Siirola, Elina Maria, Snajdrova, Radka, Lutz, Stefan, Braun, Markus, Gruber, Christian, Krassnigg, Andreas, Kummer, Arkadij and Oberdorfer, Gustav (2023) Accelerating Biocatalysis Discovery with Machine Learning: A New Era in Enzyme Engineering new title based on editors feedback: Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design. ACS Catalysis, 13 (21). pp. 14454-14469.

Abstract

New emerging computational tools promise to revolutionize protein engineering for biocatalysis application and accelerate the development timelines previously needed to optimize an enzyme to its more efficient variant. For over a decade, the benefits of predictive algorithms have helped scientists and engineers to navigate the complexity of functional protein sequence space. More recently, spurred by dramatic advances in underlying computational tools, the promise of faster, cheaper, and more accurate enzyme identification, characterization and engineering has catapulted terms such as artificial intelligence and machine learning to the must-have vocabulary in the field. This perspective aims to discuss and also to celebrate these innovative new approaches in protein science by highlighting their potential on selected recent developments and applications and offering thoughts on future opportunities. It also critically assesses the technology’s limitations, unanswered questions and unmet challenges.

Item Type:	Article
Date Deposited:	19 Dec 2023 00:45
Last Modified:	19 Dec 2023 00:45
URI:	https://oak.novartis.com/id/eprint/51216