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 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.

Authors

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-10-26
DOI
https://doi.org/10.64898/2026.10.21.760573
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

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

Tim-Henrik Buelles, Julien Jorda, Justyna Sosna, Kyle Meador et al.
bioRxiv (Cold Spring Harbor Laboratory)
Monoclonal and Polyclonal Antibodies Research
preprint

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

Tim-Henrik Buelles, Julien Jorda, Justyna Sosna, Kyle Meador, Hadrien Chauvin, Todd O. Yeates, Anya Polovina, Peter M. Bowers, Robert Tacke, Joshua Laniado, Robin A. Aglietti, Pythia Labs Team, Mohamed El Hibouri, Lucas Zanini, Matthias M. A. Malago, Katty Polyak, Ramin Ansari, Thibault M. Duplay
preprint en

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.

bioRxiv (Cold Spring Harbor Laboratory)
Monoclonal and Polyclonal Antibodies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon