Curse and Blessing of Non-proteinogenic Parts in Computational Enzyme Engineering


Enzyme engineering aims to improve or install a new function in biocatalysts for applications ranging from chemical synthesis to biomedicine. For decades, computational techniques have been developed to predict the effect of protein changes and design new enzymes. However, these techniques may have been optimized to deal with proteins composed of the standard amino acid alphabet, while the function of many enzymes relies on non-proteogenic parts like cofactors, nucleic acids, and post-translational modifications. Enzyme systems containing such molecules might be handled or modeled improperly by computational tools, and thus be unsuitable, or require additional tweaking, parameterization, or preparation. In this review, we give an overview of common and recent tools and workflows available to computational enzyme engineers. We highlight the various pitfalls that come with including non-proteogenic compounds in computations and outline potential ways to address common issues. Finally, we showcase successful examples from literature that computationally engineered such enzymes.

Kerlen T. Korbeld
Kerlen T. Korbeld
PhD student

Kerlen Korbeld joined the lab in August 2022. He is the first member to join Max in the Fürstlab.

Maximilian JLJ Fürst
Maximilian JLJ Fürst
Assistant Professor of Computational Protein Design

I research computational protein design and high-throughput protein engineering.