RESUMEN
BACKGROUND: Galactose oxidase (GOase) catalyses the highly selective oxidation of terminal galactosides on a wide range of natural glycoconjugates and has found wide applications in biotechnology - particularly in biocatalysis. GOase is copper dependent and uses oxygen to oxidise the C6-primary alcohol of galactose and produces hydrogen peroxide. The enzyme activity can be conveniently assessed by a colorimetric assay. OBJECTIVES: The objective of the present study was to develop an assay system, which is independent of the hydrogen peroxide formation to identify possible fluorinated GOase inhibitors. In case that the inhibitor bears a primary or secondary alcohol, it could also be oxidised by the enzyme. In such case, the colorimetric assay is not able to distinguish between substrate and inhibitor, since oxidation of both molecules would result in the formation of hydrogen peroxide. METHODS: D-galactose (D-Gal) was immobilised onto a gold surface functionalised by selfassembled monolayers (SAMs,). A GOase solution was then added to the surface in a droplet for a certain period of time and thereafter washed away. The activity of GOase on the immobilised D-Gal can then be quantified by MALDI-ToF MS. RESULTS: For inhibition studies, GOase was incubated together with 62.5 mM of deoxy-fluorinated monosaccharides on the D-Gal displaying platform. Five deoxy-fluorinated D-Gal showed a >50% inhibition of its activity. The array system has been moreover utilised to determine the apparent IC50 value of 3-F-Gal 15 as a proof of principle. CONCLUSION: The developed array platform allows the fast identification of GOase substrates and inhibitors from a library of deoxy-fluorinated sugars using MALDI-ToF MS as a label-free readout method. In addition, the enzymatic reaction enables for the in situ activation of sugar-coated surfaces to bioorthogonal aldehydes, which can be utilised for subsequent chemical modifications.
Asunto(s)
Inhibidores Enzimáticos/química , Galactosa Oxidasa/química , Galactosa/química , Ensayos Analíticos de Alto Rendimiento , Adsorción , Biocatálisis , Galactosa Oxidasa/antagonistas & inhibidores , Oro/química , Halogenación , Peróxido de Hidrógeno/química , Monosacáridos/química , Espectrometría de Masa por Láser de Matriz Asistida de Ionización DesorciónRESUMEN
In directed evolution (DE) the assessment of candidate enzymes and their modification is essential. In this study we have investigated genetic algorithms (GAs) in this context and conducted a systematic study of the behavior of GAs on 20 fitness landscapes (FLs) of varying complexity. This has allowed the tuning of the GAs to be explored. On the basis of this study, recommendations for the best GA settings to use for a GA-directed high-throughput experimental program (in which populations and the number of generations is necessarily low) are reported. The FLs were based upon simple linear models and were characterized by the behavior of the GA on the landscape as demonstrated by stall plots and the footprints and adhesion of candidate solutions, which highlighted local optima (LOs). In order to maximize progress of the GA and to reduce the chances of becoming stuck in a LO it was best to use: 1)â a large number of generations, 2)â high populations, 3)â removal of duplicate sequences (clones), 4)â double mutation, and 5)â high selection pressure (the two best individuals go to the next generation), and 6)â to consider using a designed sequence as the starting point of the GA run. We believe that these recommendations might be appropriate starting points for studies employing GAs within DE experiments.
Asunto(s)
Algoritmos , Evolución Molecular Dirigida/estadística & datos numéricos , Epóxido Hidrolasas/genética , Modelos Genéticos , Epóxido Hidrolasas/metabolismo , Expresión Génica , Ensayos Analíticos de Alto Rendimiento , Modelos Lineales , Mutación , Análisis de Componente PrincipalRESUMEN
Measurement of enzyme activity and selectivity at in vivo concentrations is highly desirable in a range of fields including diagnostics, functional proteomics and directed evolution. Here we demonstrate how surface-enhanced resonance Raman scattering (SERRS), measured using silver nanoparticles, can be used to detect the activity of hydrolases at ultra-low levels. This approach was made possible by designing 'masked' enzyme substrates that are initially completely undetected by SERRS. Turnover of the substrate by the enzyme leads to the release of a surface targeting dye, and intense SERRS signals proportional to enzyme activity are generated. The method was used to rapidly screen the relative activities and enantioselectivities of fourteen enzymes including examples of lipases, esterases and proteases. In the current format the sensitivity of the technique is sufficient to detect 500 enzyme molecules, which offers the potential to detect multiple enzyme activities simultaneously and at levels found within single cells.