Plastic digesting enzymes are now routinely available and are very promising candidates to treat the huge amounts of plastics found in the oceans. For example, one of those enzymes is the PETase digesting Polyethylenterephthalat plastics. It was discovered in 2016 in the organism Ideonella sakaiensis. Modern machine learning based optimization routines for the amino acid sequence can lead to highly optimized enzymes which show optimal performance under pre-defined environmental conditions. In other words, these modern techniques use existing knowledge and try and error approaches in order to optimize these enzymes. But often the understanding, why this optimization led to its success is very poor. Here, neutron protein crystallography can be used to elucidate the exact mechanism of such an optimized enzyme. Adversely to x-rays, neutrons can see the hydrogen atoms in the protein structure and can therefore determine protonation states of relevant amino acids during the enzymatic cycle of this protein.
In this GNEUS project a relevant plastic digesting enzyme should be identified, expressed and crystallized. The neutron structure of this crystallized enzyme should give information on the enzymatic process which then should be compared to the optimization routes found by the machine learning routines. Besides this biochemistry related project, the GNEUS candidate can also add UV-visible micro-spectroscopy to the instrument BioDiff which would allow to identify, whether the plastic ligand is bound in the relevant enzymatic stage or not. This provides a second pillar of this GNEUS project which will lead to a publication which will be cited by all users of this newly developed in-situ crystal spectrophotometer.