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The Kuhlman Lab
We are focusing on a variety of design goals including the creation of novel protein structures, complexes, switches, and vaccines. Currently, there is tremendous excitement in our field because of recent advances in deep learning (AlphaFold, etc…). We are incorporating these tools into our design pipeline as well as training new neural network models for protein design tasks. We are longstanding members of the RosettaCommons and have made numerous contributions to Rosetta (a molecular modeling program for protein design and structure prediction).
Recent Highlights
Predicting mutation effects on protein stability
Transfer learning to leverage larger datasets for improved prediction of protein stability changes. Proc Natl Acad Sci U S A. 2024 Dieckhaus H, Brocidiacono M, Randolph NZ, Kuhlman B. Amino acid mutations that lower a protein’s thermodynamic stability are implicated … Read more
Dengue Engineering
Science Advances, 2021 Designed, highly expressing, thermostable dengue virus 2 envelope protein dimers elicit quaternary epitope antibodies Stephan Kudlacek, Stefan Metz, …. , Aravinda de Silva, Brian Kuhlman Dengue virus (DENV) is a worldwide health burden, and a safe … Read more
Enzyme Turbocharging
Nature Chemical Biology, 2023, 19(4):460-467 Designer installation of a substrate recruitment domain to tailor enzyme specificity. Park R, Ongpipattanakul C, Nair SK, Bowers AA, Kuhlman B. Promiscuous enzymes that modify peptides and proteins are powerful tools for labeling biomolecules; … Read more
Light Controllable Nuclear Export
Nat Chem Biol. 2016 Apr 18 Light-induced nuclear export reveals rapid dynamics of epigenetic modifications. Yumerefendi H, Lerner AM, Zimmerman SP, Hahn K, Bear JE, Strahl BD, Kuhlman B. We engineered a photoactivatable system for rapidly and reversibly exporting proteins from … Read more