Genomics refined: AI-powered perspectives on structural analysis

Yi Lou; Zixin Deng; Jiangtao Gao

doi:10.1016/j.tplants.2023.10.005

Genomics refined: AI-powered perspectives on structural analysis

Trends Plant Sci. 2024 Feb;29(2):123-125. doi: 10.1016/j.tplants.2023.10.005. Epub 2023 Oct 10.

Authors

Yi Lou¹, Zixin Deng², Jiangtao Gao³

Affiliations

¹ Key Laboratory of Biopesticide and Chemical Biology of Ministry of Education, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
² State Key Laboratory of Microbial Metabolism, Joint International Laboratory on Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China.
³ Key Laboratory of Biopesticide and Chemical Biology of Ministry of Education, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China. Electronic address: jgaotao@gmail.com.

PMID: 37827897
DOI: 10.1016/j.tplants.2023.10.005

Abstract

Understanding protein function by deciphering 3D structure has distinct limitations. A recent study by Huang et al. used AlphaFold2, an artificial intelligence (AI) protein-folding prediction model, to predict and classify deaminase proteins based on structural similarities, highlighting the untapped potential of AI in functional genomics and protein engineering.

MeSH terms

Artificial Intelligence*
Genomics*