Sethera and Receptor.AI launch AI-guided peptide discovery alliance

Sethera Therapeutics and Receptor.AI have formed a strategic research collaboration to build a closed-loop discovery workflow for hard-to-drug targets. The alliance pairs Sethera’s polymacrocyclic peptide chemistry and encoded screening with Receptor.AI’s physics-based modeling to speed hit confirmation and lead optimization.

Why it matters: - The alliance aims to cut the number of discovery cycles needed to move from screening hits to differentiated peptide lead series. - The workflow is designed for difficult therapeutic targets where conventional peptide design can fall short. - Both companies want to improve potency, selectivity, stability, permeability, and other developability traits.

What happened: - Receptor.AI and Sethera Therapeutics announced a strategic research collaboration on Aug. 3, 2026. - The companies will build a closed-loop discovery and optimization workflow for polymacrocyclic peptide medicines. - The initial program will focus on a mutually selected hard-to-drug target. - The companies plan to evaluate whether the integrated workflow improves hit confirmation, target selectivity and lead optimization versus conventional enrichment- and assay-led prioritization.

The details: - Sethera will generate and experimentally screen architecture-diverse polymacrocyclic peptide libraries. - Receptor.AI will use physics-based modeling, artificial intelligence and multiparameter optimization to analyze sequence, architecture, enrichment and activity data. - Receptor.AI will develop binding hypotheses, prioritize candidate series and guide focused optimization cycles. - The companies will design, synthesize and test new candidates, then use the results to inform the next round of work. - Sethera’s platform installs one to six stable cross-links to generate polymacrocyclic, nested, in-line and interpeptide structures across large encoded libraries. - Sethera’s chemistry explores multiple experimentally accessible topologies instead of starting from a single predetermined structural motif. - The collaboration is focused on applying Receptor.AI’s computational platform to Sethera’s proprietary polymacrocyclic peptide chemistry, encoded screening data and therapeutic candidates. - Each company will keep its background platform technologies. - Joint programs will run under coordinated research plans with defined experimental, computational, data and program-management responsibilities. - Additional terms of the collaboration were not disclosed. - Sethera’s platform also integrates enzymatic macrocyclization, large-scale encoded-library screening, next-generation sequencing, peptide synthesis and biological validation. - Receptor.AI supports programs across small molecules, peptides and induced-proximity therapeutics. More information - Sethera is advancing internal and partnered programs in oncology, inflammation and immunology, metabolic disease and other therapeutic areas. More information

Between the lines: - The partnership pairs experimental breadth from Sethera with computational prioritization from Receptor.AI, which should help the teams separate promising hits from noisy screening output. - The closed-loop setup is meant to learn from sequence, architecture, counterselection, binding, functional and developability data across successive campaigns. - If the first program works, the companies intend to expand into additional internal programs and jointly structured discovery collaborations with pharma and biotech partners across selected target classes and therapeutic areas. - The companies describe the approach as a design-make-test-learn system, which signals a push toward faster feedback and fewer dead-end cycles.

What’s next: - The first step is executing the initial target program and testing the integrated workflow against conventional prioritization methods. - After validation, Receptor.AI and Sethera plan to pursue additional internal programs. - The companies also intend to seek jointly structured discovery collaborations with external pharmaceutical and biotechnology partners. - The collaboration will continue with each experimental cycle feeding the next round of design and optimization.

The bottom line: - Sethera and Receptor.AI are betting that AI plus physics-based modeling can turn unusually large peptide libraries into faster, more reliable lead discovery for hard targets.