1000 likes and I get Fable bio access

The scores don’t pick your binders. The filters don't care either. The assay does. I worked with a design partner to produce true de-novo hits to 2 immuno-oncology targets. ~1,500 de novo designs → 96 synthesized → 89 run on SPR → 5 confirmed binders; 19–195 nM No library. No starting binder. Pure de-novo goodness. This minibinder campaign produced real binders. Validated at AdaptyvBio using cell free production and SPR It does not mean “binders are solved.” It means the design-build-test loop is working. This is why we’re building Fabricagen. I believe there is more to do and soon I will share what I have been working on. DMs open; Looking for design partners and collaborators with hard problems

Yes technically, Mike 😂 🙏🏿I’m so proud of @JaboroLaurence & @McgregoryG21428 the cofounders of @PDForAfrica. It’s been a treat collaborating. Plus a big thank you to @CotetTudor & Daniel at Adaptyv for characterizing our group’s designs 🫶🏿 we’ll release the full dataset models.

Finally got the BDBV Trimer folded properly using esmfold2!

I’m proud to be speaking alongside Dr Muk @steamulater Please register to attend this free seminar on June 4!

Today we're announcing ESMFold2, an open scientific engine to power prediction, design, and discovery across protein biology. The new model delivers state of the art performance on protein interactions, especially antibodies, a critical modality for therapeutics. We have designed and validated miniprotein binders and single chain antibodies across five therapeutic targets that are important in cancer and immunology. We are seeing very high success rates, and affinities at levels consistent with therapeutic activity. We’re also releasing an atlas of 6.8 billion proteins, and 1.1 billion predicted structures. ESMFold2 is built on a state of the art language model that has been trained on billions of protein sequences. A world model of protein biology emerges through language modeling. We’ve used the techniques of mechanistic interpretability developed to understand large language models to understand the concepts ESM uses to represent proteins. The model’s representation space has a compositional organization of features across scales, levels of complexity, and abstraction, that reflects and mirrors the understanding of protein biology developed through a century of empirical science. This understanding emerges without prior knowledge, just from language modeling of protein sequences. Language models are becoming a powerful substrate to understand and program biology. The design of protein interactions is one of the most fundamental problems in biophysics, and has critical implications for the discovery of new medicines. A simple gradient based search with the model was able to discover high-affinity protein binders. I'm excited by the potential this has to accelerate basic science and the understanding of proteins. And especially for the new avenues it opens up for therapeutic design and medicine.

Exited to try out my new plasmids from @ATinyGreenCell Thank you Binomica Labs!

You can see the patent cliff here in action Revenues in the white bars for most major companies imply a 50-80% drop in the next few years Someone is going to have to fund the next generation of biotech startups for drug discovery so these mature companies can consume and commercialize them Should be an interesting few years imo This is why some of these names are trying to diversify their portfolios into Chinese drugs (particularly bsmAbs or other modalities) There aren’t enough competitive drugs coming out of the west. Anyone can make a pretty good bispec or ADC now it seems. China can make hundreds of candidates allowing big Pharma to have their pick of the litter. The west should focus on what we have always been good at - innovation and new platforms We may need to let the traditional paths to drugs get consumed by less innovative rival nations. The innovation gap in biotech is closing quickly and could look like the AI gap (K2 vs GPT) if we don’t do something about it right now.

Dude I’m so >fucking< psyched about these new models I have built and am testing in silico. After >>100,000 designed proteins using OS stacks for clients and myself I have gone my own way and built new combinations of architectures to produce something totally different. Something like 13 different pivots (🫠) - have the logs to prove it >50 cloud training runs to get here (I learned so much along the way) I built: Something like what I wished existed already Something like a hybridoma on a chip Something Pharma grade imo First class features I hand built into the stack and curated from my real drug discovery experiences: 1. Antigen awareness across the model stack - multiple structure and sequence models wired together intelligently 2. Real developability awareness - no crazy WFY fractions or poly A mess 3. Real frameworks - over 10k real frameworks from real biologically derived proteins are used in training and inference 4. No hallucinated spaghetti sequences - they fold because they’re based on natural proteins 5. Canonical residue preservation across design specs and antigen selection - no missing cys no abhorrent P or W residues 6. Actual VHH and antibodies (fragment designs and intact) which look super interesting (read natural) 7. Real levers to pull and modify the inference not just temperature and steps (though we have that too 😘). More on this later. Working on a test set to send to a CRO then publish the preprint and code to get feedback. I think people will like this a lot. I love where it’s going.

Fabricagen’s first summer Intern started today. We have something really fun cooking. He’s a system engineer who placed in a recent academic competition at uni He approached me to advise on that project and we just kept rolling Super smart young man and easy to work with We are going to take a currently available OS protein tool to the next level and rerelease under MIT with new levers to pull Looking forward to sharing our progress later in the summer

The model stack are training signal is really trending nicely Something new is coming Looking around at real lab spaces Someone is working with me now He and I are applying for some funding Intern starts next week too He is working on a cool OS project I hope to share end of summer I haven’t been posting as much because I’m so nose down but it’s going to be worth it

I just paid as much in gas as I did on a thermalcycler.