein crystallography, from protein preparation and crystallisation through to diffraction data measurement and structure refinement. These advances have significantly reduced the time required to solve protein crystal structures, while at the same time substantially improving the quality and resolution of the resulting structures. Moreover, the technological developments have induced researchers to tackle ever more complex systems, including ribosomes and intact membrane-bound proteins, with a reasonable expectation of success. In this review, the steps involved in determining a protein crystal structure are described and the impact of recent methodological advances identified. Protein crystal structures have proved to be extraordinarily useful in medicinal chemistry research, particularly with respect to inhibitor design. The precise interaction between a drug and its receptor can be visualised at the molecular level using protein crystal structures, and this information then used to improve the complementarity and thus increase the potency and selectivity of an inhibitor. The use of protein crystal structures in receptor-based drug design is highlighted by (i) HIV protease, (ii) influenza virus neuraminidase and (iii) prostaglandin H-2-synthetase. These represent, respectively, examples of protein crystal structures that (i) influenced the design of drugs currently approved for use in the treatment of HIV infection, (ii) led to the design of compounds currently in clinical trials for the treatment of influenza infection and (iii) could enable the design of highly specific non-steroidal anti-inflammatory drugs that lack the common side-effects of this drug class.

The chemistry of 5-oxodihydroisoxazoles .16. A new synthesis of pyrroles, furans, thiophens and their benzo analogues

Ethyl 5-oxo-2-phenyl-2,5-dihydroisoxazole-4-carboxylate (2) was photolysed at 300 mn in the presence of phenols, enols, anilines, enamines, aryl thiols and thioenols affording enamines. Treatment of these enamines with Lewis or protic acids gives the respective benzo and five-membered ring systems.

Comprehensive study of surface chemistry of MCM-41 using Si-29 CP/MAS NMR, FTIR, pyridine-TPD, and TGA

A comprehensive study was conducted on mesoporous MCM-41. Spectroscopic examinations demonstrated that three types of silanol groups, i.e., single, (SiO)(3)Si-OH, hydrogen-bonded, (SiO)(3)Si-OH-OH-Si(SiO)(3), and geminal, (SiO)(2)Si(OH)(2), can be observed. The number of silanol groups/nm(2), alpha(OH), as determined by NMR, varies between 2.5 and 3.0 depending on the template-removal methods. All these silanol groups were found to be the active sites for adsorption of pyridine with desorption energies of 91.4 and 52.2 kJ mol(-1), respectively. However, only free silanol groups (involving single and geminal silanols) are highly accessible to the silylating agent, chlorotrimethylsilane. Silylation can modify both the physical and chemical properties of MCM-41.