Congratulations to Qiushi for winning the Peking University President's Scholarship!
Welcome Linqing and Keji
Lipid scrambling paper online
Our collaborative work with Prof. Ben Corry's lab has been published in J. Chem. Theory Comput. (link). This study reveals that ~20% of membrane proteins exhibit lipid-scrambling behavior in Martini 3 MemProtMD simulations — a 15-fold rise relative to Martini 2.2. Martini 3 overestimates scrambling rates by an average of 66-fold versus Martini 2.2 and deviates from experimental data, even producing spurious scrambling for non-scrambling proteins and closed scramblase conformations. The findings point out critical limitations for investigating lipid-protein interactions, while minor parameter adjustments could eliminate such artificial scrambling and improve model performance. Congratulations to Zhouyu and YC!

Qianli Passes PhD Qualifying Examination
Congratulations to Qianli! She has successfully passed her PhD qualifying exam and will continue her doctoral research in our group.
FoldDoF online
Zefeng's work on the geometric and probabilistic modeling of protein backbones has been published in J. Chem. Inf. Model (link). This study proposed using a concise protein backbone representation and demonstrated peptide units' 3D rotations that unify the angular parts of internal coordinates on a single rotation manifold, composing the primary degrees of freedom of the protein backbone. This representation enables efficient differentiable coordinate conversions, effective conformation optimization ability free from the lever-arm effect, and straightforward geometric reasoning capability within deep neural networks. By integrating it into protein backbone generative models, we achieved enhanced performance in protein design regarding in silico stereochemical quality, diversity, novelty, and length generalizability. We anticipate its future application in advancing biomolecular structure prediction and design. Congratulations!

Qingdao meeting 2026
The 4th National Conference on Biomolecular Structure Prediction and Modeling was held in Qingdao from June 26 to 29, 2026, with several members of our research group in attendance. Jiajun delivered an oral presentation of our latest work, SteerAF: distogram-based steering of AlphaFold2 toward alternative conformations, and was awarded the second prize for oral reports. Ruihan and Qiushi received the third prize in the poster section. We extend our sincere congratulations to both!
PepMCP paper online
Our latest membrane contact probability (MCP) predictor, PepMCP, has been published in Bioinformatics (link). PepMCP is a novel peptide-tailored model that predicts MCP and identifies membrane-lytic antimicrobial peptides (AMPs). We trained PepMCP on data from more than 500 literature-sourced membrane-lytic AMPs. It leverages coarse-grained molecular dynamics simulations to extract residue-level MCP features for model training. PepMCP can also be used in a binary classification mode, enabling efficient identification of membrane-lytic AMPs. The study also releases MemAMPdb, a curated membrane-lytic AMP database, together with a publicly accessible PepMCP web server, to support global academic research. Several group members participated in the research. Ruihan constructed the model, and Tadsanee ran the large-scale MD simulations. Congratulations!
Welcome Yi Ren
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!



