We use a bioinformatics method combined with artificial intelligence to mine structural databases using three dimensional search templates termed “catalophores” (i.e. carrier of the catalytic function). Enzymes, identified with this technique do not share a common structure or sequence base with their currently employed counterparts and therefore potentially feature altered protein properties such as thermo- and solvent stability, substrate spectrum, selectivity and specificity.
With CatalophoreTM knowledge based we are able to mine our prepared structural databases using three dimensional search templates that cover the arrangement of chemical functional groups essential for catalysing a particular reaction.
The CatalophoreTM unguided approach is a significant improvement of this concept using pre-calculated point-clouds representing physico-chemical properties of the “empty space” in enzyme active sites.
This allows the identification of alternative enzymes for biocatalytic processes and medical applications without detailed knowledge of the involved reaction mechanism and will even enable cross-reactivity comparisons of e.g. therapeutically relevant inhibitors.
The R&D vision of Innophore is to identify high-value industrial and therapeutic enzymes and to develop and identify enzymes for more efficient, green chemical production processes and novel biosimilars for medical treatments.