Study: Enzyme engineering made easy using artificial intelligence

In a new study, Osaka University researchers have imparted a similar level of adaptability to enzymes, a goal that has remained elusive for more than 30 years. The study’s findings were recently published in ACS Synthetic Biology.

Enzymes perform amazing functions made possible by the unique arrangement of their constituent amino acids, but usually only in a specific cellular environment. When you change the cellular environment, the enzyme rarely works well – if at all. Thus, a long-standing research goal has been to preserve or even improve enzyme activity in various environments; for example, conditions favorable to the production of biofuels. Traditionally, such work involved extensive experimental trial and error, which may not have ensured the achievement of an optimal result.

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Artificial intelligence (a computer-aided tool) can minimize this trial and error, but still relies on experimentally obtained crystal structures of enzymes—which may be inaccessible or not particularly useful. Thus, “the corresponding amino acids that should be mutated in the enzyme can only be a best guess,” says Teppei Niide, co-author. “To solve this problem, we devised an amino acid classification methodology that depends only on the widely available amino acid sequence of analogous enzymes from other living species.” The researchers focused on the amino acids involved in the specificity of the malic enzyme to the molecule that the enzyme transforms (i.e., the substrate) and the substance that helps the transformation continue (i.e., the cofactor). By identifying amino acid sequences that have not changed over the course of evolution, researchers have identified amino acid mutations that are adaptations to different cellular conditions in other species.

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“Using artificial intelligence, we identified unexpected amino acid residues in the malic enzyme that correspond to the use of different redox cofactors of the enzyme,” says Hiroshi Shimizu, co-author. “This has helped us understand the mechanism of substrate specificity of the enzyme and will facilitate optimal engineering of the enzyme in laboratories.” This work was able to use artificial intelligence to dramatically accelerate and improve the success of essential reconfiguration of a specific enzyme mode of action without significantly altering enzyme function.

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Future advances in enzyme engineering will greatly benefit fields such as pharmaceutical production and biofuel production, which require careful adaptation of enzyme versatility to different biochemical environments – even in the absence of suitable enzyme crystal structures. (IS NOT IT)

(This story has not been edited by Devdiscourse staff and is automatically generated from an aggregated feed.)

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