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1.
Biochemistry ; 44(9): 3390-401, 2005 Mar 08.
Article in English | MEDLINE | ID: mdl-15736949

ABSTRACT

Haloalkane dehalogenases are microbial enzymes that cleave a carbon-halogen bond in halogenated compounds. The haloalkane dehalogenase LinB, isolated from Sphingomonas paucimobilis UT26, is a broad-specificity enzyme. Fifty-five halogenated aliphatic and cyclic hydrocarbons were tested for dehalogenation with the LinB enzyme. The compounds for testing were systematically selected using a statistical experimental design. Steady-state kinetic constants K(m) and k(cat) were determined for 25 substrates that showed detectable cleavage by the enzyme and low abiotic hydrolysis. Classical quantitative structure-activity relationships (QSARs) were used to correlate the kinetic constants with molecular descriptors and resulted in a model that explained 94% of the experimental data variability. The binding affinity of the tested substrates for this haloalkane dehalogenase correlated with hydrophobicity, molecular surface, dipole moment, and volume:surface ratio. Binding of the substrate molecules in the active site pocket of LinB depends nonlinearly on the size of the molecules. Binding affinity increases with increasing substrate size up to a chain length of six carbon atoms and then decreases. Comparative binding energy (COMBINE) analysis was then used to identify amino acid residues in LinB that modulate its substrate specificity. A model with three statistically significant principal components explained 95% of the experimental data variability. van der Waals interactions between substrate molecules and the enzyme dominated the COMBINE model, in agreement with the importance of substrate size in the classical QSAR model. Only a limited number of protein residues (6-8%) contribute significantly to the explanation of variability in binding affinities. The amino acid residues important for explaining variability in binding affinities are as follows: (i) first-shell residues Asn38, Asp108, Trp109, Glu132, Ile134, Phe143, Phe151, Phe169, Val173, Trp207, Pro208, Ile211, Leu248, and His272, (ii) tunnel residues Pro144, Asp147, Leu177, and Ala247, and (iii) second-shell residues Pro39 and Phe273. The tunnel and the second-shell residues represent the best targets for modulating specificity since their replacement does not lead to loss of functionality by disruption of the active site architecture. The mechanism of molecular adaptation toward a different specificity is discussed on the basis of quantitative comparison of models derived for two protein family members.


Subject(s)
Alkanes/chemistry , Hydrocarbons, Halogenated/chemistry , Hydrolases/chemistry , Quantitative Structure-Activity Relationship , Sphingomonas/enzymology , Alkanes/metabolism , Binding Sites , Catalysis , Computational Biology/methods , Crystallography, X-Ray , Hydrocarbons, Halogenated/metabolism , Hydrolases/metabolism , Kinetics , Models, Chemical , Models, Molecular , Models, Statistical , Multivariate Analysis , Quantum Theory , Substrate Specificity , Thermodynamics
2.
J Chem Inf Comput Sci ; 44(6): 2126-32, 2004.
Article in English | MEDLINE | ID: mdl-15554683

ABSTRACT

Binding of fatty acids to cryptogein, the proteinaceous elicitor from Phytophthora, was studied by using molecular docking and quantitative structure-activity relationships analysis. Fatty acids bind to the groove located inside the cavity of cryptogein. The structure-activity model was constructed for the set of 27 different saturated and unsaturated fatty acids explaining 87% (81% cross-validated) of the quantitative variance in their binding affinity. The difference in binding between saturated and unsaturated fatty acids was described in the model by three electronic descriptors: the energy of the lowest unoccupied molecular orbital, the energy of the highest occupied molecular orbital, and the heat of formation. The presence of double bonds in the ligand generally resulted in stronger binding. The difference in binding within the group of saturated fatty acids was explained by two steric descriptors, i.e., ellipsoidal volume and inertia moment of length, and one hydrophobicity descriptor, i.e., lipophility. The developed model predicted strong binding for two biologically important molecules, geranylgeranyol and farnesol playing an important role in plant signaling as lipid anchors of some membrane proteins. Elicitin mutants selectively binding only one type of ligand were designed for future experimental studies.


Subject(s)
Algal Proteins/chemistry , Fatty Acids/chemistry , Quantitative Structure-Activity Relationship , Amino Acid Substitution , Binding Sites , Fungal Proteins , Ligands , Mutation , Protein Binding , Protein Conformation
3.
J Comput Aided Mol Des ; 17(5-6): 299-311, 2003.
Article in English | MEDLINE | ID: mdl-14635723

ABSTRACT

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.


Subject(s)
Hydrocarbons, Halogenated/chemistry , Hydrolases/chemistry , Binding Sites , Computer Simulation , Databases, Protein , Hydrocarbons, Halogenated/metabolism , Hydrolases/metabolism , Imaging, Three-Dimensional , Least-Squares Analysis , Models, Chemical , Models, Molecular , Molecular Conformation , Molecular Structure , Principal Component Analysis , Protein Binding , Protein Conformation , Quantitative Structure-Activity Relationship , Static Electricity , Substrate Specificity , Thermodynamics , Xanthobacter/enzymology
4.
Biochemistry ; 41(15): 4847-55, 2002 Apr 16.
Article in English | MEDLINE | ID: mdl-11939779

ABSTRACT

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.


Subject(s)
Hydrolases/chemistry , Hydrolases/metabolism , Propane/analogs & derivatives , Sphingomonas/enzymology , Amino Acid Sequence , Binding Sites , Crystallography, X-Ray , Ethylene Dichlorides/pharmacology , Hydrolases/antagonists & inhibitors , Indicators and Reagents , Kinetics , Models, Molecular , Propane/pharmacology , Protein Conformation , Water/pharmacology
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