BiologybioRxiv

Ranked by formulaVerdict: Notable

Design of full-length agonist and antagonist antibodies for hard targets

Therapeutic antibodies have transformed modern medicine, yet conventional discovery relies on lengthy experimental workflows, offers limited control over how antibodies engage their targets, and struggles to deliver…

By Pythia Labs Team, Aglietti, Ansari +15

Score█████░░░░░4.6

Caveats

  • Preprint; not yet peer reviewed.

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Abstract

Therapeutic antibodies have transformed modern medicine, yet conventional discovery relies on lengthy experimental workflows, offers limited control over how antibodies engage their targets, and struggles to deliver candidates across many important target classes. Despite recent advances in computational protein design, generating full-length antibodies with desired functional activity and favorable developability profiles remains challenging. Here we present an end-to-end computational design pipeline built around Pythia-1, an all-atom generative model that reasons jointly over amino acid sequence and three-dimensional atomic structure under explicit design constraints. We generated candidates in full-length human immunoglobulin G (IgG) format across 22 therapeutic targets spanning receptor ectodomains, cytokines, growth factors, and G protein-coupled receptors (GPCRs), a particularly challenging target class for antibody discovery. Following a single computational design round, experimental screening of at most 48 candidates per target identified antibodies with single-digit nanomolar affinities for soluble proteins and single-digit nanomolar cell-binding EC50 values for GPCRs. The pipeline's ability to target specified epitopes and conformational states enabled the design of antibodies with agonist and antagonist activity. In vitro characterization demonstrated target-specific engagement and potent functional modulation, with single-digit nanomolar inhibitory potency in functional assays for a range of targets, including multiple GPCRs. To our knowledge, this study provides the first demonstration of both GPCR agonism and antagonism by de novo designed full-length IgG antibodies. We incorporated key developability and manufacturability requirements into the initial designs by conditioning generation on human germline frameworks and applying sequence constraints to limit known liabilities. The resulting antibody designs exhibited biophysical profiles comparable to or better than those of clinical-stage therapeutic controls. We provide the complete sequences of all lead candidates to support independent experimental validation and further development. Together, these findings demonstrate that our technology can deliver antibodies with programmable function and key properties expected of lead candidates, opening opportunities for first-in-class therapeutics against hard-to-drug targets.

Pythia Labs Team, R. A. Aglietti, R. Ansari, P. M. Bowers, T.-H. Buelles, H. Chauvin, T. M. Duplay, M. El Hibouri, J. Jorda, J. Laniado, M. M. A. Malago, K. Meador, A. Polovina, K. Polyak, J. Sosna, R. Tacke, T. O. Yeates, L. Zanini

The editor's rubric

Heuristic review

Leverage4 / 5
A general-purpose tool used across several fields (Adam, ResNet, LoRA, next-generation sequencing).
24% of this desk’s rubric
Magnitude3 / 5
Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
16% of this desk’s rubric
Evidence3 / 5
Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
20% of this desk’s rubric
Novelty3 / 5
A genuinely new approach to an open problem.
20% of this desk’s rubric
Trajectory2 / 5
Some room to improve with obvious engineering.
10% of this desk’s rubric
Stakes2 / 5
Benefits a professional community (practitioners, clinicians, engineers).
10% of this desk’s rubric

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose); breadth (many tasks, programmable); firsts (first); novelty (discovery); verification (experimental validation, independent replication); stakes (prevention or cure). Red flags: derivative (we apply).

How the score was computed

rank-2026-10-18

Score█████░░░░░4.6

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Desks place stronger verdicts first, then use this score to order work within the same verdict.

Merit
6.1 / 10
Weighted rubric, evidence-gated.
Adjusted merit
5.0 / 10
Shrunk toward the desk prior by editor confidence (46%).
Attention
0%
Citations, upvotes, points, mentions.
Freshness
88%
Half-life decay since publication.

No attention signals recorded yet.

The record

  • Reviewed by heuristic-v10 on Oct 27, 2026, 05:48 UTC. Paper type: method.
  • Categories: molecular biology
  • TOP, No.2 in the Front page edition of October 27, 2026.
  • LEAD, No.1 in the Biology edition of October 27, 2026.