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Local structural motifs mined from the PDB can be used for statistical protein sequence design. Work by Jianfu Zhou, Alexandra Panaitiu, and my Generate Biosciences colleague Gevorg Grigoryan. pnas.org/content/early/…

Honored to see our work on #deeplearning for protein structure prediction featured on the cover of Science Magazine. Research was led by the tremendously talented Minkyung Baek. Article: science.sciencemag.org/content/373/65… Commentary: science.sciencemag.org/content/373/65…

Excited to share our work on "top-down" reinforcement learning based approach to design proteins with exquisite structural control. The Monte Carlo tree search algorithm generate protein monomers and assemblies, guided by input geometric constraints. 1/4 biorxiv.org/content/10.110…

Happy to share our (w/ Teijaro Lab) integrated chemoprotoemic approach to develop functional inhibitors of SLC15A4 - a challenging target that controls some exciting biology

#KnightCampusBioE PhD students Nicholas Pancheri DeShea Chasko Madeline J. Martin David Frey Dieter Karly Mei Fear had loads of fun this week sharing some #Bioengineering knowledge with elementary and middle schoolers and their parents at the S.P.I.C.E open house!

Thank you for hosting us today Oregon State University, great to be able to share our classes in the field of #Bioengineering. Parisa Hosseinzadeh, Adam Higgins, Morgan B Giers, Nick Willett Paul Dalton. Knight Campus students got extra lucky, having our very own captain piloting our vehicle!

Exciting application of #ProteinEngineering in Nature Communications demonstrating an isothermal approach to #PCR. 🤔 Can similar methods be applied to generate libraries by error-prone PCR? Exciting implications for #DirectedEvolution! nature.com/articles/s4146…

え、こんなんいつの間に出てたの。「ESMFoldでprotein design」 Learning inverse folding from millions of predicted structures | bioRxiv biorxiv.org/content/10.110…

West coast or east coast, come find us at ABRCMS #ABRCMS2022 (booth 377) or oSTEM Incorporated #oSTEM2022 (booth T24)! 🌎 We are so excited to share our programs to recruit, train, & support the next generation of diverse leaders in computational protein design! 🖥️🧬⚙️🥼

About 600 compact tertiary motifs can describe 50% of the protein structure universe. 10.1073/pnas.1607178113

EquiFold uses course grain 3D representation of proteins to predict structure faster than AF2. Excited to meet the first author, Jae Hyeon Lee, today! biorxiv.org/content/10.110…

Interested in protein design, deep learning, computational biophysics? Or computational RNA folding, vaccines, enzymes, antibodies, biomaterials, machine learning? Become a Rosetta Commons undergraduate summer intern (U.S. National Science Foundation #REU) or a postbaccalaureate fellow (#RaMP)! [thread!]