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PubMedDate not supplied

E-state modeling of dopamine transporter binding. Validation of the model for a small data set.

Data for 25 tropane analogues binding to the dopamine transporter were modeled using E-state molecular structure descriptors. Both E-state and hydrogen E-state descriptors appear in the model in both atom-level and atom-type descriptors. A statistically satisfactory four-variable model is obtained, and structure interpretation is given for each variable, emphasizing substituent influence on nonpolar parts of the molecule as well as the role of hydrogen bonding. A leave-group-out approach to model validation is presented in which each observation is removed from the data set three times in random groups of 20% of the whole data set. The average of the resulting predicted values constitutes consensus predictions for these data and supports the claim that the E-state model may be useful for prediction of pIC50 values for new compounds.

Carrier Proteins↗

PubMedDate not supplied

Model reduction in the computational modeling of reaction systems.

The underlying assumption for most lumping techniques is that the reduced models must be valid for the entire composition space. This is a harsh requirement that often limits the models that are generated. The scheme that is presented here uses the inherent structure of reaction systems to divide the composition space into regions. Within each region, the order-of-magnitude relationships that exist between terms in the rate equations are used to systematically reduce the order and coupling of the model. The full system is then described through piecewise combination of these simpler, region-specific models. Although these reduced models are based on assumptions that make them invalid globally, they are accurate within the regions for which they have been crafted.

Algorithms↗

PubMed2001

A distributed reactivity model for sorption by soils and sediments. 14. Characterization and modeling of phenanthrene desorption rates.

Rates and extents of phenanthrene desorption were studied for more than 250 days as functions of sorbent type, initial loading level, and aging. Apparent first-order desorption rate constants for the slowly desorbing fraction were found to (i) range from 0.00086 to 0.148 days-1 for geosorbents that contain geologically mature kerogen and less rigid humic-type soil organic matter, respectively, (ii) decrease by as much as an order of magnitude with decreasing initial sorbed solid-phase phenanthrene concentration, (iii) decrease by a factor of 2 with increasing aging time for a humic topsoil but remain unaffected by aging time beyond 3 months for a shale, and (iv) be 1-2 orders of magnitude lower than rate constants for the rapidly desorbing phenanthrene fractions for any given contaminated sample. Six models were used to fit the desorption rate data. Biphasic diffusion and biphasic first-order models with three fitting parameters possess broad utility and are potentially useful in a variety of environmental applications. Disadvantages of a five-parameter triphasic first-order desorption model, a two-parameter gamma-function model, and a one- or two-parameter pore diffusion model are also discussed.

Adsorption↗

PubMed2001

Modeling the active sites in metalloenzymes. 3. Density functional calculations on models for [Fe]-hydrogenase: structures and vibrational frequencies of the observed redox forms and the reaction mechanism at the Diiron Active Center.

Optimized structures for the redox species of the diiron active site in [Fe]-hydrogenase as observed by FTIR and for species in the catalytic cycle for the reversible H(2) oxidation have been determined by density-functional calculations on the active site model, [(L)(CO)(CN)Fe(mu-PDT)(mu-CO)Fe(CO)(CN)(L')](q)(L = H(2)O, CO, H(2), H(-); PDT = SCH(2)CH(2)CH(2)S, L' = CH(3)S(-), CH(3)SH; q = 0, 1-, 2-, 3-). Analytical DFT frequencies on model complexes (mu-PDT)Fe(2)(CO)(6) and [(mu-PDT)Fe(2)(CO)(4)(CN)(2)](2)(-) are used to calibrate the calculated CN(-) and CO frequencies against the measured FTIR bands in these model compounds. By comparing the predicted CN(-) and CO frequencies from DFT frequency calculations on the active site model with the observed bands of D. vulgaris [Fe]-hydrogenase under various conditions, the oxidation states and structures for the diiron active site are proposed. The fully oxidized, EPR-silent form is an Fe(II)-Fe(II) species. Coordination of H(2)O to the empty site in the enzyme's diiron active center results in an oxidized inactive form (H(2)O)Fe(II)-Fe(II). The calculations show that reduction of this inactive form releases the H(2)O to provide an open coordination site for H(2). The partially oxidized active state, which has an S = (1)/(2) EPR signal, is an Fe(I)-Fe(II) species. Fe(I)-Fe(I) species with and without bridging CO account for the fully reduced, EPR-silent state. For this fully reduced state, the species without the bridging CO is slightly more stable than the structure with the bridging CO. The correlation coefficient between the predicted CN(-) and CO frequencies for the proposed model species and the measured CN(-) and CO frequencies in the enzyme is 0.964. The proposed species are also consistent with the EPR, ENDOR, and Mössbauer spectroscopies for the enzyme states. Our results preclude the presence of Fe(III)-Fe(II) or Fe(III)-Fe(III) states among those observed by FTIR. A proposed reaction mechanism (catalytic cycle) based on the DFT calculations shows that heterolytic cleavage of H(2) can occur from (eta(2)-H(2))Fe(II)-Fe(II) via a proton transfer to "spectator" ligands. Proton transfer to a CN(-) ligand is thermodynamically favored but kinetically unfavorable over proton transfer to the bridging S of the PDT. Proton migration from a metal hydride to a base (S, CN, or basic protein site) results in a two-electron reduction at the metals and explains in part the active site's dimetal requirement and ligand framework which supports low-oxidation-state metals. The calculations also suggest that species with a protonated Fe-Fe bond could be involved if the protein could accommodate such species.

Binding Sites↗

PubMed2006

Modeling of protein interactions with surface-grafted charged polymers. Correlations between statistical molecular modeling and a mean field approach.

Ion exchange media involving charge groups attached to flexible polymers are widely used for protein purification. Such media often provide enhanced target protein purity and yield. Yet, little is understood about protein interaction with such media at the molecular level, or how different media architectures might affect separation performance. To gain a better understanding of such adsorptive systems, statistical mechanical perturbation calculations, utilizing a Debye-Hückel potential, were performed on surface-grafted charged polymers and their interaction with model proteins. The studied systems were weakly charged, and the polymers were linear and relatively short (degree of polymerization is 30). Segment distributions from the surface were also determined. The interaction of spherical model protein particles of 12-30 A radius were investigated with respect to polymer grafting density, distance from matrix surface, protein charge, and ionic strength. The partitioning coefficient of the model proteins was determined for different distances from the surface. An empirical mean field theory that scales the entropy of the protein with the square of the protein radius correlates well to Monte Carlo statistical modeling results. Upon adsorption to the polymer layers, the model proteins exhibit a critical surface charge density that is proportional to the ionic strength, independent of the grafting density, and appears to be a fundamental determinant of protein adsorption. Partitioning of protein-like nanoparticles to the charged polymer surface is only favored above the particle critical charge density.

Ions↗

PubMed2000

Intrinsic priors for model selection using an encompassing model with applications to censored failure time data.

In Bayesian model selection or testing problems one cannot utilize standard or default noninformative priors, since these priors are typically improper and are defined only up to arbitrary constants. Therefore, Bayes factors and posterior probabilities are not well defined under these noninformative priors, making Bayesian model selection and testing problems impossible. We derive the intrinsic Bayes factor (IBF) of Berger and Pericchi (1996a, 1996b) for the commonly used models in reliability and survival analysis using an encompassing model. We also derive proper intrinsic priors for these models, whose Bayes factors are asymptotically equivalent to the respective IBFs. We demonstrate our results in three examples.

Bayes Theorem↗

PubMed1997

A model with separate hepato-portal compartment ("first-pass" model): fitting to plasma concentration-time profiles in humans.

PURPOSE: To demonstrate the value of "first-pass" pharmacokinetic models (FPMs) in which the hepato-portal (HP) system is kinetically separated from the central compartment in fitting pharmacokinetic data obtained after intravenous (IV) and oral administration. METHODS: Plasma concentration-time profiles of an investigational drug obtained in six healthy subjects each received 4 mg as an intravenous (IV) bolus dose and 10 mg as an oral solution served as a real data example. The common three- and four-compartment models with the first-order absorption and lag time (3CM and 4CM, respectively) in which HP system is assumed to be part of the central compartment were used as alternative models. We tested also: (i) the sensitivity of the output of FPM to variations in its parameters assuming IV and oral administration; (ii) practical estimability of the FPM parameters by fitting it to 20 simulated noisy data sets; (iii) distinguishability of FPM, 3CM and 4CM by fitting them to the simulated data sets. RESULTS: FPM was shown to give the best fit as compared to 3CM or 4CM in 5 subjects of 6. The sensitivity of FPM was sufficient for the sake of parameter estimation. The "individual" means of parameter estimates obtained after fitting simulated data did not differ significantly from the preselected values. The variance in "individual" estimates was dependent on the sampling frequency. FPM was demonstrated to be distinguishable among relevant models. CONCLUSIONS: FPM is preferable as compared to standard compartmental models for drugs extensively taken up by the intestine and/or the liver, and may have a broad spectrum of applications.

Administration, Oral↗

PubMed1999

Mechanism-based modeling of adaptive changes in the pharmacodynamics of midazolam in the kindling model of epilepsy.

PURPOSE: A mechanism-based model is proposed for the analysis of adaptive changes in the pharmacodynamics of benzodiazepines in vivo. METHODS: The pharmacodynamics of midazolam was studied in the kindling model of experimental epilepsy. Concentration-EEG effect data from kindled rats and their controls were fitted to the operational model of agonism. A stepwise procedure was used, allowing changes in the parameters efficacy (tau) and tissue maximum (Em) either separately or in combination. The results were compared to data obtained in vitro in a brain synaptoneurosomal preparation. RESULTS: The relationship between midazolam concentration and EEG effect was non-linear. In kindled rats the maximum EEG effect was reduced by 27+/-8.3 microV from the original value of 94+/-4.4 microV. Analysis on the basis of the operational model of agonism showed that this decrease could be explained by a difference in the parameter system maximum (Em) rather than efficacy (tau). In the in vitro receptor binding assay no changes in density, affinity or functionality of the benzodiazepine receptor were observed, consistent with the lack of a change in efficacy (tau). CONCLUSIONS: The operational model of agonism provides a mechanistic basis to characterise adaptive changes in the pharmacodynamics of midazolam.

Adaptation, Physiological↗

PubMed1998

Modeling of spreading cortical depression using a realistic head model.

Barkley and colleagues in 1990 reported large amplitude waves (LAWs) in time series magnetoencephalography (MEG) recordings from migraine patients and inferred that these LAWs arose from spreading cortical depression (SCD). SCD propagates slowly across the cortex in all species in which it has been observed. Previously, we reported that LAWs could be simulated and compared with the recorded signals using the four-sphere model (Wijesinghe and Tepley 1997). We showed that LAWs could arise from the propagation of SCD across a sulcus. In this paper, we model LAWs using a realistically shaped head model based on magnetic resonance images (MRI) (Roth et al. 1993). Simulated signals using this model are similar to the recorded signals. In this model, current dipoles represent the excitable neurons in the cortex and magnetic fields created by these individual dipoles are calculated. The magnetic field arising from the excited area of cortex is obtained by summing the fields due to these individual dipoles.

Brain Mapping↗

PubMed1997

Modeling of nucleotide binding domains of ABC transporter proteins based on a F1-ATPase/recA topology: structural model of the nucleotide binding domains of the cystic fibrosis transmembrane conductance regulator (CFTR).

Members of the ABC transporter superfamily contain two nucleotide binding domains. To date, the three dimensional structure of no member of this super-family has been elucidated. To gain structural insight, the known structures of several other nucleotides binding proteins can be used as a framework for modeling these domains. We have modeled both nucleotide binding domains of the protein CFTR (Cystic Fibrosis Transmembrane Conductance Regulator) using the two similar domains of mitochondrial F1-ATPase. The models obtained, provide useful insights into the putative functions of these domains and their possible interaction as well as a rationale for the basis of Cystic Fibrosis causing mutations. First, the two nucleotide binding domains (folds) of CFTR are each predicted to span a 240-250 amino acid sequence rather than the 150-160 amino acid sequence originally proposed. Second, the first nucleotide binding fold, is predicted to catalyze significant rates of ATP hydrolysis as a catalytic base (E504) resides near the y phosphate of ATP. This prediction has been verified experimentally [Ko, Y.H., and Pedersen, P.L. (1995) J. Biol. Chem. 268, 24330-24338], providing support for the model. In contrast, the second nucleotide binding fold is predicted at best to be a weak ATPase as the glutamic acid residue is replaced with a glutamine. Third, F508, which when deleted causes approximately 70% of all cases of cystic fibrosis, is predicted to lie in a cleft near the nucleotide binding pocket. All other disease causing mutations within the two nucleotide binding domains of CFTR either reside near the Walker A and Walker B consensus motifs in the heart of the nucleotide binding pocket, or in the C motif which lies outside but near the nucleotide binding pocket. Finally, the two nucleotide binding domains of CFTR are predicted to interact, and in one of the two predicted orientations, F508 resides near the interface. This is the first report where both nucleotide binding domains of an ABC transporter and their putative domain-domain interactions have been modeled in three dimensions. The methods and the template used in this work can be used to analyze the structures and function of the nucleotide binding domains of all other members of the ABC transporter super-family.

ATP-Binding Cassette Transporters↗

PubMed1998

Pharmacokinetic-pharmacodynamic modeling of tolmetin antinociceptive effect in the rat using an indirect response model: a population approach.

The relationship between the pharmacokinetics and the antinociceptive effect of tolmetin was characterized by an indirect model using a population approach. Animals received an intra-articular injection of uric acid in the right hindlimb to induce its dysfunction. Once dysfunction was complete, rats received an oral tolmetin dose of 1, 3.2, 10, 31.6, 56.2 or 100 mg/kg and antinociceptive effect and blood tolmetin concentration were simultaneously evaluated. Tolmetin produced a dose-dependent recovery of functionality, which was not directly related to blood concentration. An inhibitory indirect response model was used based on these response patterns and the fact that tolmetin reduced nociception by inhibiting prostaglandin synthesis. Pharmacokinetic (PK) and pharmacodynamic (PD) data were simultaneously fitted using nonlinear mixed effects modeling (NONMEM) to the one-compartment model and indirect response model. The individual time courses of the response were described using Bayesian analysis with population parameters as a priori estimates. There was good agreement between the predicted and observed data. Population analysis yielded a maximal inhibition of the nociceptive response of 76% and an IC50 of 9.22 micrograms/ml. This IC50 is similar to that for tolmetin-induced prostaglandin synthesis inhibition in vitro (3.0 micrograms/ml). The present results demonstrate that mechanism-based PK-PD analysis using a population approach is useful for quantitating individual responses as well as reflecting the actual mechanism of action of a given drug in vivo.

Animals↗

PubMed2000

Hydrophilic matrices for controlled drug delivery: an improved mathematical model to predict the resulting drug release kinetics (the "sequential layer" model).

PURPOSE: The aims of this study were (i) to elucidate the transport mechanisms involved in drug release from hydrophilic matrices; and (ii) to develop an improved mathematical model allowing quantitative predictions of the resulting release kinetics. METHODS: Our previously presented model has been substantially modified, by adding: (i) inhomogeneous swelling; (ii) poorly water-soluble drugs; and (iii) high initial drug loadings. The validity of the improved model has been tested experimentally using hydroxypropyl methylcellulose (HPMC)-matrices, containing either a poorly or a freely water-soluble drug (theophylline or chlorpheniramine maleate) at various initial loadings in phosphate buffer pH 7.4 and 0.1 N HCl, respectively. RESULTS: By overcoming the assumption of homogeneous swelling we show that the agreement between theory and experiment could be significantly improved. Among others, the model could describe quantitatively even the very complex effect on the resulting relative release rates (first slowing down, then accelerating drug release) observed when increasing the initial loading of poorly water-soluble drugs. CONCLUSIONS: The practical benefit of this work is an improved design model that can be used to predict accurately the required composition and dimensions of drug-loaded hydrophilic matrices in order to achieve desired release profiles, thus facilitating the development of new pharmaceutical products.

Chemistry, Pharmaceutical↗

PubMed2004

Formulation of the CBC-model for modelling the contaminants and footprints in natural attenuation of BTEX.

This paper provides the details of the Coupled Biological and Chemical (CBC) model for representing in situ bioremediation of BTEX. The CBC model contains novel features that allow it to comprehensively track the footprints of BTEX bioremediation, even when the fate of those footprints is confounded by abiotic reactions and complex interactions among different kinds of microorganisms. To achieve this comprehensive tracking of all the footprints, the CBC model contains important new biological features and key abiotic reactions. The biological module of the CBC-model includes these important new aspects: (1) it separates BTEX fermentation from methanogenesis, (2) it explicitly includes biomass as a sink for electrons and carbon, (3) it has different growth rates for each biomass type, and (4) it includes inhibition of the different reactions by other electron acceptors and by sulfide toxicants. The chemical module of the CBC-model includes abiotic reactions that affect the footprints of the biological reactions. In particular, the chemical module describes the precipitation/dissolution of CaCO3, Fe2O3, FeS, FeS2, and S degrees. The kinetics for the precipitation/dissolution reactions follow the critical review in Maurer & Rittmann (2004).

Biodegradation, Environmental↗

PubMed1998

Top-down, bottom-up, and horizontal models: the direction of causality in multidimensional, hierarchical self-concept models.

A new structural equation modeling approach to questions of the direction of causal flow between global and specific multidimensional measures of self-concept (SC) in two 2-wave, longitudinal studies demonstrated that (a) higher order factors were unable to explain relations among first-order factors at Time 1 (T1), at Time 2 (T2), or between T1 and T2; (b) T1 global SC had little effect on specific SC factors at T2 (a top-down model), but specific factors at T1 had even less effect on T2 global SC (a bottom-up model); and (c) many specific factors were more stable than global factors, but higher order factors were most stable. Results provide little support for top-down, bottom-up, or reciprocal models, instead arguing for a horizontal model in which each T2 SC factor is primarily a function of the matching T1 SC. This casts further doubt on the usefulness of hierarchical representations of SC.

Achievement↗

PubMed2003

Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling.

R. M. Baron and D. A. Kenny (1986; see record 1987-13085-001) provided clarion conceptual and methodological guidelines for testing mediational models with cross-sectional data. Graduating from cross-sectional to longitudinal designs enables researchers to make more rigorous inferences about the causal relations implied by such models. In this transition, misconceptions and erroneous assumptions are the norm. First, we describe some of the questions that arise (and misconceptions that sometimes emerge) in longitudinal tests of mediational models. We also provide a collection of tips for structural equation modeling (SEM) of mediational processes. Finally, we suggest a series of 5 steps when using SEM to test mediational processes in longitudinal designs: testing the measurement model, testing for added components, testing for omitted paths, testing the stationarity assumption, and estimating the mediational effects.

Cross-Sectional Studies↗

PubMed2004

Modeling associative recognition: a comparison of two-high-threshold, two-high-threshold signal detection, and mixture distribution models.

A 2-high-threshold signal detection (HTSDT) model, a mixture distribution (SON) model, and 2-high-threshold (HT) models with responses distributed over 1 or several response categories were fit to results of 6 experiments from 2 studies on associative recognition: R. Kelley and J. T. Wixted (2001) and A. P. Yonelinas (1997). HTSDT assumes that associative recognition is based on conscious recollection and familiarity assessment, whereas according to SON and HT, associative information results in a shift of familiarity. The modeling results cast doubt on the prominent role of conscious recollection, and as far as models are valid, parameter estimation suggests 2 processes in associative recognition: a shift in familiarity that is due to associative information and the determination of the source of familiarity of pairs.

Association↗

PubMed2005

Multilevel modeling of two cyclical processes: extending differential structural equation modeling to nonlinear coupled systems.

The authors present a dynamical multilevel model that captures changes over time in the bidirectional, potentially asymmetric influence of 2 cyclical processes. S. M. Boker and J. Graham's (1998) differential structural equation modeling approach was expanded to the case of a nonlinear coupled oscillator that is common in bimanual coordination studies in which participants swing hand-held pendulums but is also applicable to social systems in general. The authors' nonlinear coupled oscillator model decomposed the fluctuations into a competitive component, unique to each individual variable, and a cooperative component that captured bidirectional influence. The authors' model also generated an index of the symmetry/asymmetry of bidirectional influence. Together, the models are useful quantitative tools for the study of interacting, changing processes.

Humans↗

PubMed2006

Information-theoretic latent distribution modeling: distinguishing discrete and continuous latent variable models.

Distinguishing between discrete and continuous latent variable distributions has become increasingly important in numerous domains of behavioral science. Here, the authors explore an information-theoretic approach to latent distribution modeling, in which the ability of latent distribution models to represent statistical information in observed data is emphasized. The authors conclude that loss of statistical information with a decrease in the number of latent values provides an attractive basis for comparing discrete and continuous latent variable models. Theoretical considerations as well as the results of 2 Monte Carlo simulations indicate that information theory provides a sound basis for modeling latent distributions and distinguishing between discrete and continuous latent variable models in particular.

Behavioral Sciences↗