Nathaniel Corley

This study designs de novo amide ligases with a cysteine catalytic triad to selectively form amide bonds across diverse substrates, demonstrating high selectivity and applicability in synthesizing bioactive molecules.

The paper designs and validates protein readers that specifically detect disease-related modifications in Tau and Abeta in Alzheimer's disease models and human samples.

An all-atom diffusion model using a 14-atom residue representation and sparse U-Net architecture accelerates biomolecular design 10-fold, enabling experimentally validated DNA-binding proteins and multi-turnover cysteine hydrolases.

AtomWorks, a modular atom-level data framework, trains structure prediction and design models; the resulting RF3 improves chirality handling and performs between AF3 and Boltz.

ProtNote is a multimodal deep learning model that enables supervised and zero-shot protein function prediction using free-form text inputs, generalizing to unseen functions.