Protein Design Competition - RESULTS
The long awaited results are here -- and they don’t disappoint!
The long awaited results are here -- and they don’t disappoint!
📈 We doubled the number of proteins we tested in our lab from 200 to 400!
🧬 Out of those 400 proteins, 378 expressed (95% expression rate!)
🚀 Out of those 378 expressed proteins, 53 did successfully bind the target protein EGFR (that’s a 14% success rate, more than 5x of the success rate of the previous round just 2 months ago!)
💪 The best binders reached single-digit nanomolar affinities which is within the range of the commercially sold Cetuximab antibody by Merck
😎 30 out of 130 protein designers managed to design at least one binding protein
Want to join the discussion about the results?
Check out the thread on X or on LinkedIn
Here’s the breakdown:
The team at Cradle takes the top spot in terms of binding affinity by using their protein language models to introduce 10 mutations into the framework regions of the Cetuximab antibody.
This way, they generated an scFv with a KD of 1.2 nM which is lower than the original Cetuximab scFv. Congrats!
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Tihumab aka Chris Xu aka Xushaoyong (https://lnkd.in/e8Mj8eq3) lands two of his nanobodies on rank 2 & 3 using his antibody humanization technique.
The pipeline consist of CDR grafting, iterative optimization using a deep learning model, antigen-antibody complex prediction and developability index prediction.
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Aurelia Bustos MD, PhD's approach of modifying the TGFa protein with diffusion models to yield an optimized binder for EGFR was already super successful in our computational ranking, with 8 out of her 10 designs landing in the top 25.
This turned out to be also successful in the lab, with all 8 of those binders working!
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Also in the top 10:
- Jeff Vogt with his scFv optimization pipeline
- Lennart Nickel using BindCraft to generate fully de novo binders
- Brian Naughton and Alan Blakely who both had the idea of using a linker approach to combine binders from previous rounds
- Shosuke Suzuki's de novo binder
- Yoichi Kurumida’s RFdiffusion scaffolded binder
- Young Su Ko who’s using Raygun+Protrek to filter his sequences
Congrats to everyone that ended up designing one or more of those binders and thanks to everyone that participated!
We loved reading about all those interesting design approaches and tried to give as many shoutouts as possible. The energy in the protein design community is truly amazing and we can’t wait to see how many more cool proteins you'll all be designing in the future!