OleT(JE), a cytochrome P450, catalyzes the conversion of fatty acids to terminal alkenes using hydrogen peroxide as a cosubstrate. Analytical studies with an eicosanoic acid substrate show that the enzyme predominantly generates nonadecene and that carbon dioxide is the one carbon coproduct of the reaction. The addition of hydrogen peroxide to a deuterated substrate-enzyme (E-S) complex results in the transient formation of an iron(IV) oxo π cation radical (Compound I) intermediate which is spectroscopically indistinguishable from those that perform oxygen insertion chemistries. A kinetic isotope effect for Compound I decay suggests that it abstracts a substrate hydrogen atom to initiate fatty acid decarboxylation. Together, these results indicate that the initial mechanism for alkene formation, which does not result from oxygen rebound, is similar to that widely suggested for P450 monooxygenation reactions.

OleT is a cytochrome P450 enzyme that catalyzes the removal of carbon dioxide from variable chain length fatty acids to form 1-alkenes. In this work, we examine the binding and metabolic profile of OleT with shorter chain length (n ≤ 12) fatty acids that can form liquid transportation fuels. Transient kinetics and product analyses confirm that OleT capably activates hydrogen peroxide with shorter substrates to form the high-valent intermediate Compound I and largely performs C–C bond scission. However, the enzyme also produces fatty alcohol side products using the high-valent iron oxo chemistry commonly associated with insertion of oxygen into hydrocarbons. When presented with a short chain fatty acid that can initiate the formation of Compound I, OleT oxidizes the diagnostic probe molecules norcarane and methylcyclopropane in a manner that is reminiscent of reactions of many CYP hydroxylases with radical clock substrates. These data are consistent with a decarboxylation mechanism in which Compound I abstracts a substrate hydrogen atom in the initial step. Positioning of the incipient substrate radical is a crucial element in controlling the efficiency of activated OH rebound.

OleT, a recently discovered member of the CYP152 family of cytochrome P450s, catalyzes a unique decarboxylation reaction, converting free fatty acids into 1-olefins and carbon dioxide using H2O2 as an oxidant. The C–C cleavage reaction proceeds through hydrogen atom abstraction by an iron­(IV)-oxo intermediate known as Compound I. The capacity of the enzyme for generating important commodity chemicals and liquid biofuels has inspired a flurry of investigations seeking to maximize its biosynthetic potential. One common approach has sought to address the limitations imposed by the H2O2 cosubstrate, particularly for in vivo applications. Numerous reports have shown relatively efficient decarboxylation activity with various combinations of the enzyme with pyridine nucleotides, biological redox donors, and dioxygen, implicating a mechanism whereby OleT can generate Compound I via a canonical P450 O2 dependent reaction scheme. Here, we have applied transient kinetics, cryoradiolysis, and steady state turnover studies to probe the precise origins of OleT turnover from surrogate redox systems. Electron transfer from several redox donors is prohibitively sluggish, and the enzyme is unable to form the hydroperoxo-ferric adduct that serves as a critical precursor to Compound I. Despite the ability for OleT to readily bind O2 once it is reduced, autoxidation of the enzyme and redox partners leads to the generation of H2O2, which is ultimately responsible for the vast majority of turnover. These results illuminate several strategies for improving OleT for downstream biocatalytic applications.

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Increasing levels of energy consumption, dwindling resources, and environmental considerations have served as compelling motivations to explore renewable alternatives to petroleum-based fuels, including enzymatic routes for hydrocarbon synthesis. Phylogenetically diverse species have long been recognized to produce hydrocarbons, but many of the enzymes responsible have been identified within the past decade. The enzymatic conversion of C chain length fatty aldehydes (or acids) to C hydrocarbons, alkanes or alkenes, involves a C-C scission reaction. Surprisingly, the enzymes involved in hydrocarbon synthesis utilize non-heme mononuclear iron, dinuclear iron, and thiolate-ligated heme cofactors that are most often associated with monooxygenation reactions. In this review, we examine the mechanisms of several enzymes involved in hydrocarbon biosynthesis, with specific emphasis on the structural and electronic changes that enable this functional switch.

Slurries are often used in chemical and pharmaceutical manufacturing processes but present challenging online measurement and monitoring problems. In this paper, a novel multivariate kinetic modeling application is described that provides calibration-free estimates of timeresolved profiles of the solid and dissolved fractions of a substance in a model slurry system. The kinetic model of this system achieved data fusion of time-resolved spectroscopic measurements from two different kinds of fiber-optic probes. Attenuated total reflectance UV−vis (ATR UV−vis) and diffuse reflectance near-infrared (NIR) spectra were measured simultaneously in a small-scale semibatch reactor. A simplified comprehensive kinetic model was then fitted to the time-resolved spectroscopic data to determine the kinetics of crystallization and the kinetics of dissolution for online monitoring and quality control purposes. The parameters estimated in the model included dissolution and crystal growth rate constants, as well as the dissolution rate order. The model accurately estimated the degree of supersaturation as a function of time during conditions when crystallization took place and accurately estimated the degree of undersaturation during conditions when dissolution took place. S ignificant progress in the area of multivariate batch process monitoring, modeling, and control has been made over the last 2 decades; 1 however, strategies for monitoring and modeling of slurries have not been widely reported, despite the fact that slurries are often used in chemical and pharmaceutical manufacturing processes. Many of the early developments in process analysis can be attributed to groundbreaking work of Nomikos and MacGregor 2,3 and Wold and co-workers.4−6 These efforts were largely focused on the use of principal component analysis (PCA) and partial least-squares (PLS) to develop multivariate statistical process control (MSPC) models for characterization of process operating conditions and thereafter the definition of normal operating conditions for the production of batches fulfilling the desired specifications.1 These models were then used to monitor future batches, product quality, and yield, as well as detect faults and diagnose process deviations.An alternative to this approach called multivariate kinetic modeling has also seen significant development over the last 2 decades. In these approaches, first-principles physical models are fitted directly to multivariate spectroscopic measurements where, typically, the adjustable model parameters are rate constants.7−10 Recently, kinetic model fitting methods were extended to achieve fusion of calorimetric measurements of univariate nature with multivariate spectroscopic measurements, 11−14 extended to incorporate chemical equilibria, 15,16 used for estimation of additional parameters such as activation energies and reaction enthalpies, 17,18 and for fitting of extents of reaction in gas−liquid systems. 19 These modeling approaches offer some advantages and some drawbacks compared to...

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