Joanna S.G. Slusky

The paper introduces coarse-tuning to specialize a protein foundation model for a specific domain, showing improved performance on transfer learning tasks using a medium-sized dataset of outer membrane beta barrels.

The paper introduces COB, a database of chloroplast outer-envelope beta-barrel proteins, revealing structural and functional diversity across plant species.

N-Zinclopedia predicts transition metal-binding sites and candidate metalloenzymes across protein folds, expanding the known landscape of metal utilization.

The paper introduces an algorithm to accurately count strands in bacterial outer membrane beta-barrels, achieving 97% accuracy on 571,760 structures from AlphaFold2.

The paper creates a large, high-quality database of bacterial transmembrane beta barrels using co-evolution data and presents a new algorithm with high accuracy for identifying these proteins.

The paper improves a method to predict enzymatic metal binding sites using machine learning and computationally generated structures, achieving high precision and recall.

The paper traces the evolutionary pathway of outer membrane beta barrels, showing how repeat protein topology evolves through strand number changes without domain duplication, driven by membrane environment constraints.