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    Home»AI Tools»[2510.14989] Constrained Diffusion for Protein Design with Hard Structural Constraints
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    [2510.14989] Constrained Diffusion for Protein Design with Hard Structural Constraints

    AwaisBy AwaisMarch 27, 2026No Comments1 Min Read0 Views
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    [Submitted on 1 Oct 2025 (v1), last revised 25 Mar 2026 (this version, v2)]

    View a PDF of the paper titled Constrained Diffusion for Protein Design with Hard Structural Constraints, by Jacob K. Christopher and 4 other authors

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    Abstract:Diffusion models offer a powerful means of capturing the manifold of realistic protein structures, enabling rapid design for protein engineering tasks. However, existing approaches observe critical failure modes when precise constraints are necessary for functional design. To this end, we present a constrained diffusion framework for structure-guided protein design, ensuring strict adherence to functional requirements while maintaining precise stereochemical and geometric feasibility. The approach integrates proximal feasibility updates with ADMM decomposition into the generative process, scaling effectively to the complex constraint sets of this domain. We evaluate on challenging protein design tasks, including motif scaffolding and vacancy-constrained pocket design, while introducing a novel curated benchmark dataset for motif scaffolding in the PDZ domain. Our approach achieves state-of-the-art, providing perfect satisfaction of bonding and geometric constraints with no degradation in structural diversity.

    Submission history

    From: Jacob Christopher [view email]
    [v1]
    Wed, 1 Oct 2025 17:55:45 UTC (11,396 KB)
    [v2]
    Wed, 25 Mar 2026 19:37:47 UTC (11,394 KB)

    Constrained Constraints Design Diffusion hard Protein Structural
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