Hannah L. Han

This study designs de novo proteins that selectively inhibit alpha-synuclein aggregation by targeting specific intermediates, with one binder preferentially inhibiting oligomer formation and secondary nucleation.

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

The paper identifies a cellular tipping point between aggregate accumulation and removal as a universal feature of neurodegeneration, validated through live-cell assays and super-resolution imaging.

The paper develops RFdiffusion to generate protein binders for IDPs/IDRs, achieving nanomolar affinity and functional applications in amylin and IL2RG.

The paper designs peptide traps that bind amyloidogenic segments in {beta}-strand and {beta}-hairpin conformations, effectively blocking fibril assembly for A{beta}42.