Predictive biotechnology – A case study on 4-phenol oxidase

Enzymes are Nature´s catalysts and have a great impact on (organic)synthesis either in their natural role or by being applied in technical processes. Certainly, the knowledge about enzymes and their functionality is steadily increasing. In addition, frequently novel enzymes and reactions are described. Herein, we present a streamlined approach of enzyme mining in order to rationally select enzymes with proposed functionalities from the ever-increasing amount of available sequence data. Hence, we want to predict enzyme functionality and applicability based on the amino acid sequence: a work related to predictive biotechnology.

In a case study on 4-phenol oxidases, to be precise on the VAO/PCMH flavoprotein family, eight enzymes were selected from about 300 sequences on basis of the properties of first shell residues of the catalytic center. Thus, a broad sequence space was covered on base of a first bioinformatic screening approach including known enzyme studies. To handle numerous sequences and easily rationalize or even predict sequence-function relations we created a computational tool, called amino acid cluster analysis (A2CA; https://doi.org/10.57760/sciencedb.09549). It allows to correlate the phylogenetic information with the data from a respective multiple sequence alignment as well as to link any other data such as activity, binding, structural data. Thereafter, selected candidates were produced and fully characterized. Correlations between important residues identified and enzyme activity yielded robust sequence-function relations, which were exploited by site-saturation mutagenesis. The application of a novel oxidase screening assay resulted in 16 active enzyme variants which were up to 90-times more active than respective wildtype enzymes. The results were supported by kinetic experiments and structural models. The newly introduced amino acids confirmed the correlation studies which overall highlights the successful logic of the presented approach.