CN
Cryo-EM reveals mechanisms of natural RNA multivalency

On March 13, 2025, Zhaoming Su and Xuedong Zhou from Sichuan University, together with Siqi Sun from Fudan University, jointly published a research article online in Science titled...

Structural basis of circularly permuted group II intron self-splicing

January 31, 2025. Congrats to Liu Wang, Jiahao and Chong Zhang on presenting cryo-EM structures of a natural CP intron in different states during back-splicing at a resolution of 2...

RNA sample optimization for cryo-EM analysis

January 31, 2025. Congrats to Liuwang, Jiahao and Chongzhang on presenting an iterative approach of RNA sample optimization for cryo-EM analysis, combined with data processing to r...

The WDR11 complex is a recceptor cargo proteinsfor acidic-cluster-containing

August 8, 2024. Congrats to Guowen on the awesome collaboration with Huaqing, Ping, Yingying and Lin from Da Jia's lab on resolving the cryo-EM structure of WDR11 complex and ...

Cryo-EM reveals dynamics of Tetrahymena group I intron self-splicing

March 23, 2023. Congrats to Bingnan and Chong Zhang resolving six conformations associated with Tetrahymena group I intron self-splicing at 2.84-3.73 Å directly following by in vi...

Structural basis of sRNA RsmZ regulation of Pseudomonas aeruginosa virulence

February 24, 2023. Congrats to Xinyu Zhiling on the awesome collaboration with Yangyuan from Kelei Zhao's of Chengdu University resolving the cryo-EM structure of sRNA RsmZ co...

Cryo-EM structures of full-length Tetrahymena ribozyme at 3.1 Å resolution

The latest research results in the journal Nature—Cryo-EM Structures of Full-Length Tetrahymena Ribozyme at 3.1 Å Resolution published in in the journal Nature.

Welcome to

SuLab!

My research focus is using cryogenic-electron microscopy to provide structural and mechanistic insights of (1) functional non-coding RNAs (ncRNAs) including ribozymes, riboswitches and other bacterial and viral ncRNAs, and (2) pathogenic ribonucleoprotein complexes such as viral nucleocapsid assembly and bacterial sRNAs in complex with their protein partners. With the structural information in hand, we have developed HitSTARS strategy to discover hit small molecules targeting RNA structures. This strategy is empowered by a molecular representation learning (MRL) framework that curates a library of commercial small molecules targeting RNA (CSTAR). The evergrowing RNA structure repertoire will eventually enable accurate predictions of complexed RNA structures, which will make HitSTARS more scalable, advancing our knowledge of RNA-small molecule recognition patterns and accelerating drug discovery against pathogenic RNA targets.


Research