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The statistical evaluation of triacylglycerol profiles in plant oils based on high-performance liquid chromatography mass spectrometry (HPLC/MS) analysis enables the differentiation of various plant oils on the basis of the multidimensional data matrix. A data set of 93 oil samples from 60 varieties of plants composed from 355 triacylglycerols is evaluated using the principal component analysis. Analyzed samples are resolved in the principal component analysis plot, and similarities among some types of plant oils are visualized by the formation of clusters. The authentication of plant oils is tested with model samples of olive oil adulterated with sunflower oil at different concentration levels. Our HPLC/MS method using the statistical multivariate data analysis of a large data matrix enables a clear identification of adulterated olive oils already from 1% of added sunflower oil as an adulterant.

We evaluate the applicability of automated molecular docking techniques and quantum mechanical calculations to the construction of a set of structures of enzyme-substrate complexes for use in Comparative binding energy (COMBINE) analysis to obtain 3D structure-activity relationships. The data set studied consists of the complexes of eighteen substrates docked within the active site of haloalkane dehalogenase (DhlA) from Xanthobacter autotrophicus GJ10. The results of the COMBINE analysis are compared with previously reported data obtained for the same dataset from modelled complexes that were based on an experimentally determined structure of the DhlA-dichloroethane complex. The quality of fit and the internal predictive power of the two COMBINE models are comparable, but better external predictions are obtained with the new approach. Both models show a similar composition of the principal components. Small differences in the relative contributions that are assigned to important residues for explaining binding affinity differences can be directly linked to structural differences in the modelled enzyme-substrate complexes: (i) rotation of all substrates in the active site about their longitudinal axis, (ii) repositioning of the ring of epihalohydrines and the halogen substituents of 1,2-dihalopropanes, and (iii) altered conformation of the long-chain molecules (halobutanes and halohexanes). For external validation, both a novel substrate not included in the training series and two different mutant proteins were used. The results obtained can be useful in the future to guide the rational engineering of substrate specificity in DhlA and other related enzymes.

Haloalkane dehalogenases catalyze cleavage of the carbon-halogen bond in halogenated aliphatic compounds, resulting in the formation of an alcohol, a halide, and a proton as the reaction products. Three structural features of haloalkane dehalogenases are essential for their catalytic performance: (i) a catalytic triad, (ii) an oxyanion hole, and (iii) the halide-stabilizing residues. Halide-stabilizing residues are not structurally conserved among different haloalkane dehalogenases. The level of stabilization of the transition state structure of S(N)2 reaction and halide ion provided by each of the active site residues in the enzymes DhlA, LinB, and DhaA was quantified by quantum mechanic calculations. The residues that significantly stabilize the halide ion were assigned as the primary (essential) or the secondary (less important) halide-stabilizing residues. Site-directed mutagenesis was conducted with LinB enzyme to confirm location of its primary halide-stabilizing residues. Asn38Asp, Asn38Glu, Asn38Phe, Asn38Gln, Trp109Leu, Phe151Leu, Phe151Trp, Phe151Tyr, and Phe169Leu mutants of LinB were constructed, purified, and kinetically characterized. The following active site residues were classified as the primary halide-stabilizing residues: Trp125 and Trp175 of DhlA; Asn38 and Trp109 of LinB; and Asn41 and Trp107 of DhaA. All these residues make a hydrogen bond with the halide ion released from the substrate molecule, and their substitution results in enzymes with significantly modified catalytic properties. The following active site residues were classified as the secondary halide-stabilizing residues: Phe172, Pro223, and Val226 of DhlA; Trp207, Pro208, and Ile211 of LinB; and Phe205, Pro206, and Ile209 of DhaA. The differences in the halide stabilizing residues of three haloalkane dehalogenases are discussed in the light of molecular adaptation of these enzymes to their substrates.

The hydrolysis of haloalkanes to their corresponding alcohols and inorganic halides is catalyzed by alpha/beta-hydrolases called haloalkane dehalogenases. The study of haloalkane dehalogenases is vital for the development of these enzymes if they are to be utilized for bioremediation of organohalide-contaminated industrial waste. We report the kinetic and structural analysis of the haloalkane dehalogenase from Sphingomonas paucimobilis UT26 (LinB) in complex with each of 1,2-dichloroethane and 1,2-dichloropropane and the reaction product of 1-chlorobutane turnover. Activity studies showed very weak but detectable activity of LinB with 1,2-dichloroethane [0.012 nmol s(-1) (mg of enzyme)(-1)] and 1,2-dichloropropane [0.027 nmol s(-1) (mg of enzyme)(-1)]. These activities are much weaker compared, for example, to the activity of LinB with 1-chlorobutane [68.2 nmol s(-1) (mg of enzyme)(-1)]. Inhibition analysis reveals that both 1,2-dichloroethane and 1,2-dichloropropane act as simple competitive inhibitors of the substrate 1-chlorobutane and that 1,2-dichloroethane binds to LinB with lower affinity than 1,2-dichloropropane. Docking calculations on the enzyme in the absence of active site water molecules and halide ions confirm that these compounds could bind productively. However, when these moieties were included in the calculations, they bound in a manner similar to that observed in the crystal structure. These data provide an explanation for the low activity of LinB with small, chlorinated alkanes and show the importance of active site water molecules and reaction products in molecular docking.

The application of molecular modelling and quantum-chemistry calculations for the 'computational site-directed mutagenesis' of haloalkane dehalogenase is described here. The exhaustive set of single point mutants of haloalkane dehalogenase in position 172 was constructed by homology modelling. The ability of substituting residues to stabilize the halide ion formed during the dehalogenation reaction in the enzyme active site was probed by quantum-chemical calculations. A simplified modelling procedure was adopted to obtain informative results on the potential activity of mutant proteins in a sufficiently short period of time, which, in the future, could be applicable for making bona fide predictions of mutants' activity prior to their preparation in the laboratory. The reaction pathways for the carbon-halide bond cleavage were calculated using microscopic models of wild type and mutant proteins. The theoretical parameters derived from the calculation, i.e. relative energies and selected atomic charges of educt, product and transition state structures, were statistically correlated with experimentally determined activities. The charge difference of educt and product on the halide-stabilizing hydrogen atom of residue 172 was the best parameter to distinguish protein variants with high activity from mutant proteins displaying a low activity. All mutants with significant activity in the experiment were found to have this parameter one order of magnitude higher than mutants with low activity. The results obtained are discussed in the light of the practical application of this methodology for the prediction of potentially active protein variants. Further automation of the modelling procedure is suggested for combinatorial screening of the large number of protein variants. Coupling of the dehalogenation reaction with hydrogenation of the halide ion formed during the reaction in the enzyme active site was proposed as a possible way to improve the catalytic activity of the haloalkane dehalogenase of Xanthobacter autotrophicus GJ10.