Angehefteter Tweet
Just curious thinking here, but we can seriously model ligandability in-silico. You can build post translation modification models to have the protein more accurately modeled in its cellular environment, predict binding sites, use NN’s to compute forcefield parameters for molecular dynamics (soon skip the empirical parameters and use NN’s to run the MD’s themselves), you can build perturbative response models, essential site scanning analysis, drop that into anisotropic models and predict side chain fluctuations, predict if a drug is going to be agonist/antagonist, predict protein-protein interaction deviations, predict ligand tautomerizations, and design de-novo ligands to enact specific receptor conformational changes, and more that I don’t have the time to write down. The accuracy of that modeling is only getting better with time.
Admittedly, the place it stops being predictable is when you have to monitor systematic effects across the cell (soon there will a Google-like index of protein interactions that can model that on a cellular scale). So, forgive me for being naive, but why do we have to spend years of upfront protein science in-vivo just to determine if a single novel target is ligandable. Shouldn’t it be just rapidly modeling all of the aforementioned scenarios and if they pass, then move into in-vitro->in vivo->clinical? At worst you’ve spent ~2 weeks of time and 500$ on in-silico compute. At best, it’s taken 2 weeks of time and 500$ of compute to get to a place ready for wet-lab hypothesis testing.
At least that’s the mission we’re building towards @try_litefold. Ending Eroom’s Law and making all those modeling scenarios so cost effective, undergraduate students can do them at scale and so affordable you’ll be able to make in-silico hypotheses for the whole human proteome…simply because you can (even if drugging every protein isn’t needed).
David Li@davidycli
anybody in AI x bio who wants to know what industrial drug discovery is actually about should read this briefing by Treeline Bio (announced $200m additional capital yesterday, have raised $1.1bn total) led by serious drug hunters Josh Bilenker and Jeff Engelman link in comments
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