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arxiv: 2606.07567 · v1 · pith:IODDUNZYnew · submitted 2026-05-25 · 🧬 q-bio.BM · cs.AI· cs.CE

SurfDesign: Effective Protein Design on Molecular Surfaces

classification 🧬 q-bio.BM cs.AIcs.CE
keywords proteindesignsurfdesignmolecularsurfacebenchmarksenzymefunctional
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Protein function is largely determined by molecular surface geometry and physicochemical complementarity, yet most protein design methods condition only on backbone structure. We introduce SurfDesign, a surface-conditioned protein design framework that models molecular surfaces as continuous geometric manifolds and integrates them with pretrained protein language models. SurfDesign employs surface-based equivariant message passing to capture surface normals, curvature, and directional geometry, together with a parameter-efficient fine-tuning strategy. Focusing on functional protein design, we show that SurfDesign consistently outperforms prior surface-conditioned and backbone-only methods on de novo binder and enzyme design benchmarks. We also report strong performance on inverse-folding benchmarks as a diagnostic of structural compatibility. Our results highlight manifold-aware surface representations as a principled foundation for functional protein and enzyme design. Code is available at https://github.com/smiles724/SurfDesign.

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