Qiuzhen Li

The paper validates and analyzes 12,000 AI-designed CAR-T binders from a global competition, identifying successful designs and factors improving their performance.

The paper presents SHE, a phylogeny of eukaryotic proteomes based on structural comparisons, revealing a bipartite model of evolution and a framework for model organism selection.

RareFoldGPCR designs peptide agonists using noncanonical amino acids to modulate GPCRs, validated experimentally for functional activity.

This paper designs cyclic peptide agonists for GCGR and GLP1R using EvoBind, achieving dual activation with EC50 values comparable to natural hormones.

RareFold predicts and designs protein structures with noncanonical amino acids, achieving low-micromolar affinities and no immune activation in organoid models.

This paper introduces EvoBind, an AI method to design cyclic peptides that inhibit HIV-1 membrane fusion, demonstrating potent inhibition of two HIV-1 strains with no toxicity.

The paper presents a method to design linear and cyclic peptide binders of varying lengths using only a protein target sequence, achieving nM affinity and avoiding adversarial designs.