H. K. Haddox

This paper designs a protein family that binds and senses small molecules using deep learning and physics-based methods, achieving nanomolar sensitivity for cortisol.

This paper introduces design rules for immunoglobulin-like domains and demonstrates the de novo creation of stable, functional scaffolds with improved biophysical properties.

The paper presents two neural network models for predicting and generating stable proteins based on amino acid sequences, showing improved stability in both expert-designed and model-generated proteins.

The paper maps functional epitopes of antibodies targeting HIV Env fusion peptide by analyzing mutations affecting neutralization, revealing differences between vaccine- and infection-elicited antibodies.

The paper quantifies how amino-acid mutations affect HIV Env protein fitness across two diverged viral strains, finding most sites have conserved preferences but some show shifted mutational tolerance.

This study maps HIV-1 escape mutations from a broadly neutralizing antibody by quantifying the effect of all single amino-acid mutations on viral sensitivity.