酶祖先序列重建与定向进化

Translated title of the contribution: Enzyme ancestral sequence reconstruction and directed evolution

Kun Zhang, Yifei Dai, Jindi Sun, Jiachen Lu, Kequan Chen

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

The amino acid sequence of ancestral enzymes from extinct organisms can be deduced through in silico approach termed ancestral sequence reconstruction (ASR). ASR usually has six steps, which are the collection of nucleic acid/amino acid sequences of modern enzymes, multiple sequence alignment, phylogenetic tree construction, computational deduction of ancestral enzyme sequence, gene cloning, and characterization of enzyme properties. This method is widely used to study the adaptation and evolution mechanism of molecules to the changing environmental conditions on planetary time scale. As enzymes play key roles in biocatalysis, this method has become a powerful method for studying the relationship among the sequence, structure, and function of enzymes. Notably, most of the ancestral enzymes show better temperature stability and mutation stability, making them ideal protein scaffolds for further directed evolution. This article summarizes the computer algorithms, applications, and commonly used computer software of ASR, and discusses the potential application in directed evolution of enzymes.

Translated title of the contributionEnzyme ancestral sequence reconstruction and directed evolution
Original languageChinese (Traditional)
Pages (from-to)4187-4200
Number of pages14
JournalShengwu Gongcheng Xuebao/Chinese Journal of Biotechnology
Volume37
Issue number12
DOIs
StatePublished - 25 Dec 2021

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