Chance M Gammill

This paper introduces a protein conformation prediction model optimized for structural accuracy using a structure-aware GNN, achieving results comparable to sequence-focused methods without sequence recovery supervision.

The paper introduces an iterative refinement method to improve de novo protein sequence structural accuracy by substituting amino acids based on structural metrics, achieving significant reductions in RMSD.

This paper introduces an interactive server that combines a structure-aware GNN and ESMFold for bidirectional protein design, enabling users to analyze and validate design hypotheses without software installation.