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TERMinator: A Neural Framework for Structure-Based Protein Design using Tertiary Repeating Motifs
Recent neural graph-based models that use backbone coordinate-derived features show exceptional performance on native sequence recovery tasks and are promising frameworks for design.
Attribution Methods Reveal Flaws in Fingerprint-Based Virtual Screening
Our results confirm that high-performing models may not learn the correct binding rule, and suggest concrete steps that can remedy this situation.
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