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  ---
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- license: mit
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  tags:
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- - protein-design
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- - allosteric
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- - state-selectivity
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- - guided-generation
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- - rfdiffusion
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- - pxdesign
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- - proteina
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  library_name: pytorch
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  ---
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  Q_θ serves as both a re-ranker (best-of-K) and a gradient signal for guided generation on top of frozen priors (RFdiffusion, PXDesign, Proteina-ComplexA) via Langevin, SMC, TDS, or classifier guidance.
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- This repository accompanies the paper *AlloGen: State-Selective Scoring for Allosteric Binder Design* (NeurIPS 2026).
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  ## Installation
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  primaryClass = {q-bio.BM}
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  }
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  ```
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-
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-
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- ## License
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-
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- MIT — see [`LICENSE`](LICENSE).
 
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  ---
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+ license: apache-2.0
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  tags:
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+ - protein-design
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+ - allosteric
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+ - state-selectivity
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+ - guided-generation
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+ - rfdiffusion
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+ - pxdesign
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+ - proteina
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  library_name: pytorch
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  ---
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  Q_θ serves as both a re-ranker (best-of-K) and a gradient signal for guided generation on top of frozen priors (RFdiffusion, PXDesign, Proteina-ComplexA) via Langevin, SMC, TDS, or classifier guidance.
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+ This repository accompanies the paper *AlloGen: AlloGen: Conformation-Selective Binder Generation with Differential State Scoring* (arXiv 2026).
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  ## Installation
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  primaryClass = {q-bio.BM}
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  }
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  ```