Nicholas F. Polizzi

Deep-learning-based design of an orthogonal self-labeling protein from K-Ras(G12C)

This paper designs an orthogonal self-labeling protein, LUCI-tag, using deep learning, which enables rapid and payload-agnostic labeling of proteins in live cells.

Molecular basis of mitochondrial leucine transport by human Sideroflexin 1

The paper identifies leucine as the substrate for SFXN1 and reveals its alternating-access transport mechanism using structural and biochemical analyses.

De novo design of small-molecule-induced conformational change

This paper designs de novo proteins that undergo small-molecule-induced conformational changes, demonstrating strong binding affinity and specificity for exatecan.

Principles of in situ protein sequencing: expansion microscopy-adapted Edman degradation and amino acid recognition

This study adapts Edman degradation and amino acid recognition to expansion microscopy gels to demonstrate in situ protein sequencing principles using synthetic constructs.

Zero-shot design of drug-binding proteins via neural selection-expansion

This paper introduces a method using two neural networks to design drug-binding proteins with high affinity, surpassing current state-of-the-art methods.

De novo design of transmembrane accessory subunits for fold stabilization and expansion

This paper designs synthetic transmembrane subunits to stabilize and expand membrane proteins, demonstrating their utility in structural biology and disease treatment.

Emergence of specific binding and catalysis from a designed generalist binding protein

This study shows how a designed generalist binding protein can evolve into specific functions like a fluorophore binder and an efficient enzyme through weak, promiscuous interactions.

MreC-MreD structure reveals a multifaceted interface that controls MreC conformation

The paper determines the structure of MreC-MreD complex and shows how MreD controls MreC conformation, essential for bacterial cell shape and antibiotic targeting.

De novo design of semisynthetic protein nanopores

This paper designs de novo proteins to modify nanopore complexes, creating customized structural and functional properties for enhanced sequencing applications.

AF2BIND: Predicting ligand-binding sites using the pair representation of AlphaFold2

AF2BIND predicts ligand-binding sites using AlphaFold2's pairwise representation without requiring a ligand, outperforming other models and linking bait amino acids to ligand properties.