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PubMed1999

Empirical versus mechanistic modelling: comparison of an artificial neural network to a mechanistically based model for quantitative structure pharmacokinetic relationships of a homologous series of barbiturates.

The aim of the current study was to compare the predictive performance of a mechanistically based model and an empirical artificial neural network (ANN) model to describe the relationship between the tissue-to-unbound plasma concentration ratios (Kpu's) of 14 rat tissues and the lipophilicity (LogP) of a series of nine 5-n-alkyl-5-ethyl barbituric acids. The mechanistic model comprised the water content, binding capacity, number of the binding sites, and binding association constant of each tissue. A backpropagation ANN with 2 hidden layers (33 neurons in the first layer, 9 neurons in the second) was used for the comparison. The network was trained by an algorithm with adaptive momentum and learning rate, programmed using the ANN Toolbox of MATLAB. The predictive performance of both models was evaluated using a leave-one-out procedure and computation of both the mean prediction error (ME, showing the prediction bias) and the mean squared prediction error (MSE, showing the prediction accuracy). The ME of the mechanistic model was 18% (range, 20 to 57%), indicating a tendency for overprediction; the MSE is 32% (range, 6 to 104%). The ANN had almost no bias: the ME was 2% (range, 36 to 64%) and had greater precision than the mechanistic model, MSE 18% (range, 4 to 70%). Generally, neither model appeared to be a significantly better predictor of the Kpu's in the rat.

Algorithms↗

PubMed2005

Organolanthanide-mediated intermolecular hydroamination of 1,3-dienes: mechanistic insights from a computational exploration of diverse mechanistic pathways for the stereoselective hydroamination of 1,3-butadiene with a primary amine supported by an ansa-neodymocene-based catalyst.

The complete catalytic reaction course for the organolanthanide-mediated intermolecular hydroamination of 1,3-butadiene and n-propylamine by an archetypical [Me2Si(eta5-Me4C5)2NdCH(SiMe3)2] precatalyst was critically scrutinized by employing a reliable gradient-corrected DFT method. A free-energy profile of the overall reaction is presented that is based on the thorough characterization of all crucial elementary steps for a tentative catalytic cycle. A computationally verified, revised mechanistic scenario is proposed which is consistent with the experimentally derived empirical rate law and accounts for crucial experimental observations. It involves kinetically mobile reactant association/dissociation equilibria and facile, reversible intermolecular diene insertion into the Nd-amido bond, linked to turnover-limiting protonolysis of the eta3-butenyl-Nd functionality. The computationally predicted effective kinetics (Delta(tot) = 11.3 kcal mol(-1), Delta(tot) = -35.7 e.u.) are in reasonably good agreement with experimental data for the thoroughly studied hydroamination of alkynes. The thermodynamic and kinetic factors that determine the almost complete regio- and stereoselectivity of the mechanistically diverse intermolecular 1,3-diene hydroamination have been unraveled. The present computational study complements experiments because it allows, first, a more detailed understanding and a consistent rationalization of the experimental results for the hydroamination of 1,3-dienes and primary amines and, second, enhances the insights into general mechanistic aspects of organolanthanide-mediated intermolecular hydroamination.

Journal Article↗

PubMed1986

Determination of the upper and lower limits of the mechanistic stoichiometry of incompletely coupled fluxes. Stoichiometry of incompletely coupled reactions.

A rationale is formulated for the design of experiments to determine the upper and lower limits of the mechanistic stoichiometry of any two incompletely coupled fluxes J1 and J2. Incomplete coupling results when there is a branch at some point in the sequence of reactions or processes coupling the two fluxes. The upper limit of the mechanistic stoichiometry is given by the minimum value of dJ2/dJ1 obtained when the fluxes are systematically varied by changes in steps after the branch point. The lower limit is given by the maximum value of dJ2/dJ1 obtained when the fluxes are varied by changes in steps prior to the branch point. The rationale for determining these limits is developed from both a simple kinetic model and from a linear nonequilibrium thermodynamic treatment of coupled fluxes, using the mechanistic approach [Westerhoff, H. V. & van Dam, K. (1979) Curr. Top. Bioenerg. 9, 1-62]. The phenomenological stoichiometry, the flux ratio at level flow and the affinity ratio at static head of incompletely coupled fluxes are defined in terms of mechanistic conductances and their relationship to the mechanistic stoichiometry is discussed. From the rationale developed, experimental approaches to determine the mechanistic stoichiometry of mitochondrial oxidative phosphorylation are outlined. The principles employed do not require knowledge of the pathway or the rate of transmembrane leaks or slippage and may also be applied to analysis of the stoichiometry of other incompletely coupled systems, including vectorial H+/O and K+/O translocation coupled to mitochondrial electron transport.

Biological Transport↗

PubMed2006

Role of mechanistically-based pharmacokinetic/pharmacodynamic models in drug development : a case study of a therapeutic protein.

BACKGROUND AND OBJECTIVE: This case study describes the pharmacokinetic and pharmacodynamic modelling undertaken during the development programme for UK-279,276 (neutrophil inhibitory factor), focusing on the transition from early empirical-based models to a final mechanistic-based model. UK-279,276 binds to the CD11b/CD18 (MAC-1) on neutrophils and was under development for the treatment of ischaemic stroke. METHODS: The aims, data, models, results and value-to-drug development process across four stages of model development are described: (i) the validation of the pharmacokinetic assay; (ii) the development and application of an empirical patient pharmacokinetic/pharmacodynamic model; (iii) the development of a mechanistic-based model to bridge between patients and healthy volunteers; and (iv) propagation of the stage III model to a large efficacy study. The analyses utilised available concentration measurements (stages I-IV), CD11b receptor occupancy data (stages I-III) and neutrophil count data (stages III-IV) from three healthy volunteers (study 1, n=51; study 2, n=31; study 4, n=15) and two patient studies (study 3, n=169; study 5, n=992). In studies 1-4, subjects received placebo or between three and six doses of UK-279,276 covering a range of 0.006 and 1.5 mg/kg as a single 15-minute intravenous infusion. In study 5, subjects received placebo or one of 15 possible doses of UK-279,276 (10--20mg) assigned through adaptive design and administered as a single 15-minute intravenous infusion. All model building was conducted using NONMEM version VI (beta). The empirical pharmacokinetic/pharmacodynamic model developed during stage I was used to demonstrate that the pharmacokinetic assay was measuring biologically active drug. Simulations from the stage II model, developed from study 3, were used in the design of study 5. The model supported the switch to a fixed-dose regimen and the selection of the maximum dose and dosage increments. The common mechanistic-based model developed during stage III was used to support the 'comparability strategy' for UK-279,276 and provided insight into the underlying clearance mechanisms. At stage 4, the prior functionality available with NONMEM was used to successfully propagate the model from stage III in order to analyse the pharmacokinetic data from study 5. The analysis indicated that the exposure in study 5 was consistent with prior data. The role of empirical-based models in providing the learning for future mechanistic model development was highlighted. Similarly, the qualitative and quantitative aspects to knowledge propagation and the ultimate benefits from the development of the mechanistic-based model were demonstrated. While the empirical-based models were used to guide some early drug development decisions for UK-279,276, the development of the mechanistic-based model was valuable in linking the complex pharmacokinetics/pharmacodynamics of UK-279,276 across the phases of drug development.

Adult↗

PubMed2026

Loss of the Mechanistic Target of Rapamycin Complex 1 Causes a Lethal Alpha-1 Antitrypsin Deficiency-Associated Liver Disease.

BACKGROUND & AIMS: SERPINA1 mutations cause retention of the otherwise secreted alpha-1 antitrypsin and lead to the proteotoxic alpha-1 antitrypsin deficiency-related liver disease. As mechanistic target of rapamycin is a key coordinator of proteostasis, we studied its role in alpha-1 antitrypsin deficiency-related liver disease. METHODS: PiZ mice overexpressing the characteristic SERPINA1 mutation were mated with rodents harboring a hepatocyte specific-ablation of the interaction partners regulatory-associated protein of mechanistic target of rapamycin or rapamycin-insensitive companion of mammalian target of rapamycin, corresponding to mechanistic target of rapamycin complexes 1 or 2, or with mice lacking mechanistic target of rapamycin. Serum proteomics, liver bulk proteomics, spatial proteomics, and metabolomics were applied to characterize molecular and metabolic alterations. RESULTS: At 2 months of age, PiZ-mTORΔhep and PiZ-RaptorΔhep but not PiZ-RictorΔhep mice showed signs of increased liver injury and mortality despite diminished hepatic alpha-1 antitrypsin accumulation. PiZ-RaptorΔhep animals displayed increased levels of the proapoptotic protein C/EBP homologous protein, but C/EBP homologous protein ablation did not rescue the phenotype. Serum proteomics revealed no signs of advanced synthetic liver failure but immature hepatocellular products. Liver bulk proteomics and small metabolite measurement demonstrated a metabolic reprogramming of PiZ-RaptorΔhep mice. Spatial proteomics revealed alterations in liver zonation with increased ammonia levels as the likely cause of death in PiZ-RaptorΔhep animals. CONCLUSIONS: In summary, in alpha-1 antitrypsin deficiency-related proteotoxic liver injury, regulatory-associated protein of mechanistic target of rapamycin preserves a liver zonation, thereby protecting from lethal metabolic dysregulation.

Animals↗

PubMed1986

The upper and lower limits of the mechanistic stoichiometry of mitochondrial oxidative phosphorylation. Stoichiometry of oxidative phosphorylation.

Determination of the intrinsic or mechanistic P/O ratio of oxidative phosphorylation is difficult because of the unknown magnitude of leak fluxes. Applying a new approach developed to overcome this problem (see our preceding paper in this journal), the relationships between the rate of O2 uptake [( Jo)3], the net rate of phosphorylation (Jp), the P/O ratio, and the respiratory control ratio (RCR) have been determined in rat liver mitochondria when the rate of phosphorylation was systematically varied by three specific means. (a) When phosphorylation is titrated with carboxyatractyloside, linear relationships are observed between Jp and (Jo)3. These data indicate that the upper limit of the mechanistic P/O ratio is 1.80 for succinate and 2.90 for 3-hydroxybutyrate oxidation. (b) Titration with malonate or antimycin yields linear relationships between Jp and (Jo)3. These data give the lower limit of the mechanistic P/O ratio of 1.63 for succinate and 2.66 for 3-hydroxybutyrate oxidation. (c) Titration with a protonophore yields linear relationships between Jp, (Jo)3, and (Jo)4 and between P/O and 1/RCR. Extrapolation of the P/O ratio to 1/RCR = 0 yields P/O ratios of 1.75 for succinate and 2.73 for 3-hydroxybutyrate oxidation which must be equal to or greater than the mechanistic stoichiometry. When published values for the H+/O and H+/ATP ejection ratios are taken into consideration, these measurements suggest that the mechanistic P/O ratio is 1.75 for succinate oxidation and 2.75 for NADH oxidation.

Adenosine Triphosphate↗

PubMed1994

Use of mechanistic models to estimate low-dose cancer risks.

The utility of mechanistic models of cancer for predicting cancer risks at low doses is examined. Based upon a general approximation to the dose-response that is valid at low doses, it is shown that at low doses the dose-response predicted by a mechanistic model is a linear combination of the dose-responses for each of the physiological parameters in the model that are affected by exposure. This demonstrates that, unless the mechanistic model provides a theoretical basis for determining the dose-responses for these parameters, the extrapolation of risks to low doses using a mechanistic model is basically "curve fitting," just as is the case when extrapolating using statistical models. This suggests that experiments to generate data for use in mechanistic models should emphasize measuring the dose-response for dose-related parameters as accurately as possible and at the lowest feasible doses.

Carcinogens↗

PubMed1990

A survey of students' notions of body function as teleologic or mechanistic.

The objectives of this study were to determine 1) the relative degrees to which students' notions of physiological functions are teleologic or mechanistic in nature, 2) whether these notions differ between students in elementary and advanced-level physiology courses, and 3) whether the degree of teleologic vs. mechanistic thinking can be modified by direct discussion of this topic. A questionnaire that determined whether students thought about body functions in a teleologic (why) or mechanistic (how) manner was administered to the following categories of students: 1) a class of high school biology students, 2) classes of students taking elementary college-level physiology courses, and 3) college students in advanced physiology courses. Overall, there was an average 61% teleologic response among the various classes, and differences between the classes were not statistically significant (P greater than 0.05). To address objective 3, one of the classes was presented the questionnaire after being given a lecture on teleology vs. mechanistic approaches to body function. The average teleological response of this class was only 12%, a value significantly lower in comparison, by a one-way analysis of variance, to any of the other groups (P less than 0.0001). These results indicate that the students have a strong tendency to think of body functions in teleological terms and that this tendency can be modified on a short-term basis by a direct discussion (by an instructor) of teleologic vs. mechanistic thinking.

Africa↗

PubMed1996

Mechanistic considerations in the evaluation of chemopreventive data.

Possible chemopreventive mechanisms include carcinogen-blocking activities, antioxidant/anti-inflammatory activities and antiproliferation/antiprogression activities. Carcinogen-blocking activities encompass inhibition of carcinogen uptake, inhibition of carcinogen formation or activation, deactivation or detoxification of carcinogens, prevention of carcinogen binding to DNA, and enhancement of the level or fidelity of DNA repair. Antioxidant/anti-inflammatory activities include scavenging of reactive electrophiles and oxygen radicals, and inhibition of arachidonic acid metabolism. Antiproliferation/antiprogression activities comprise modulation of signal transduction, modulation of hormonal and growth factor activity, inhibition of aberrant oncogene activity, inhibition of polyamine metabolism, induction of terminal differentiation, restoration of immune responses, enhancement of intercellular communication, restoration of tumour suppressor function, induction of apoptosis, telomerase inhibition, correction of DNA methylation imbalances, inhibition of angiogenesis, inhibition of basement membrane degradation, and activation of antimetastasis genes. In evaluating the potential efficacy of chemopreventive agents several mechanistic parameters are weighed: (1) the number of chemoprevention-related pharmacological activities, (2) the impact of the agent on likely carcinogenesis pathways to the targeted cancer, (3) pharmacodynamics, and (4) specificity for chemopreventive activity compared with interference with normal cellular function. Mechanistic data are important throughout the development process for chemopreventive drugs, and they are particularly important in the earlier phases of identifying promising candidate agents and characterizing efficacy. In vitro mechanistic assays are a first step in evaluating chemopreventive potential. Mechanistic considerations are also useful in defining animal efficacy models and in interpreting the results of assays in these models. Mechanistic data are also applied in designing short-term Phase II clinical chemoprevention trials that use reductions in intermediate biomarkers of cancer rather than cancer incidence as end points. The basis for identifying and evaluating these biomarkers is in understanding carcinogenesis and chemopreventive mechanisms.

Anticarcinogenic Agents↗

PubMed2002

Enzymatic synthesis of amoxicillin: avoiding limitations of the mechanistic approach for reaction kinetics.

A recurrent doubt that occurs to the enzyme-kinetics modeler is, When should I stop adding parameters to my mechanistic model in order to fit a non-conventional behavior? This problem becomes more and more involving when the complexity of the reaction network increases. This work intends to show how the use of artificial neural networks may circumvent the need of including an overwhelming number of parameters in the rate equations obtained through the classical, mechanistic approach. We focus on the synthesis of amoxicillin by the reaction of p-OH-phenylglycine methyl ester and 6-aminopenicillanic acid, catalyzed by penicillin G acylase immobilized on glyoxyl-agarose, at 25 degrees C and pH 6.5. The reaction was carried on a batch reactor. Three kinetic models of this system were compared: a mechanistic, a semi-empiric, and a hybrid-neural network (NN). A semi-empiric, simplified model with a reasonable number of parameters was initially built-up. It was able to portray many typical process conditions. However, it either underestimated or overestimated the rate of synthesis of amoxicillin when substrates' concentrations were low. A more complex, full-scale mechanistic model that could span all operational conditions was intractable for all practical purposes. Finally, a hybrid model, that coupled artificial neural networks (NN) to mass-balance equations was established, that succeeded in representing all situations of interest. Particularly, the NN could predict with accuracy reaction rates for conditions where the semi-empiric model failed, namely, at low substrate concentrations, a situation that would occur, for instance, at the end of a fed-batch industrial process.

Amoxicillin↗

PubMed2005

Collapsing mechanistic models: an application to dose selection for proof of concept of a selective irreversible antagonist.

When data fail to support fully mechanistic models, alternative modeling strategies must be pursued. Simpler, more empirical models or the fixing of various rate constants are necessary to avoid over-parameterization. Fitting empirical models can dilute information, limit interpretation, and cloud inference. Fixing rate constants requires external, relevant, and reliable information on the mechanism and can introduce subjectivity as well as complicate determining the validity of model extrapolation. Furthermore, both these methods ignore the possibility that failure of the data to support the mechanistic model could contain information about the pharmacodynamic process. If the pathway has processes with "fast" dynamics, these steps could collapse yielding parametrically simpler classes of models. The collapsed models would retain the mechanistic interpretation of the full model, which is crucial for performing substantive inference, while reducing the number of parameters to be estimated. These concepts are illustrated through their manifestations on the dose-effect relationship and ensuing dose selection for a proof of concept study. Specifically, a mechanistic model for a selective irreversible antagonist was posited and candidate classes of models were derived utilizing "fast dynamics" assumptions. Model assessment determined the rate-limiting step facilitating pertinent inference with respect to the mechanism. For comparison, inference using a more empirical modeling strategy is also presented. A general solution for the collapse of the typical PK-PD model differential equations is provided in Appendix A.

Administration, Oral↗

PubMed1995

The future of mechanistic research in risk assessment: where are we going and can we get there from here?

Quantitative estimates of human health risk are often based on mathematical models fit to experimental or epidemiological data. Recent years have witnessed a trend towards the use of mechanistic models in risk assessment applications. Such models afford a more biologically based interpretation of the data and a firmer scientific basis for extrapolation beyond the conditions under which the original data were obtained. In this article, we review some recent advances in the development of biologically based models for mutagenesis, carcinogenesis and developmental toxicity. Pharmacokinetic and receptor-binding models and their roles in mechanistic risk assessment are also discussed. The future of mechanistic research in risk assessment is contemplated, including the need for more elaborate experiments to obtain the data necessary for mechanistic modeling.

Animals↗

PubMed1995

Modification of cyanide toxicodynamics: mechanistic based antidote development.

Cyanide's actions are complex and cannot be attributed solely to inhibition of oxygen utilization. Recent mechanistic studies show that cyanide inhibits multiple enzymes and alters several vital intracellular processes to produce the intoxication syndrome. By understanding the intracellular targets and the mechanisms underlying the toxicity, it is proposed that more effective antidotal regimens can be achieved. A mechanistic based, multi-step in vitro model was developed for screening potential cyanide antidotes. A series of compounds was screened for their ability to reverse the effect of cyanide on six neurochemical markers in the PC12 cell line (neuronal cell model). Each compound was assigned a composite score based on the six assays; several compounds were identified which then exhibited efficacy in animal testing. Additional mechanistic based studies show that antioxidants and nitric oxide generators have promise as anti-cyanide agents. It is concluded that mechanistic based antidote design can be used to identify new compounds for testing in animal models.

Animals↗

PubMedDate not supplied

Mechanistic systems models of cell signaling networks: a case study of myocyte adrenergic regulation.

Signal transduction networks coordinate a wide variety of cellular functions, including gene expression, metabolism, and cell fate processes. Understanding biological networks quantitatively is a major challenge to post-genomic biology, and mechanistic systems models will be crucial for this task. Here, we review approaches towards developing mechanistic systems models of established cell signaling networks. The ability of mechanistic system models to generate testable biological hypotheses and experimental strategies is discussed. As a case study of model development and analysis, we examined the functional roles of phospholamban, the L-type calcium channel, the ryanodine receptor, and troponin I phosphorylation upon beta-adrenergic stimulation in the rat ventricular myocyte. Model analysis revealed that while protein kinase A-mediated phosphorylation of the ryanodine receptor greatly increases its calcium sensitivity, calcium autoregulation may adapt quickly by negating potential increases in contractility. Systematic combinations of in silico perturbations supported the conclusion that phospholamban phosphoregulation is the primary mechanism for increased sarcoplasmic reticulum load and calcium relaxation rate during beta-adrenergic stimulation, while both phospholamban and the L-type calcium channel contribute to increased systolic calcium. Combined with detailed experimental studies, mechanistic systems models will be valuable for developing a quantitative understanding of cell signaling networks.

Animals↗

PubMed1998

Correlation of mechanistic data and histopathology in the evaluation of selected toxic endpoints of the endocrine system.

The objective of this review is to correlate endocrinologic data from mechanistic studies with quantitative histopathology in selected examples of toxic endpoints of the endocrine system in laboratory animals. Mechanistic data can aid in the interpretation of animal toxicology findings and help clarify their significance in risk assessment. Endocrine organs of rodents frequently undergo proliferative changes with advancing age and following chronic exposure to large doses of xenobiotic chemicals, and the sensitivity of rodent endocrine tissues appears to be increasing. Many xenobiotic chemicals in large doses disrupt thyroid function in rodents either by a direct effect on the thyroid influencing synthesis of thyroid hormones or by adversely influencing their peripheral metabolism. A number of chemicals disrupt thyroid function by inhibiting the important enzyme, thyroperoxidase (TPO). A contemporary example of a chemical acting as TPO-inhibitor is sulfamethazine. In short-term mechanistic studies in rats there was a log-dose response relationship in circulating levels of thyroid and pituitary hormones plus a similar non-linear dose-response in morphologic changes in thyroid follicular cells. Endocrinologic data from mechanistic studies and histopathologic/ultrastructural findings will also be presented for the effects of the food color, FDC Red No. 3 (Erythrosine), on the thyroid gland in rats and parathyroid hormone-related protein (a major causative factor in cancer-associated hypercalcemia) on parathyroid chief cells in mice.

Animals↗

PubMed2003

Mechanistic considerations for general acid-base catalysis by RNA: revisiting the mechanism of the hairpin ribozyme.

Several small ribozymes carry out self-cleavage at a specific phosphodiester bond to yield 2',3'-cyclic phosphate and 5'-hydroxyl termini. Prior mechanistic and structural studies on the HDV ribozymes led to the proposal that the pK(a) of C75 is shifted toward neutrality, making it an effective general acid. Recent mechanistic studies on the hairpin ribozyme have led to models in which protonation of G8 is required for phosphodiester cleavage, either for general acid catalysis or for electrostatic stabilization. Inspection of recent crystal structures of the hairpin ribozyme, including a complex with a vanadate transition state mimic, suggests an alternative model involving general acid-base catalysis with G8 serving as the general base and A38 as the general acid. This model is consistent with the literature on the hairpin ribozyme, including pH-rate profiles of wild-type and mutant ribozymes and solvent isotope effects. General mechanistic considerations for RNA catalysis suggest that the penalty for having general acids and bases with pK(a)s removed from neutrality is not as severe as expected. These considerations suggest that general acid-base catalysis may be a common mechanistic strategy of RNA enzymes.

Animals↗

PubMed2004

Evolution of enzymatic activities in the orotidine 5'-monophosphate decarboxylase suprafamily: mechanistic evidence for a proton relay system in the active site of 3-keto-L-gulonate 6-phosphate decarboxylase.

3-Keto-L-gulonate 6-phosphate decarboxylase (KGPDC) and orotidine 5'-monophosphate decarboxylase (OMPDC) are homologous enzymes that share the (beta/alpha)(8)-fold but catalyze mechanistically distinct reactions [Wise, E., Yew, W. S., Babbitt, P. C., Gerlt, J. A., and Rayment, I. (2002) Biochemistry 41, 3861-3869]. KGPDC catalyzes the Mg(2+)-dependent decarboxylation of 3-keto-L-gulonate 6-phosphate, an intermediate in the catabolic pathway of L-ascorbate utilization by Escherichia coli K-12 [Yew, W. S., and Gerlt, J. A. (2002) J. Bacteriol. 184, 302-306]. OMPDC catalyzes a metal ion-independent reaction that likely proceeds without a vinyl anion intermediate [Appleby, T. C., Kinsland, C., Begley, T., and Ealick, S. E. (2000) Proc. Natl. Acad. Sci. U.S.A. 97, 2005-2010], although the mechanistic details are uncertain. An active site Lys located at the end of the third beta-strand in OMPDC has been proposed to be the general acid that delivers a solvent-derived proton to the UMP product; the active site of KGPDC contains a homologous Lys residue (Lys64). Herein, we report investigations of the KGPDC-catalyzed reaction that are consistent with a mechanism involving a Mg(2+)-stabilized cis-enediolate intermediate [Wise, E. L., Yew, W. S., Gerlt, J. A., and Rayment, I. (2003) Biochemistry 42, 12133-12142] and implicate waters proximal to His136 and Arg139, both located at the end of the sixth beta-strand, as the general acids that deliver a solvent-derived proton to the intermediate to form the L-xylulose 5-phosphate product. On the basis of our mechanistic investigations, Lys64 stabilizes the cis-enediolate intermediate by forming hydrogen bonds to both O1 and O2 of the intermediate. Thus, although the active sites of OMPDC and KGPDC contain a conserved Lys at the end of the third beta-strand, their roles in catalysis are not conserved. Furthermore, a conserved Asp at the end of the third beta-strand in OMPDC participates in a hydrogen-bonded network that positions the acidic Lys residue; in the active site of KGPDC, the homologous Asp67 participates in stabilization of the enediolate intermediate and enforces a cis geometry. We conclude that the conserved active site residues perform different functions in the OMPDC- and KGPDC-catalyzed reactions, so the mechanisms of their reactions are completely distinct. This study further highlights the opportunistic nature of divergent evolution in conscripting the active site of a progenitor to catalyze a mechanistically distinct reaction.

Amino Acid Sequence↗

PubMed2005

P(450)/NADPH/O(2)- and P(450)/PhIO-catalyzed N-dealkylations are mechanistically distinct.

A high-valent iron-oxo species analogous to the compound I of peroxidases has been thought to be the activated oxygen species in P450-catalyzed reactions. Spectroscopic characterization of the catalytically competent iron-oxo species in iodosobenzene (PhIO)-supported model reactions and parallels between these model reactions and PhIO- and NADPH/O2-supported P450 reactions have been taken as strong evidence for this proposal. To support this proposal, subtle differences observed in regio- and chemoselectivities, isotope effects, and source of oxygen, etc., between NADPH/O2- and PhIO-supported P450 reactions have been generally attributed to reasons other than the mechanistic differences between the two systems. In the present study, we have used a series of sensitive mechanistic probes, 4-chloro-N-cyclopropyl-N-alkylanilines, to compare and contrast the chemistries of the NADPH/O2- and PhIO-supported purified CYP2B1 N-dealkylation reactions. Herein we present the first experimental evidence to demonstrate that the NADPH/O2- and PhIO-supported P450 N-dealkylations are mechanistically distinct and, thus, the P450/PhIO system may not be a good mechanistic model for P450/NADPH/O2-catalyzed N-dealkylations.

Alkylation↗