Utilizing an artificial intelligence system to build the digital structural proteome of reef-building corals

Yunchi Zhu; Xin Liao; Tingyu Han; J-Y Chen; Chunpeng He; Zuhong Lu

doi:10.1093/gigascience/giac117

Utilizing an artificial intelligence system to build the digital structural proteome of reef-building corals

Gigascience. 2022 Nov 18:11:giac117. doi: 10.1093/gigascience/giac117.

Authors

Yunchi Zhu¹, Xin Liao², Tingyu Han¹, J-Y Chen³, Chunpeng He¹, Zuhong Lu¹

Affiliations

¹ State Key Laboratory of Bioelectronics, Southeast University, Nanjing, Jiangsu, 210096, China.
² Guangxi Key Lab of Mangrove Conservation and Utilization, Guangxi Mangrove Research Center, Guangxi Academy of Sciences, Beihai 536000, China.
³ Nanjing Institute of Paleontology and Geology, Chinese Academy of Sciences, Nanjing 210008, China.

Abstract

Background: Reef-building corals play an important role in the marine ecosystem, and analyzing their proteomes from a structural perspective will exert positive effects on exploring their biology. Here we integrated mass spectrometry with newly published ColabFold to obtain digital structural proteomes of dominant reef-building corals.

Results: Of the 8,382 homologous proteins in Acropora muricata, Montipora foliosa, and Pocillopora verrucosa identified, 8,166 received predicted structures after about 4,060 GPU hours of computation. The resulting dataset covers 83.6% of residues with a confident prediction, while 25.9% have very high confidence.

Conclusions: Our work provides insight-worthy predictions for coral research, confirms the reliability of ColabFold in practice, and is expected to be a reference case in the impending high-throughput era of structural proteomics.

Keywords: ColabFold; reef-building coral; structural proteomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Anthozoa*
Artificial Intelligence
Coral Reefs
Ecosystem
Proteome
Reproducibility of Results

Substances

Proteome