Ancestral Sequence Reconstruction for Designing Biocatalysts and Investigating their Functional Mechanisms
Kridsadakorn Prakinee, Suppalak Phaisan, Sirus Kongjaroon, Pimchai Chaiyen
Abstract
Biocatalysis has emerged as a green approach for efficient and sustainable production in various industries. In recent decades, numerous advancements in computational and predictive approaches, including ancestral sequence reconstruction (ASR) have sparked a new wave for protein engineers to improve and expand biocatalyst capabilities. ASR is an evolution-based strategy that uses phylogenetic relationships among homologous extant sequences to probabilistically infer the most likely ancestral sequences. It has proven to be a powerful tool with applications ranging from creating highly stable enzymes for direct applications to preparing moderately active robust protein scaffolds for further enzyme engineering. Intriguingly, it can also provide insights into fundamental aspects that are challenging to study with extant (current) enzymes. This Perspective discusses a practical strategy for guiding enzyme engineers on how to embrace ASR as a practical or associated protocol for protein engineering and highlights recent examples of using ASR in various applications, including increasing thermostability, expanding promiscuity, fine-tuning selectivity and function, and investigating mechanistic and evolution aspects. We believe that the use of the ASR approach will continue to contribute to the ongoing development of the biocatalysis field. We have been in a "golden era" for biocatalysis in which numerous useful enzymes have been developed through many waves of enzyme engineering via advancements in computational methodologies.