Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins

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Authors: Matthew Sinclair, Moeen Meigooni, Archit Vasan, Ozan Gokdemir, Xinran Lian, Heng Ma, Yadu Babuji, Alexander Brace, Khalid Hossain, Carlo Siebenschuh, Thomas Brettin, Kyle Chard
+6 more Christopher Henry, Daniel Schabacker, Venkatram Vishwanath, Rick Stevens, Ian Foster, Arvind Ramanathan
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References: 67

Abstract

Intrinsically disordered proteins (IDPs) represent crucial therapeutic targets due to their significant role in disease-approximately 80% of cancer-related proteins contain long disordered regions -but their lack of stable secondary/tertiary structures makes them “undruggable.” While recent computational advances, such as diffusion models, can design high-affinity IDP binders, autonomous systems can accelerate their translation to practical drug discovery by reducing the need for expert intervention across large-scale design campaigns. To address this challenge, we designed and implemented StructBioReasoner, a scalable multi-agent system for designing biologics that can be used to target both IDPs and structured proteins. StructBioReasoner employs a novel tournament-based reasoning framework where specialized agents compete to generate and refine therapeutic hypotheses, naturally distributing computational load for efficient exploration of the vast design space. Agents integrate domain knowledge with access to literature synthesis, Al-structure prediction, molecular simulations, and stability analysis, coordinating their execution on HPC infrastructure via an extensible federated agentic middleware, Academy. We benchmark StructBioReasoner across Der f 21 and NMNAT-2 and demonstrate that over 50% of 787 designed and validated candidates for Der f 21 outperformed the human-designed reference binders from literature, in terms of improved in silico binding free energy. For the more challenging NMNAT-2 protein, we identified three binding modes from 97,066 binders, including the well-studied NMNAT2:p53 interface. Thus, StructBioReasoner lays the groundwork for agentic reasoning systems for IDP therapeutic discovery on Exascale platforms.

Fields of Study & Subjects

Protein Structure and Dynamics Computational Drug Discovery Methods Bioinformatics and Genomic Networks

Publication details

Journal / source
Proceedings of the Platform for Advanced Scientific Computing Conference
Publisher
ACM
Pages
1–13
Publication date
26 June 2026