Elevated GM-CSF and IL-1beta levels compromise the ability of p38 MAPK inhibitors to modulate TNFalpha levels in the human monocytic/macrophage U937 cell line.

Rheumatoid arthritis (RA) is a complex, multicellular disease involving a delicate balance between both pro- and anti-inflammatory cytokines which ultimately determines the disease phenotype. The simultaneous presence of multiple signaling molecules, and more specifically their relative levels, potentially influences the efficacy of directed therapies. Using the human U937 monocytic cell line, we generated a self-consistent dataset measuring 50 cytokines and 23 phosphoproteins in the presence of 6 small molecule inhibitors under 15 stimulatory conditions throughout a 24 hour time course. From this dataset, we are able to explore phosphoprotein and cytokine relationships, as well as evaluate the significance of cellular context on the ability of small molecule inhibitors to block inflammatory processes. We show that the ability of a p38 inhibitor to attenuate TNFalpha production is influenced by local levels of GM-CSF and IL-1beta, two cytokines known to be elevated in the joints of RA patients. Within the cell, compensatory mechanisms between signaling pathways are apparent, as selective p38 MAPK inhibition results in the increased phosphorylation of other MAPKs (ERK and JNK) and their downstream substrates (CREB, c-Jun, and ATF-2). Further, we demonstrate that TNFalpha-neutralizing antibodies have secondary effects on cytokine production, impacting more than just TNFalpha alone. p38 MAPK inhibition using a small molecule inhibitor also blocks production of anti-inflammatory cytokines including IL-10, IL-1ra and IL-2ra. Collectively, the impact of cell context on TNFalpha production and unintended blockade of anti-inflammatory cytokines may compromise the efficacy of p38 inhibitors in a clinical setting. The effort described in this work evaluates the effect of inhibitors on multiple endpoints (both intra- and extracellular), under a range of biologically relevant conditions, thus providing a unique means for differentiation of compounds and potential opportunity for improved pharmacological manipulation of disease endpoints in RA.

Association (micellization) and partitioning of aglycon triterpenoids.

Micellization and solution properties of the aglycon triterpenoids asiatic acid (AA) and madecassic acid (MA) were examined experimentally and in computational simulations. AA and MA belong to the large class of bioactive aglycon triterpenoids, for which limited physicochemical data are available. In this study, solubility, partition coefficient, critical micelle concentrations (CMC), and surface tensions of AA and MA were measured. Reverse phase HPLC data, supported by dye probe experiments and drop shape analysis, showed the CMC in phosphate buffered saline (PBS) to be 15+/-2 microM, and 86+/-9 microM for AA and MA, respectively. The surface tensions of AA and MA in PBS were 64.1 and 64.4 mN/m, respectively. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry indicated the aggregation numbers of AA and MA to be 5 to 7. Molecular dynamics simulations confirmed that molecular association could occur between 5 and 7 molecules in solution. The IC(50) of AA and MA on human small cell carcinoma and human glioblastoma cell lines was 25+/-5 microM and 66+/-13 microM, respectively. The IC(50) is within the range of calculated CMC of AA and MA in bioassay media, suggesting that the micellar aggregates may lead to their cytotoxicity.

Molecular dynamics simulation and thermodynamic modeling of the self-assembly of the triterpenoids asiatic acid and madecassic acid in aqueous solution.

The self-assembly behavior of the triterpenoids asiatic acid (AA) and madecassic acid (MA), both widely studied bioactive phytochemicals that are similar in structure to bile salts, were investigated in aqueous solution through atomistic-level molecular dynamics (MD) simulation. AA and MA molecules initially distributed randomly in solution were observed to aggregate into micelles during 75 ns of MD simulation. A "hydrophobic contact criterion" was developed to identify micellar aggregates from the computer simulation results. From the computer simulation data, the aggregation number of AA and MA micelles, the monomer concentration, the principal moments of the micelle radius of gyration tensor, the one-dimensional growth exhibited by AA and MA micelles as the aggregation number increases, the level of internal ordering within AA and MA micelles (quantified using two different orientational order parameters), the local environment of atoms within AA and MA in the micellar environment, and the total, hydrophilic, and hydrophobic solvent accessible surface areas of the AA and MA micelles were each evaluated. The MD simulations conducted provide insights into the self-assembly behavior of structurally complex, nontraditional surfactants in aqueous solution. Motivated by the high computational cost required to obtain an accurate estimate of the critical micelle concentrations (CMCs) of AA and MA from evaluation of the average monomer concentration present in the AA and MA simulation cells, a modified computer simulation/molecular-thermodynamic model (referred to as the MCS-MT model) was formulated to quantify the free-energy change associated with optimal AA and MA micelle formation in order to predict the CMCs of AA and MA. The predicted CMC of AA was found to be 59 microM, compared with the experimentally measured CMC of 17 microM, and the predicted CMC of MA was found to be 96 microM, compared with the experimentally measured CMC of 62 microM. The AA and MA CMCs predicted using the MCS-MT model are much more accurate than the CMCs inferred from the monomer concentrations of AA and MA present in the simulation cells after micelle self-assembly (2390 microM and 11,300 microM, respectively). The theoretical modeling results obtained for AA and MA indicate that, by combining computer simulation inputs with molecular-thermodynamic models of surfactant self-assembly, reasonably accurate estimates of surfactant CMCs can be obtained with a fraction of the computational expense that would be required by using computer simulations alone.

Flexible informatics for linking experimental data to mathematical models via DataRail.

MOTIVATION: Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all normalization, scaling, and fusion routines used to assemble the training data from primary results. RESULTS: We describe the implementation of DataRail, an open source MATLAB-based toolbox that stores experimental data in flexible multi-dimensional arrays, transforms arrays so as to maximize information content, and then constructs models using internal or external tools. Data integrity is maintained via a containment hierarchy for arrays, imposition of a metadata standard based on a newly proposed MIDAS format, assignment of semantically typed universal identifiers, and implementation of a procedure for storing the history of all transformations with the array. We illustrate the utility of DataRail by processing a newly collected set of approximately 22 000 measurements of protein activities obtained from cytokine-stimulated primary and transformed human liver cells. AVAILABILITY: DataRail is distributed under the GNU General Public License and available at http://code.google.com/p/sbpipeline/

Molecular-thermodynamic theory of micellization of multicomponent surfactant mixtures: 1. Conventional (pH-Insensitive) surfactants.

A molecular-thermodynamic (MT) theory was developed to model the micellization of mixtures containing an arbitrary number of conventional (pH-insensitive) surfactants. The theory was validated by comparing predicted and experimental cmc's of ternary surfactant mixtures, yielding results that were comparable to, and sometimes better than, the cmc's determined using regular solution theory. The theory was also used to model a commercial nonionic surfactant (Genapol UD-079), which was modeled as a mixture of 16 surfactant components. The predicted cmc agreed well with the experimental cmc, and the monomer concentration was predicted to increase significantly above the cmc. In addition, the monomer and the micelle compositions were predicted to vary significantly with surfactant concentration. These composition variations were rationalized in terms of competing steric and entropic effects and a micelle shape transition near the cmc. To understand the packing constraints imposed on ternary surfactant mixtures better, the maximum micelle radius was also examined theoretically. The MT theory presented here represents the first molecular-based theory of the micellization behavior of mixtures of three or more conventional surfactants. In article 2 of this series, the MT theory will be extended to model the micellization of mixtures of conventional and pH-sensitive surfactants.

Molecular-thermodynamic theory of micellization of multicomponent surfactant mixtures: 2. pH-sensitive surfactants.

In article 1 of this series, we developed a molecular-thermodynamic (MT) theory to model the micellization of mixtures containing an arbitrary number of conventional (pH-insensitive) surfactants. In this article, we extend the MT theory to model mixtures containing a pH-sensitive surfactant. The MT theory was validated by examining mixtures containing both a pH-sensitive surfactant and a conventional surfactant, which effectively behave like ternary surfactant mixtures. We first compared the predicted micellar titration data to experimental micellar titration data that we obtained for varying compositions of mixed micelles containing the pH-sensitive surfactant dodecyldimethylamine oxide (C12DAO) mixed with either a cationic surfactant (dodecyltrimethylammonium bromide, C12TAB), a nonionic surfactant (dodecyl octa(ethylene oxide), C12E8), or an anionic surfactant (sodium dodecyl sulfate, SDS) surfactant. The MT theory accurately modeled the titration behavior of C12DAO mixed with C12E8. However, C12DAO was observed to interact more favorably with SDS and with C12TAB than was predicted by the MT theory. We also compared predictions to data from the literature for mixtures of C12DAO and SDS. Although the pH values of solutions with no added acid were modeled with only qualitative accuracy, the MT theory resulted in quantitatively accurate predictions of solution pH for mixtures containing added acid. In addition, the predicted degree of counterion binding yielded a lower bound to the experimentally measured value. Finally, we predicted the critical micelle concentration (cmc) of solutions of two pH-sensitive surfactants, tetradecyldimethylamine oxide (C14DAO) and hexadecyldimethyl betaine (C16Bet), at varying solution pH and surfactant composition. However, at the pH values considered, the pH sensitivity of C16Bet could be neglected, and it was equivalently modeled as a zwitterionic surfactant. The cmc's predicted using the MT theory agreed well with the experimental cmc's and were found to be comparable to and sometimes better than the cmc's determined using the regular solution theory (RST), even though the empirical RST utilizes experimentally measured cmc's as an input. The MT theory presented here represents the first molecular-based quantitative description of the micellization behavior of mixtures of pH-sensitive surfactants and conventional surfactants, and allows qualitative and quantitative predictions of the micellization behavior of a variety of surfactant systems.

Quantifying the hydrophobic effect. 1. A computer simulation-molecular-thermodynamic model for the self-assembly of hydrophobic and amphiphilic solutes in aqueous solution.

Surfactant micellization and micellar solubilization in aqueous solution can be modeled using a molecular-thermodynamic (MT) theoretical approach; however, the implementation of MT theory requires an accurate identification of the portions of solutes (surfactants and solubilizates) that are hydrated and unhydrated in the micellar state. For simple solutes, such identification is comparatively straightforward using simple rules of thumb or group-contribution methods, but for more complex solutes, the hydration states in the micellar environment are unclear. Recently, a hybrid method was reported by these authors in which hydrated and unhydrated states are identified by atomistic simulation, with the resulting information being used to make MT predictions of micellization and micellar solubilization behavior. Although this hybrid method improves the accuracy of the MT approach for complex solutes with a minimum of computational expense, the limitation remains that individual atoms are modeled as being in only one of two states-head or tail-whereas in reality, there is a continuous spectrum of hydration states between these two limits. In the case of hydrophobic or amphiphilic solutes possessing more complex chemical structures, a new modeling approach is needed to (i) obtain quantitative information about changes in hydration that occur upon aggregate formation, (ii) quantify the hydrophobic driving force for self-assembly, and (iii) make predictions of micellization and micellar solubilization behavior. This article is the first in a series of articles introducing a new computer simulation-molecular thermodynamic (CS-MT) model that accomplishes objectives (i)-(iii) and enables prediction of micellization and micellar solubilization behaviors, which are infeasible to model directly using atomistic simulation. In this article (article 1 of the series), the CS-MT model is introduced and implemented to model simple oil aggregates of various shapes and sizes, and its predictions are compared to those of the traditional MT model. The CS-MT model is formulated to allow the prediction of the free-energy change associated with aggregate formation (gform) of solute aggregates of any shape and size by performing only two computer simulations-one of the solute in bulk water and the other of the solute in an aggregate of arbitrary shape and size. For the 15 oil systems modeled in this article, the average discrepancy between the predictions of the CS-MT model and those of the traditional MT model for gform is only 1.04%. In article 2, the CS-MT modeling approach is implemented to predict the micellization behavior of nonionic surfactants; in article 3, it is used to predict the micellization behavior of ionic and zwitterionic surfactants.

Quantifying the hydrophobic effect. 2. A computer simulation-molecular-thermodynamic model for the micellization of nonionic surfactants in aqueous solution.

In this article, the validity and accuracy of the CS-MT model is evaluated by using it to model the micellization behavior of seven nonionic surfactants in aqueous solution. Detailed information about the changes in hydration that occur upon the self-assembly of the surfactants into micelles was obtained through molecular dynamics simulation and subsequently used to compute the hydrophobic driving force for micelle formation. This information has also been used to test, for the first time, approximations made in traditional molecular-thermodynamic modeling. In the CS-MT model, two separate free-energy contributions to the hydrophobic driving force are computed. The first contribution, gdehydr, is the free-energy change associated with the dehydration of each surfactant group upon micelle formation. The second contribution, ghydr, is the change in the hydration free energy of each surfactant group upon micelle formation. To enable the straightforward estimation of gdehydr and ghydr in the case of nonionic surfactants, a number of simplifying approximations were made. Although the CS-MT model can be used to predict a variety of micellar solution properties including the micelle shape, size, and composition, the critical micelle concentration (CMC) was selected for prediction and comparison with experimental CMC data because it depends exponentially on the free energy of micelle formation, and as such, it provides a stringent quantitative test with which to evaluate the predictive accuracy of the CS-MT model. Reasonable agreement between the CMCs predicted by the CS-MT model and the experimental CMCs was obtained for octyl glucoside (OG), dodecyl maltoside (DM), octyl sulfinyl ethanol (OSE), decyl methyl sulfoxide (C10SO), decyl dimethyl phosphine oxide (C10PO), and decanoyl-n-methylglucamide (MEGA-10). For five of these surfactants, the CMCs predicted using the CS-MT model were closer to the experimental CMCs than the CMCs predicted using the traditional molecular-thermodynamic (MT) model. In addition, CMCs predicted for mixtures of C10PO and C10SO using the CS-MT model were significantly closer to the experimental CMCs than those predicted using the traditional MT model. For dodecyl octa(ethylene oxide) (C12E8), the CMC predicted by the CS-MT model was not in good agreement with the experimental CMC and with the CMC predicted by the traditional MT model, because the simplifying approximations made to estimate gdehydr and ghydr in this case were not sufficiently accurate. Consequently, we recommend that these simplifying approximations only be used for nonionic surfactants possessing relatively small, non-polymeric heads. For MEGA-10, which is the most structurally complex of the seven nonionic surfactants modeled, the CMC predicted by the CS-MT model (6.55 mM) was found to be in much closer agreement with the experimental CMC (5 mM) than the CMC predicted by the traditional MT model (43.3 mM). Our results suggest that, for complex, small-head nonionic surfactants where it is difficult to accurately quantify the hydrophobic driving force for micelle formation using the traditional MT modeling approach, the CS-MT model is capable of making reasonable predictions of aqueous micellization behavior.

Titration of mixed micelles containing a pH-sensitive surfactant and conventional (pH-Insensitive) surfactants: a regular solution theory modeling approach.

We present a thermodynamic theory to model the hydrogen-ion titration of mixed micelles containing a pH-sensitive surfactant and any number of conventional (pH-insensitive) surfactants. In particular, a simple expression is derived for the pKm, a parameter analogous to the pKa of simple acids, which describes the deprotonation equilibrium of the micellized pH-sensitive surfactant. The pseudophase approximation and regular solution theory (RST) are used to relate the pKm to (1) the pKa of the surfactant monomers, (2) the critical micelle concentrations (cmc's) of the protonated and deprotonated forms of the pH-sensitive surfactant, (3) the composition of the mixed micelle, and (4) parameters characterizing pairwise interactions between the surfactant molecules in the mixed micelle. Micellar titrations can be used to determine the magnitude of these interaction parameters. Conversely, knowledge of the cmc's and the interaction parameters allows the prediction of the pKm, which can then be used to calculate the micelle composition and surface charge as a function of solution pH. In addition, we have found that, in the context of RST, multicomponent surfactant mixtures are equivalent to a binary surfactant mixture of the pH-sensitive surfactant and a single effective surfactant whose interactions with the pH-sensitive surfactant are an average of those in the multicomponent surfactant mixture. We also discuss the experimental uncertainty in the pKm measurements. To account for the increased uncertainty in the pKm data at extreme micelle compositions, a weighted regression is proposed for the analysis of experimental titration data characterized by widely varying uncertainties. The theory presented here is validated using micellar titration data from the literature for several pH-sensitive surfactants in solutions containing 0.1 M salt. In most cases, the parameters extracted from an analysis of the titration data agree with the cmc and interaction parameters obtained by other means. One notable exception is the surfactant tetradecyldimethylamine oxide (C14DAO), which appears to have concentration-dependent interactions due to extensive growth of cylindrical micelles. Micellar titrations were also conducted on binary surfactant mixtures containing the pH-sensitive surfactant dodecyldimethylamine oxide (C12DAO) and either the cationic surfactant dodecyltrimethylammonium bromide (C12TAB) or the nonionic surfactant dodecyl octa(ethylene oxide) (C12E8). The theory provides a reasonable description of the experimental titration data at all surfactant mixing ratios, although a larger discrepancy is found in the C12DAO/C12E8 system, in which C12E8 interacts preferentially with the protonated, cationic form of C12DAO. Interestingly, C12TAB was also observed to interact preferentially with the protonated, cationic form of C12DAO, although the preference is much weaker than that in the C12DAO/C12E8 system.

Molecular-thermodynamic theory of micellization of pH-sensitive surfactants.

A predictive, molecular-thermodynamic theory is developed to model the micellization of pH-sensitive surfactants. The theory combines a molecular-thermodynamic description of micellization in binary surfactant mixtures with the protonation equilibrium of the surfactant monomers. The thermodynamic component of the theory models the pH-mediated equilibrium between micelles, surfactant monomers, and counterions. These counterions may originate from the surfactant or from added salt, acid, or base. The molecular component of the theory models the various contributions to the free energy of micellization, which corresponds to the free-energy change associated with forming a mixed micelle from the protonated and deprotonated forms of the surfactant and from the bound counterions. The free energy of micellization includes hydrophobic, interfacial, packing, steric, electrostatic, and entropic contributions, which are all calculated molecularly. The theory also requires knowledge of the surfactant molecular structure and the solution conditions, including the temperature and the amount of any added salt, acid, or base. To account for the pH sensitivity of the surfactant, the theory requires knowledge of the surfactant monomer equilibrium deprotonation constant (pK1), which may be obtained from experimental titration data obtained below the critical micelle concentration (cmc). The theory can be utilized to predict the equilibrium micelle and solution properties, including the cmc, the micelle composition, the micelle shape and aggregation number, the solution pH, and the micelle deprotonation equilibrium constant (pKm). Theoretical predictions of the cmc, the micelle aggregation number, and the pKm compare favorably with the available experimental data for alkyldimethylamine oxide surfactants. This class of pH-sensitive surfactants exhibits a form of self-synergy, which has previously been attributed to hydrogen-bond formation at the micelle interface. Instead, we show that much of the observed synergy is related to the electrostatic contribution to the free energy of micellization. Although we do not explicitly include hydrogen bonding in the molecular model of micellization, we briefly discuss how it may be incorporated and its anticipated effect on the predicted micellization behavior.

Modeling counterion binding in ionic-nonionic and ionic-zwitterionic binary surfactant mixtures.

A predictive molecular-thermodynamic theory is developed to model the effect of counterion binding on micellar solution properties of binary surfactant mixtures of ionic and nonionic (or zwitterionic) surfactants. The theory combines a molecular-thermodynamic description of micellization in binary surfactant mixtures with a recently developed model of counterion binding to single-component ionic surfactant micelles. The thermodynamic component of the theory models the equilibrium between the surfactant monomers, the counterions, and the mixed micelles. The molecular component of the theory models the various contributions to the free-energy change associated with forming a mixed micelle from ionic surfactants, nonionic (or zwitterionic) surfactants, and bound counterions (referred to as the free energy of mixed micellization). Specifically, the various molecular contributions to the free energy of mixed micellization model the underlying physics associated with the assembly of, and the interactions between, the surfactant polar heads, the surfactant nonpolar tails, and the bound counterions. Utilizing known structural characteristics of the surfactants and the counterions, along with the solution conditions, the free energy of mixed micellization is minimized to predict various optimal micelle characteristics, including the degree of counterion binding, the micelle composition, and the micelle shape and size. These predicted optimal micelle characteristics are then used to predict the critical micelle concentration (cmc) and the average micelle aggregation number. Our predictions of the degree of counterion binding, the cmc, and the average micelle aggregation number show good agreement with available experimental results from the literature for several binary surfactant mixtures. In addition, the theory is used to shed light on the relationship between the micelle composition, counterion binding and ion condensation, and the micelle shape transition.