Iterative Refinement for Structural Optimization of De Novo Protein Sequences
In this paper, we introduce an iterative refinement procedure that substitutes individual amino acid residues in a predicted protein sequence to minimize structural error; substitutions are guided by a weighted composite score of global evaluation metrics including the TM-score, GDT-TS, and RMSD. Starting from an initial sequence prediction produced by a structure-aware graph neural network (GNN)…
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