Sets of limited amino acid species for reconstruction of protein sequences before the last common ancestor

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K19831
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 62:Applied informatics and related fields
• Research Institution: Waseda University
• Principal Investigator: Kiga Daisuke 早稲田大学, 理工学術院, 教授 (30376587)
• Project Period (FY): 2021-07-09 – 2023-03-31
• Keywords: 遺伝暗号 / 合成生物学 / 進化 / 祖先配列 / 系統樹

Outline of Final Research Achievements

In this study, ancestral protein sequences were inferred by informatics methods for proteins that function on a set of amino acids before the last common ancestor of life, and such proteins were also evaluated in biological experiments. It was shown that combining classical ancestral sequence reconstruction methods and variational autoencoders that consider residue-residue interactions can identify more active ancestral sequences. In addition, experiments mimicking the evolution of a protein composed of 16 different amino acids were also performed, showing the possibility of obtaining variants with new activity. This research introduces a new informatics approach to understanding the origin of proteins and provides a basis for creating proteins with industrial applications.

Free Research Field

合成生物学

Academic Significance and Societal Importance of the Research Achievements

この研究の学術的意義は、進化の初期段階でのタンパク質の機能形成を解明することにある。従来の祖先配列推定法の限界を超え、新たな情報科学的手法を導入することで、生命の起源に関する理論を進展させた。また、機械学習を生命起源研究に応用することで、共通祖先の壁を越えて、進化の過程でどのようにしてタンパク質の活性が向上していったかを理解する新たな視点を提供した。社会的には、これらの知見は医学や生物工学の分野において、より効率的で安全なタンパク質設計や新薬の開発に貢献する可能性が高い。