Grok 设计前列腺癌蛋白结合体，Sonnet 5.5 做视频

Jacob @JacobMolBio原推发布于 2026.10.13

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“Grok, design protein binders for prostate cancer research” In this binder design workflow test, Grok used various comp bio tools on neocloud resources to generate potential binder candidates against the AF-2 site of the androgen receptor (as many prostate cancers are AR driven). Grok created > 1K candidate sequences using BindCraft2, RFdiffusion3, and BoltzGen, along with ProteinMPNN sequence generation. ESMFold2-Fast and Boltz2 were used to predict the binder–target structures and evaluate their interfaces. A subset was also screened with ESMFold2-Full and Protenix to further assess binder–target placement. Next, to test a refolding workflow, new predictions of 30 candidate binder–target complexes were made via ESMFold2-Fast, ESMFold2-Full, Boltz2, and Protenix, where 5 random seeds were used per tool (another 600 predictions total). For a sequence diversification workflow, given starting predicted binder structures, new sequences were generated for 8 backbones using ProteinMPNN and the recent ProtonPotts, which takes into account protonation states. These seq gen tools created 64 redesign attempts. A subset of these was then evaluated with fresh structure predictions using ESMFold2-Fast, ESMFold2-Full, Boltz2, and Protenix. A pH-aware workflow continued with taking a subset of these, along with their parents, then using PDB2PQR / PROPKA and APBS to predict protonation states and calculate electrostatic contributions to the binder–target interactions, over a pH range of 6.5 -8.0. Ballpark compute costs ranged roughly ~1-26 cents per structure prediction or design attempt. The skill repo, BioSymphony Structure Factory, was used as a foundation for Grok to use these tools. Modal was used for the cloud resources. And, Claude Sonnet 5.5 made this video of the workflow test using ChimeraX, HyperFrames, and ElevenLabs.