We are delighted to welcome Dr. Yi Ren to the group. Having earned his PhD, he joins us as a postdoctoral researcher. We look forward to his future contributions. Welcome aboard!

Hongyang and Zhouyu successfully completed their undergraduate thesis defenses on May 29 and June 5, 2026, respectively. Congratulations!

Kai defended his PhD viva on May 25, 2026, while Jingze and Lingfeng completed theirs on May 26, 2026. Their defenses proceeded smoothly. Congratulations to all three! The whole group joins in celebrating this wonderful achievement.

Zhongjie has completed his postdoctoral research and left our group to take up a new role. During his time here, he made outstanding contributions to the development of the membrane-aware anisotropic network model (MCP-ANM). He has joined Beijing Sun-Novo Pharmaceutical Research Co., Ltd. as a director of innovative drug research. We wish him every success in his future career.

Our collaborative study with Prof. Xiao-Wei Chen' lab and Prof. Ning Gao' lab has been published online in Molecular Cell (link). Using MD simulations, we uncovered specific phosphatidylinositol (PI)-binding pockets on the Erlin1/2 complex at the ER membrane luminal leaflet. PI binding is critical for the complex’s stability and assembly. Congratulations to Tadsanee!

Zhongjie's work on membrane protein dynamics has been published in PRX Life (link). The study introduces MCP-ANM, a membrane-aware anisotropic network model that incorporates membrane contact probability (MCP) to better describe membrane-induced constraints in protein dynamics. The method significantly improves flexibility prediction for membrane proteins compared with conventional ANM approaches. By integrating MCP-ANM with perturbation response scanning (PRS), the framework efficiently simulates mechanosensitive gating mechanisms, reproducing both force-from-lipids (e.g., MscS, PIEZO) and force-from-tether (e.g., NOMPC) models. The predicted mechanosensitivity agrees with experimental observations, while requiring only seconds to minutes per system. Congratulations!

Prof. Chen Song, along with YC, Kai, and Jingze, attended the BPS2026 meeting held in San Francisco, USA, from February 21 to 25, 2026. At the conference, they presented and discussed our recent work on ProtRAP-LM, RAPFold, as well as the molecular mechanics studies of the ion channels (including NOMPC and CaV1 channel).

Lei and Kai’s work on ProtRAP-LM has been published in Genom. Proteom. Bioinform. (link). The study introduces ProtRAP-LM, a transformer-based model that uses protein language model embeddings to rapidly and accurately predict membrane contact probability (MCP) and relative accessibility for each residue within a given protein sequence. ProtRAP-LM achieves a speed-up of over 300 times compared to MSA-based MCP predictor, enabling proteome-wide predictions within hours. This facilitates large-scale analysis of challenging membrane protein classes, including single-pass transmembrane proteins, membrane-anchored proteins, and β-sheet-containing membrane proteins. In particular, this study provides a comprehensive list of membrane proteins across 48 proteomes, including 78 potential human membrane proteins, offering a valuable resource for future structural and functional studies. An online server is available at http://www.songlab.cn/ProtRAP-LM/home/. Congratulations!

Jun's MemConverter work has been published in J. Chem. Theory Comput. (link). MemConverter is a computational pipeline for converting soluble proteins to membrane proteins — and vice versa. Guided by membrane contact probability (MCP), the method iteratively couples MemProtMPNN or SolubleMPNN with AlphaFold2 prediction, enabling automated and data-driven engineering of proteins to adapt to membrane or aqueous environments. MD simulations was conducted by Haozhe. Congratulations!

Tadsanee has finished her postdoctoral training and moved to Peter J. Bond's lab at A*STAR Bioinformatics Institute. She did excellent work on MD simulations of the Erlin1/2 complex and membrane-lytic antimicrobial peptides. All the best for her new journey!