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Substrate specificity of 2-deoxy-D-ribose 5-phosphate aldolase (DERA) assessed by different protein engineering and machine learning methods

DOI: 10.1007/s00253-020-10960-x DOI Help

Authors: Sanni Voutilainen (VTT Technical Research Centre of Finland Ltd) , Markus Heinonen (Aalto University; Helsinki Institute for Information Technology) , Martina Andberg (VTT Technical Research Centre of Finland Ltd) , Emmi Jokinen (Aalto University) , Hannu Maaheimo (VTT Technical Research Centre of Finland Ltd) , Johan Pääkkönen (University of Eastern Finland) , Nina Hakulinen (University of Eastern Finland) , Juha Rouvinen (University of Eastern Finland) , Harri Lähdesmäki (Aalto University) , Samuel Kaski (Aalto University; Helsinki Institute for Information Technology) , Juho Rousu (Aalto University; Helsinki Institute for Information Technology) , Merja Penttilä (VTT Technical Research Centre of Finland Ltd) , Anu Koivula (VTT Technical Research Centre of Finland Ltd)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Applied Microbiology And Biotechnology , VOL 104 , PAGES 10515 - 10529

State: Published (Approved)
Published: November 2020

Open Access Open Access

Abstract: In this work, deoxyribose-5-phosphate aldolase (Ec DERA, EC from Escherichia coli was chosen as the protein engineering target for improving the substrate preference towards smaller, non-phosphorylated aldehyde donor substrates, in particular towards acetaldehyde. The initial broad set of mutations was directed to 24 amino acid positions in the active site or in the close vicinity, based on the 3D complex structure of the E. coli DERA wild-type aldolase. The specific activity of the DERA variants containing one to three amino acid mutations was characterised using three different substrates. A novel machine learning (ML) model utilising Gaussian processes and feature learning was applied for the 3rd mutagenesis round to predict new beneficial mutant combinations. This led to the most clear-cut (two- to threefold) improvement in acetaldehyde (C2) addition capability with the concomitant abolishment of the activity towards the natural donor molecule glyceraldehyde-3-phosphate (C3P) as well as the non-phosphorylated equivalent (C3). The Ec DERA variants were also tested on aldol reaction utilising formaldehyde (C1) as the donor. Ec DERA wild-type was shown to be able to carry out this reaction, and furthermore, some of the improved variants on acetaldehyde addition reaction turned out to have also improved activity on formaldehyde.

Journal Keywords: DERA; Aldolase; Protein engineering; Machine learning; Crystal structure determination; C–C bond formation; Biocatalysis

Diamond Keywords: Enzymes

Subject Areas: Biology and Bio-materials, Chemistry, Information and Communication Technology

Instruments: I24-Microfocus Macromolecular Crystallography

Other Facilities: ID30A-1 at ESRF

Added On: 18/11/2020 11:41


Discipline Tags:

Artificial Intelligence Biochemistry Catalysis Information & Communication Technologies Chemistry Structural biology Life Sciences & Biotech

Technical Tags:

Diffraction Macromolecular Crystallography (MX)