LPT framework orchestrates bounded agentic loops for automated protein binder design

[bioRxiv] A bioRxiv preprint by Uckelmann et al. presents LPT (little protein tiger), a framework that fixes the orchestration of LLM stages, each running a bounded agentic loop with custom system prompts and tool access, to enable de novo protein binder design from a single natural language prompt. The stages can query a curated literature database containing about 14,000 papers digested into key findings. According to the paper, an LLM with database access answered 41 of 48 test questions drawn from database key findings correctly, while a model without access answered none. In three end-to-end design campaigns initiated from a single prompt, LPT autonomously identified design intent, selected targets, structures and hotspot residues, and designed candidate binders to disrupt CALCRL/RAMP1, PD-1/PD-L1 and PVR-TIGIT interactions. Cross-validation with multiple folding models indicated a high in silico success rate at minimal token consumption and low computational cost. The findings have not been peer reviewed.