Bioinformatics analysis of enzyme systems can provide key insight and direction to better understand the chemical effects that structural features confer to the enzyme as a whole. Ancestral sequence reconstruction has been experimentally shown to be capable of generating VHPOs that represent common ancestors of extant forms, and that they generally follow expected evolutionary patterns based on clade distributions. From experimental data, N177 has been shown to be more stable and promiscuous than its characterized descendants, making it a valuable target for further investigation in protein engineering.
A future experiment in protein engineering would be to use error-prone PCR on N177 to reintroduce mutations that could evolve it to act on more unique substrates, such as antibiotic precursor molecules. This would enable simpler and more efficient synthesis of complex and relevant compounds.
Acknowledgements
Professor Shaun McKinnie
Dr. Jin Feng
Dr. Manasa Ramachandra
Dr. Jackson Baumgartner
Dr. Austin Hopiavuori
Jennifer Cordoza
Radcliff Huffman
Lia Lozano Salazar
Christine Lee
Sarah Kreeger
Ananya Manjunath
Surina Beal
Jack Hanson
Thank you to
The Koret foundation
and UC Santa Cruz
References
Prakinee, Kridsadakorn, Suppalak Phaisan, Sirus Kongjaroon, and Pimchai Chaiyen. “Ancestral Sequence Reconstruction for Designing Biocatalysts and Investigating Their Functional Mechanisms.” JACS Au, October 25, 2024. https://doi.org/10.1021/jacsau.4c00653.
Musil, Milos, Rayyan Tariq Khan, Andy Beier, Jan Stourac, Hannes Konegger, Jiri Damborsky, and David Bednar. “FireProtASR: A Web Server for Fully Automated Ancestral Sequence Reconstruction.” Briefings in Bioinformatics 22, no. 4 (July 1, 2021): bbaa337. https://doi.org/10.1093/bib/bbaa337.