X. Liu, J. Lu, L. Jia, D. Xia, J. Huang, Y. Chen, M. Li, Y. Chen, X. Liu, G. Li, W. Liu, J. Li, J. Ying, Y. Wang, Z. Li, X. Tong, Y. Hou, Z. E, J. Zhang, J. Zhang
Protein protein interactions (PPIs) play a crucial role in enabling proteins to carry out their functions within various biological processes. Rice, as a key model organism in plant biological studies, has been at the forefront of PPI research. However, most PPI datasets in rice stem from computational predictions, while experiment-based rice PPI datasets are fragmented due to the lack of systematic profiling at the rice PPIome level, which largely hinders information sharing in the rice research community. In previous research, we constructed the Port of Protein-Protein Interactomes (POPPIN; https://riceome.hzau.edu.cn/poppin/), an integrated database dedicated to sharing experimentally verified 150,451 PPIs and functional clues in rice. Empowered by high-throughput PPIome profiling technologies and text mining assisted by a large language model. Additionally, POPPIN provides detailed protein information, including GO annotations, subcellular localizations, domains, trait ontology (TO) information, and hyperlinks to external biological databases. Through offering a user-friendly web interface for search and dynamic network visualization, POPPIN serves as the first large-scale, experiment-based database for searchable PPIs in rice.