We have developed a cysteine-free, highly thermostable tagging system, UTag, that enables single-mRNA translation tracking in live cells. You may wonder how different tagging systems affect translation kinetics—we addressed this by performing a systematic comparison.

New preprint from our lab, led by Luis Aguilera! We have developed an open-source software, "MicroLive," to track single molecules in live cells. This one-step platform enables researchers without coding experience to perform single-molecule studies in a user-friendly interface!

Imaging single endogenous RNA in live cells comes true!

Visualizing RNA in live cells using CRISPR @DoudnaLab @NatureBiotech nature.com/articles/s41587-0…

IgGM: A Generative Model for Functional Antibody and Nanobody Design 1/ IgGM is a novel generative model designed to facilitate the de novo design of antibodies and nanobodies with functional specificity, focusing on their ability to bind specific antigens. This model uniquely generates both the sequences and structures of antibodies in a single step. 2/ The model consists of three main components: a pre-trained language model that extracts sequence features, a feature learning module to identify relevant features, and a prediction module to generate antibody sequences and predict the antibody-antigen complex structure. 3/ IgGM addresses a major challenge in antibody design by generating novel antibody sequences and their structures without the need for existing experimental antibody-antigen complex structures, making it suitable for scenarios involving new antigens. 4/ The model is capable of designing antibody CDR regions, which are crucial for antigen binding, and can also predict and design entire antibody structures, a significant advancement over existing methods that often require pre-existing structures or templates. 5/ IgGM excels in both antibody and nanobody design tasks, achieving superior performance in multiple design scenarios, such as generating antibodies with high specificity and binding affinity to antigens, outperforming previous methods in terms of sequence and structure fidelity. 6/ Its ability to design antibodies and nanobodies for specific epitopes, including the design of multiple CDR regions simultaneously, provides a versatile solution for therapeutic and diagnostic applications. 7/ Experimental results demonstrate IgGM's impressive accuracy, including higher success rates in docking performance and lower RMSD values compared to existing methods, showcasing its potential in the rapidly growing field of AI-driven drug design. 💻Code: github.com/TencentAI4S/IgGM 📜Paper: biorxiv.org/content/10.1101/… #AntibodyDesign #NanobodyDesign #GenerativeModels #MachineLearning #AIinHealthcare #DrugDiscovery #Bioinformatics #ComputationalBiology #DeepLearning #AIforMedicine #ProteinDesign

Emergency town hall at #BPS2025 Impact of U.S. policies on biophysics research and what you can do about it. Tuesday, February 18 1:30 pm - 3:30 pm Room 411

Making intrabodies from antibodies just got easier! Learn how we made 𝟭𝟵 intrabodies to bind and light up peptides and histone modifications in live cells. And thanks to Academia, all sequences are freely available. (video credit: Yuko Sato @YukoSatoT2) biorxiv.org/content/10.1101/…

The first review paper from the Zhao lab is out today! This is a comprehensive review of not only tool development but also novel discoveries in translation. #CU_BMG #Biochem_Journal #NewPI Expanding the tagging toolbox for visualizing translation live portlandpress.com/biochemj/a…

A big surprise from my lab! Happy Chinese New Year!

We had a great time at MOLB retreat! Presented our work in ancient Greece themed costumes and sumitted Twin Cones in Winter Park. Thanks for organizing this fatastic retreat and hiking! @molbcu @prekerislab

We're ready for the spooky season!

Postdoc candidates, we'd love to "CU" here!

Beautiful work from the Stasevich lab! Imaging the full central dogma.@tim_stasevich

Cannot agree more!

Excited to share the work on single-molecule translation imaging of C9ORF72 repetitive RNA, spearheaded by @GosiaJl , Shaopeng Wang, and Daoyuan Dong, in collaboration with @shuying_sun, , @NingInScience , @tim_stasevich , now published on Nat Comm: nature.com/articles/s41467-0…

CSU is hiring! Great science and colleagues!