REME: an integrated platform for reaction enzyme mining and evaluation

Author:

Shi Zhenkun1,Wang Dehang12,Li Yang13,Deng Rui12,Lin Jiawei12,Liu Cui1,Li Haoran1,Wang Ruoyu1,Zhao Muqiang1,Mao Zhitao1ORCID,Yuan Qianqian1,Liao Xiaoping14ORCID,Ma Hongwu1ORCID

Affiliation:

1. Biodesign Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences , Tianjin 300308, PR China

2. College of Biotechnology, Tianjin University of Science and Technology , Tianjin 300457, PR China

3. University of Chinese Academy of Sciences , Beijing 101408, PR China

4. Haihe Laboratory of Synthetic Biology , Tianjin 300308, PR China

Abstract

Abstract A key challenge in pathway design is finding proper enzymes that can be engineered to catalyze a non-natural reaction. Although existing tools can identify potential enzymes based on similar reactions, these tools encounter several issues. Firstly, the calculated similar reactions may not even have the same reaction type. Secondly, the associated enzymes are often numerous and identifying the most promising candidate enzymes is difficult due to the lack of data for evaluation. Thirdly, existing web tools do not provide interactive functions that enable users to fine-tune results based on their expertise. Here, we present REME (https://reme.biodesign.ac.cn/), the first integrated web platform for reaction enzyme mining and evaluation. Combining atom-to-atom mapping, atom type change identification, and reaction similarity calculation enables quick ranking and visualization of reactions similar to an objective non-natural reaction. Additional functionality enables users to filter similar reactions by their specified functional groups and candidate enzymes can be further filtered (e.g. by organisms) or expanded by Enzyme Commission number (EC) or sequence homology. Afterward, enzyme attributes (such as kcat, Km, optimal temperature and pH) can be assessed with deep learning-based methods, facilitating the swift identification of potential enzymes that can catalyze the non-natural reaction.

Funder

Strategic Priority Research Program of the Chinese Academy of Sciences

National Natural Science Foundation of China

Tianjin Synthetic Biotechnology Innovation Capacity Improvement

Haihe Laboratory of Synthetic Biology

Publisher

Oxford University Press (OUP)

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