␥-Hexachlorocyclohexane dehydrochlorinase (LinA) catalyzes the initial steps in the biotransformation of the important insecticide ␥-hexachlorocyclohexane (␥-HCH) by the soil bacterium Sphingomonas paucimobilis UT26. Stereochemical analysis of the reaction products formed during conversion of ␥-HCH by LinA was investigated by GC-MS, NMR, CD, and molecular modeling. The NMR spectra of 1,3,4,5,6-pentachlorocyclohexene (PCCH) produced from ␥-HCH using either enzymatic dehydrochlorination or alkaline dehydrochlorination were compared and found to be identical. Both enantiomers present in the racemate of synthetic ␥-PCCH were converted by LinA, each at a different rate.

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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.