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Christopher Frank
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Christopher Frank
@chrisfrank662
De novo Protein Designer DNA Origami wizzard I like lifting rocks PhD from @TU_Muenchen
Hallbergmoos
Joined June 2013
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    Christopher Frank
    @chrisfrank662
    Oct 24, 2024
    Finally, out in @ScienceMagazine today, our work on de novo protein design. Together with @HattoriLab , @sokrypton & @hendrik_dietz we showed how we can drastically improve AF2 based hallucination, surpassing, or reaching SOTA diffusion models doi.org/10.1126/scienc…
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    Christopher Frank
    @chrisfrank662
    Feb 26, 2023
    Roughly one year ago we started out venturing in the world of #proteindesign. Today I am very happy to share our first preprint ‘Efficient and scaleable de-novo protein design using a relaxed sequence space’ (biorxiv.org/content/10.110…) with @sokrypton & @hendrik_dietz 1/x
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    biorxiv.org
    Efficient and scalable de novo protein design using a relaxed sequence space
    Deep learning techniques are being used to design new proteins by creating target backbone geometries and finding sequences that can fold into those shapes. While methods like ProteinMPNN provide an...
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    Christopher Frank
    @chrisfrank662
    Jun 1, 2022
    Replying to @KaHochberg
    Might be worth considering PNAS as a well suited publishing choice 😅
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    Christopher Frank
    @chrisfrank662
    Nov 22, 2024
    After showing that AF2 can be used to design very large proteins by performing #RSO, I am happy to share another fun project we did: the #af2cycler @sokrypton @hendrik_dietz
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    biorxiv.org
    Alphafold2 refinement improves designability of large de novo proteins
    Recent advances in computational protein design have enabled the creation of novel proteins for a variety of purposes. The capability for producing custom-shape high-quality backbones for very large...
    20K
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    Christopher Frank
    @chrisfrank662
    Apr 27, 2023
    Great work! Congratulations to all authors! Also very nice GitHub page providing the code 🥳
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    Michael Bronstein
    @mmbronstein
    Apr 26, 2023
    Our paper with @befcorreia @CirauquiPablo et al on protein design using geometric deep learning is finally in @Nature We show experimental results of diverse de novo designed binders nature.com/articles/s4158…
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    Christopher Frank
    @chrisfrank662
    Sep 22, 2022
    Me one year ago: *Happy about my first few Alphafold predictions* Me now: *Casually predicts 60.000 sequences over the weekend* Its unbelievable how fast the field advances. Just imagine what will be possible in a few years
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    Christopher Frank
    @chrisfrank662
    Apr 25, 2023
    Finally got this new bad boys installed 🥳 May the CUDA installation be easy and the designed proteins fold well 😅
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    Christopher Frank
    @chrisfrank662
    Mar 30, 2023
    This is so awesome! Thanks so much for sharing and the awesome description in the Git🥳 It seems like we are more and more shifting from 'how to design' to 'what to design' 💪
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    In this animation, RF Diffusion generates a new protein (orange) that binds to the insulin receptor (blue).
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    Institute for Protein Design
    @UWproteindesign
    Mar 30, 2023
    Today we're making RF Diffusion, our guided diffusion model for protein design with potential applications in medicine, vaccines & advanced materials, free to use. The software has proven much faster and more capable than prior protein design tools. bakerlab.org/2023/03/30/rf-…
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    Christopher Frank
    @chrisfrank662
    Dec 14, 2022
    At this point I think its actually easier, faster and more convenient to de-novo design a protein binder then to generate an antibody #RFDiffusion
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    Christopher Frank
    @chrisfrank662
    Nov 1, 2022
    There you go my little bacteria 🦠 As always: may the hallucinated protein be soluble, the yield high and not accidentally super toxic to humans 😅🙌
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    Christopher Frank
    @chrisfrank662
    Oct 21, 2022
    Why ProteinMPNN, why? 😅
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    Christopher Frank
    @chrisfrank662
    Dec 9, 2024
    I somebody up to date about the legal aspect of redesigning existing antibodies etc? Just wondering how dis-similar a sequence needs to be, to be able to be used again? Nevertheless, the results are 🔥🚀
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    Adaptyv Bio
    @adaptyvbio
    Dec 7, 2024
    PROTEIN DESIGN COMPETITION ROUND 2 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
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    Christopher Frank
    @chrisfrank662
    Feb 25, 2024
    Awesome! This is in line with what we saw further investigating this method! More to come soon 🥳
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    Motoyuki Hattori (服部素之)
    @HattoriLab
    Feb 25, 2024
    We recently tested this notebook. The predicted and experimental structures are well consistent! We highly recommend this, as well as the one for RFdiffusion, as excellent options for everybody to start de novo protein design!
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    Christopher Frank
    @chrisfrank662
    Dec 12, 2022
    Replying to @stephanie_mul @generate_biomed and 2 others
    Only our #ColabDiffusion 😉
    colab.research.google.com
    af_pseudo_diffusion_dgram.ipynb
    Run, share, and edit Python notebooks

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