Nygaard, M. M. | Search bioRxiv

bioRxiv2026

Specificity-driven protein binder design with Odin-Multi

A useful protein binder is defined as much by what it does not bind as by what it does. Some applications call for one binder to cover a family of related targets; others require it to distinguish a single member from near-identical relatives. Yet, widely used deep-learning-based de novo design methods typically optimise one interaction at a time, leaving cross-reactivity and specificity to emerge during downstream screening. Here we present Odin-Multi, a binder design framework that optimises a shared binder sequence against several complexes simultaneously, applying attractive objectives to on-targets and repulsive objectives to off-targets. We benchmarked Odin-Multi in silico across three systems representing distinct cross-reactivity and specificity challenges: class B1 G protein-coupled receptors (GPCRs), testing cross-reactivity across multiple therapeutically relevant receptors; short-chain three-finger toxins, testing cross-reactivity across homologous toxin family members; and peptide-MHC (pMHC) complexes, testing specificity between near-identical target and off-target surfaces. For pairs of related class B1 GPCRs, 83.5 to 96.8% of jointly optimised designs exceeded an interaction-confidence threshold for both targets, compared with 6.8 to 36.3% of designs from single-target campaigns. For two short-chain three-finger neurotoxins, 9.2% of jointly optimised designs exceeded the corresponding threshold for both targets, compared with 0.8% of designs optimised against one toxin alone. Finally, in a pMHC specificity benchmark where target and off-target differed only in a single peptide residue, counter-selection increased the fraction of designs satisfying both the target-confidence criterion and a target-to-off-target interaction-confidence ratio of 2.5 from 6.0% to 14.2%. Experimental screening produced leads consistent with both design regimes in the two systems tested in vitro. We identified a cross-reactive toxin minibinder showing apparent nanomolar binding to the neurotoxin Erabutoxin A and to a candidate NK-shNTx-containing fraction from Naja kaouthia venom (higher-affinity fitted components of 11.95 and 34.43 nM, respectively), and a pMHC minibinder with greater target-to-off-target discrimination than a previously reported design. By treating cross-reactivity and specificity as explicit design objectives rather than screening outcomes, Odin-Multi widens the range of binding behaviours accessible to computational design.

bioengineering↗

bioRxiv2026

De novo designed cyclic MC4R peptide agonist reduces food intake in mice

Deep learning-based structure prediction enables the design of peptide ligands without relying on naturally occurring scaffolds. However, most computationally generated peptides are not advanced beyond initial activity measurements, leaving the path to drug-like optimization and in vivo validation underexplored. Here we establish an end-to-end workflow for de novo peptide agonist discovery and maturation using the melanocortin-4 receptor (MC4R) as a model target. Using an AlphaFold2-based hallucination protocol implemented in ColabDesign, we generated more than 5,000 linear and head-to-tail cyclic candidate peptides directed towards the MC4R orthosteric pocket. Functional screening of a prioritized subset revealed measurable activity in 74% of linear peptides and 23% of cyclic peptides, from which we identified a cyclic agonist with an EC50 of 340 nM despite lacking the canonical melanocortin activation motif. We then performed systematic in vitro maturation by deep mutational scanning, half-life extender conjugation scanning, and a combinatorial optimization library, coupled with data-driven analysis to map sequence-activity relationships. These experiments identified an alternative activation motif centered on an APWR segment and yielded single-site variants with substantially improved potency. The most effective substitution, a proline at position 5, produced the E5P variant with an EC50 of 6.7 nM against the human melanocortin-4 receptor (hMC4R). Finally, central administration of E5P (10 nmol) reduced acute food intake in mice, providing in vivo proof of concept. Together, our results demonstrate a generalizable design-to-validation strategy for converting de novo peptide designs into optimized, pharmacologically active peptides, and expand the space of MC4R agonist chemotypes beyond endogenous melanocortins.

molecular biology↗