Jerry P. Greenberg

The prediction of methane solubility in natural waters to high ionic strength from 0 to 250°C and from 0 to 1600 bar

Abstract A model for the solubility of methane in brines (0–6 m) for temperatures from 0 to 250°C and for pressures from 0 to 1600 bar (or slightly above) is presented. The model is based on Pitzer phenomenology for the liquid phase and a highly accurate equation of state recently developed for the vapor phase. Comparison of model predictions with experimental data indicates that they are within experimental uncertainty. Most experimental data sets are consistent within errors of about 7%. Although the parameters were evaluated from binary and ternary data, the model accurately predicts methane solubility in much more complicated systems like seawater and Salton geothermal brines. Application to fluid inclusion analysis is discussed. Minimum trapping pressures are calculated given the composition and homogenization temperature.

The prediction of mineral solubilities in natural waters: A chemical equilibrium model for the Na-K-Ca-Cl-SO4-H2O system to high concentration from 0 to 250°C☆

A chemical equilibrium model is described which is used to calculate solubilities within experimental uncertainties in the Na-K-Ca-Cl-SO4-H2O system from zero to high ionic strength and from 0 to 250°C. This model is an expansion of the variable temperature Na-Ca-Cl-SO4-H2O model of Moller (1988). It is parameterized by fitting available osmotic and solubility data in all common ion systems involving the potassium ion: Na-K-Cl-H2O, Na-K-SO4-H2O, K-Cl-SO4-H2O, K-Ca-Cl-H2O, and K-Ca-SO4-H2O. Limitations of the model due to data insufficiencies are discussed and comparisons of model calculations with the available data are given. Model predictions for solubility in the complex reciprocal systems, Na-K-Cl-SO4-H2O and K-Ca-Cl-SO4-H2O, are compared with experiment. Data for the two systems were available only in the temperature ranges 0–100°C and 25–55°C, respectively. The phase diagram predicted for the halite-saturated Na-K-Ca-Cl-SO4-H2O quinary system at 100°C is also presented. This model will be used to extend the Harvie et al. (1984) model for the Na-K-Ca-Mg-Cl-SO4-CO2-H2O seawater system to high temperature.

A chemical equilibrium algorithm for highly non-ideal multiphase systems: Free energy minimization☆

A method is presented for calculating equilibrium phase assemblages in very nonideal systems. It may be applied to any system for which a thermodynamically consistent model of the free energy which satisfies the usual Maxwell relations and convexity criterion is available. The algorithm minimizes the Gibbs free energy by independently choosing stable reaction directions. The procedure is described in detail and various numerical problems encountered and strategies for dealing with them are discussed. It will be shown that the necessary and sufficient conditions for solution phase selection may be derived from the values of the Lagrange multipliers corresponding to constraints on phases that are not present in the system. The method for evaluating the solution phase Lagrangian multipliers and choosing the optimum composition with which to bring the new solution phase into the system involves a separate constrained minimization problem. This method is sufficiently general so that the correct phase assemblage is chosen free from external control. Special procedures for adding and removing phases including solution phases are also described.

QMView: a computational chemistry three-dimensional visualization tool at the interface between molecules and mankind.

QMView is designed to facilitate the visualization and interpretation of quantum mechanical data. Capabilities include display of chemical structure, animation of quantum mechanically determined vibrational modes, and depiction of electronic properties and three-dimensional molecular orbitals. QMView has a user-friendly interface that allows users to interactively manipulate many features of the molecular structure and/or property, including positioning and structure representation, via mouse-activated dialog boxes. Although the interface allows input from results of any of the popularly used quantum mechanical software, we have focused on GAMESS, a widely distributed quantum chemistry code. QMView has been designed with the special feature of working in distributed mode with GAMESS, the latter running on a supercomputer, the former running on a Silicon Graphics platform. Ancillary programs provide a method of obtaining output of graphic images in various media, including hardcopy, PostScript files, slide, and/or video. These and other original features discussed in this article provide a graphic interface that is unique compared to others that are currently available. Examples of images produced by QMView are presented.

An All-Atom Model of the Structure of Human Copper Transporter 1

Human copper transporter 1 (hCTR1) is the major high affinity copper influx transporter in mammalian cells that also mediates uptake of the cancer chemotherapeutic agent cisplatin. A low resolution structure of hCTR1 determined by cryoelectron microscopy was recently published. Several protein structure simulation techniques were used to create an all-atom model of this important transporter using the low resolution structure as a starting point. The all-atom model provides new insights into the roles of specific residues of the N-terminal extracellular domain, the intracellular loop, and C-terminal region in metal ion transport. In particular, the model demonstrates that the central region of the pore contains four sets of methionine triads in the intramembranous region. The structure confirms that two triads of methionine residues delineate the intramembranous region of the transporter, and further identifies two additional methionine triads that are located in the extracellular N-terminal part of the transporter. Together, the four triads create a structure that promotes stepwise transport of metal ions into and then through the intramembranous channel of the transporter via transient thioether bonds to methionine residues. Putative copper-binding sites in the hCTR1 trimer were identified by a program developed by us for prediction of metal-binding sites. These sites correspond well with the known effects of mutations on the ability of the protein to transport copper and cisplatin.

Computer Modeling for Geothermal Systems: Predicting Carbonate and Silica Scale Formation, CO2 Breakout and H2S Exchange

This paper describes chemical equilibrium models for predicting carbonate and silica scale formation, CO2 breakout and H2S gas exchange in geothermal brine systems to high concentration and temperature. The equilibrium description is based on a minimization of the free energy of the system with solute activities described by the semiempirical equations of Pitzer (1973; 1987). The carbonate model is parameterized by appropriate osmotic, electromotive force and solubility data (T ≤ 250°C) available in binary and ternary solutions in the seawater Na–K–H–Ca–Cl–SO4–H2O system. The silica model is parameterized by solubility data to 320°C in the Na–Mg–Cl–SO4–SiO2–H2O system. The H2S model is parameterized by solubility data in the H2S–NaCl–H2O system to 320°C. The predictive capabilities of the models are demonstrated by comparison to both laboratory and field data. Examples have been given to illustrate the use of the carbonate model to predict downhole brine compositions in contact with specified formation minerals, temperature and pressure effects on carbonate scaling, the effect of scale inhibitors and breakout characteristics. Application of the silica model demonstrates the effect of temperature on silica scale formation. These illustrations show that the models can be used to reliably predict important chemical behavior in geothermal operations.

An end-to-end Web services-based infrastructure for biomedical applications

Services-oriented architectures hold a lot of promise for grid-enabling scientific applications. In recent times, Web services have gained wide-spread acceptance in the grid community as the standard way of exposing application functionality to end-users. Web services-based architectures provide accessibility via a multitude of clients, and the ability to enable composition of data and applications in novel ways for facilitating innovation across scientific disciplines. However, issues of diverse data formats and styles which hinder interoperability and integration must be addressed. Providing Web service wrappers for legacy applications alleviates many problems because of the exchange of strongly typed data, defined and validated using XML schemas, that can be used by workflow tools for application integration. In this paper, we describe the end-to-end architecture of such a system for biomedical applications that are part of the National Biomedical Computation Resource (NBCR). We present the technical challenges in setting up such an infrastructure, and discuss in detail the back-end resource management, application services, user-interfaces, and the security infrastructure for the same. We also evaluate our prototype infrastructure, discuss some of its shortcomings, and the future work that may be required to address them.

MAPAS: a tool for predicting membrane-contacting protein surfaces.

To the editor: Many important biological processes, from serum phospholipid metabolism to amyloid disease, involve formation of protein-membrane complexes. Thus, tools for identifying membranecontacting features in a protein structure are very important. However, few algorithmic approaches for membrane-contacting surface prediction have yet been reported1,2. We developed a program and web-based tool called MAPAS, or membrane-associated-proteins assessment (http://cancertools.sdsc.edu/MAPAS/pro2.html). MAPAS uses a set of algorithmic scoring functions to predict whether a given protein structure can form strong membrane contacts and to define the regions of the protein surface that most likely form such contacts (Supplementary Methods online). The MAPAS input window (Supplementary Fig. 1 online) accepts Protein Data Bank (PDB) protein identifiers or a pasted file in pdb format. The MAPAS algorithm is based on the assumption that membrane-contacting protein surfaces have a specific distribution of membranephilic surface residues in a plane. This planar region would contact the membrane (the explicit assumption is that, on the scale of proteins, the cell membrane can be considered as a plane). These residues must provide the necessary binding energy to keep the protein at the membrane surface. MAPAS (i) identifies the planar surfaces that encompass a given protein, and (ii) scores them according to their membranephilic properties. To provide a measure of membranephilicity, we estimated the relative tendency of individual residues to bind to a phospholipid bilayer. We calculated scoring functions using a semi-empiric approach based on steered molecular dynamics (Supplementary Figs. 2–4 and Supplementary Table 1 online) and Poisson-Boltzmann calculations (Supplementary Methods). MAPAS accepts a protein’s three-dimensional structure as input and identifies all planes encompassing the protein structure (Fig. 1a) then calculates all residues that lie in the layer of a given thickness (Supplementary Fig. 5 online). Then MAPAS sorts the planar protein surfaces based on their membranephilic character. The output window displays rotatable three-dimensional presentations of submitted proteins with their possible membrane–contacting surfaces indicated (see for example, Supplementary Figs. 6 and 7 online). We validated the performance of MAPAS with several known membrane-contacting proteins (Fig. 1b and Supplementary Tables 2 and 3 online). MAPAS can predict membrane-contacting proteins, membrane-associated proteins and the membrane-contacting surfaces of proteins including transmembrane proteins (Supplementary Discussion online). Nevertheless, as with all prediction programs, MAPAS can yield false positive and false negative predictions. One possible source of error is the fact that coordinates of proteins listed in PDB as membrane-contacting do not include the membrane–contacting regions, either because they are disordered or because they are engineered out of the protein to permit crystallization. Another problem is the relatively small area of membrane contact found in some proteins. Our tests show that MAPAS is reliable when the number of membrane-contacting residues is at least 5 (data not shown). With fewer residues in the membrane-contacting zone the statistical error increases. Note: Supplementary information is available on the Nature Methods website.

QMView and GAMESS: Integration into the World Wide Computational Grid

High performance computing, storage, visualization, and database infrastructures are increasing geometrically in complexity as scientists move towards grid-based computing. While this is natural, it has the effect of pushing computational capabilities beyond the reach of scientists because of the time needed to harness the infrastructure. Hiding the complexity of networked resources becomes essential if scientists are to utilize them effectively. In this work, we describe our efforts to integrate various computational chemistry components into a scientific computing environment. We briefly describe improvements we have made to individual components of the chemistry environment as well as future directions, followed by a more in-depth discussion of our strategy for integration into a grid workflow environment based on web services, which enables access to remote resources while shielding users from the complexities of the grid infrastructures. A preliminary schema for storing data obtained from computational chemistry calculations is also described.

Structural Diversity of Alzheimer's Disease Amyloid-β Dimers and Their Role in Oligomerization and Fibril Formation

Alzheimers disease (AD) is associated with the formation of toxic amyloid-β (Aβ)42 oligomers, and recent evidence supports a role for Aβ dimers as building blocks for oligomers. Molecular dynamics simulation studies have identified clans for the dominant conformations of Aβ42 forming dimers; however, it is unclear if a larger spectrum of dimers is involved and which set(s) of dimers might evolve to oligomers verse fibrils. Therefore, for this study we generated multiple structural conformations of Aβ42, using explicit all-atom molecular dynamics, and then clustering the different structures based on key conformational similarities. Those matching a selection threshold were then used to model a process of oligomerization. Remarkably, we showed a greater diversity in Aβ dimers than previously described. Depending on the clan family, different types of Aβ dimers were obtained. While some had the tendency to evolve into oligomeric rings, others formed fibrils of diverse characteristics. Then we selected the dimers that would evolve to membranephilic annular oligomers. Nearly one third of the 28 evaluated annular oligomers had the dimer interfaces between the neighboring Aβ42 monomers with possible salt bridges between the residue K28 from one side and either residue E22 or D23 on the other. Based on these results, key amino acids were identified for point mutations that either enhanced or suppressed the formation and toxicity of oligomer rings. Our studies suggest a greater diversity of Aβ dimers. Understanding the structure of Aβ dimers might be important for the rationale design of small molecules that block formation of toxic oligomers.