Exploiting enzyme evolution for computational protein design

Summary, in English

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies.

• Author: Gaspar P Pinto; Marina Corbella; Andrey O Demkiv; Shina Caroline Lynn Kamerlin
• Publishing year: 2022-05
• Language: English
• Pages: 375-389
• Publication/Series: Trends in Biochemical Sciences
• Volume: 47
• Issue: 5
• Links: http://dx.doi.org/10.1016/j.tibs.2021.08.008
• Document type: Journal article review
• Publisher: Elsevier
• Keywords: Computational Biology; Evolution, Molecular; Proteins/genetics
• Status: Published
• ISBN/ISSN/Other: ISSN: 0968-0004