bioRxiv Science⌕ Search

Biology subjects

Vavra, O.

Publications and source records attributed to Vavra, O..

2 recordsLinked to original sources

Molecular trick to reverse SN2 mechanism in hydrolytic enzyme

Hydrolytic haloalkane dehalogenase enzymes catalyze an SN2 nucleophilic substitution to erase halogen substituents in organohalogen compounds. The acid-base-nucleophile triad secures irreversible SN2 displacement of the halogen for the hydroxyl derived from the water. Catalysis relies on the protonatable imidazole ring of the histidine base, and its substitution with an asparagine traps the enzyme in a covalently bound intermediate state, a principle exploited in the widely used HaloTag technology. In contrast, the histidine-to-phenylalanine substitution triggers reversibility of the SN2 mechanism, but the molecular trick by which it reprograms the catalytic pathway remains unknown. Here, we show that the phenylalanine at the site of the histidine base spatially disturbs the adjacent residues, leading to the remodeling of surrounding active-site loops. Consequently, rerouting of the access tunnels imparts distinctive kinetic behavior, featuring a reversible SN2 chemical step that facilitates transhalogenation reactions. This information is crucial for engineering next-generation biocatalysts for sustainable chemistry. HighlightsO_LICatalytic triad (glutamate-histidine-aspartate) secures irreversible SN2 mechanism C_LIO_LIHistidine-to-phenylalanine substitution in the triad leads to a reversible SN2 reaction C_LIO_LIEnzyme active site rerouting is a hallmark of the catalytic reprogramming C_LIO_LIBasis for designing biocatalysts for sustainable transhalogenation chemistry C_LI The bigger pictureHaloalkane dehalogenases catalyze the hydrolytic cleavage of the carbon-halogen bond in halogenated hydrocarbons, a feature used in a wide variety of industrial and biotechnological processes. In HaloTag technology, the catalytic histidine is replaced by an asparagine to enable a stable covalent bonding between a probe and a protein for biological imaging, affinity purification, etc. Remarkably, this originally irreversible SN2 process becomes fully reversible in a histidine-to-phenylalanine mutant. Moreover, halogen ion product is released at this stage, offering a greener alternative for transhalogenation reactions compared to the conventional synthetic approach and a way to recycle environmentally harmful halogenated compounds. However, the optimization of enzymes is needed for applications on an industrial scale. Therefore, we investigated the kinetics of the SN2 step and structural features of these two enzyme mutants, providing a basis for subsequent optimization efforts.

bioengineering↗

Large-scale Annotation of Biochemically Relevant Pockets and Tunnels in Cognate Enzyme-Ligand Complexes

Tunnels in enzymes with buried active sites are key structural features allowing the entry of substrates and the release of products, thus contributing to the catalytic efficiency. Targeting the bottlenecks of protein tunnels is also a powerful protein engineering strategy. However, the identification of functional tunnels in multiple protein structures is a non-trivial task that can only be addressed computationally. We present a pipeline integrating automated structural analysis with an in-house machine-learning predictor for the annotation of protein pockets, followed by the calculation of the energetics of ligand transport via biochemically relevant tunnels. A thorough validation using eight distinct molecular systems revealed that CaverDock analysis of ligand un/binding is on par with time-consuming molecular dynamics simulations, but much faster. The optimized and validated pipeline was applied to annotate more than 17,000 cognate enzyme-ligand complexes. Analysis of ligand un/binding energetics indicates that the top priority tunnel has the most favourable energies in 75 % of cases. Moreover, energy profiles of cognate ligands revealed that a simple geometry analysis can correctly identify tunnel bottlenecks only in 50 % of cases. Our study provides essential information for the interpretation of results from tunnel calculation and energy profiling in mechanistic enzymology and protein engineering. We formulated several simple rules allowing identification of biochemically relevant tunnels based on the binding pockets, tunnel geometry, and ligand transport energy profiles.

bioinformatics↗