3 papers
q-bio.BM2026
SwitchCraft: A Programmatic Framework for Designing State-Switching Proteins
Bowen Jing, Mihir Bafna, Anisha Parsan +5
Multistate mechanisms underlie many of the complex functions observed in natural proteins. The ability to rationally design multistate proteins would have transformative implicatio…
cs.LG2026
Mechanistic Interpretability of Antibody Language Models Using SAEs
Rebonto Haque, Oliver M. Turnbull, Anisha Parsan +4
Sparse autoencoders (SAEs) are a mechanistic interpretability technique that have been used to provide insight into learned concepts within large protein language models. Here, we…
cs.LG2025
BindEnergyCraft: Casting Protein Structure Predictors as Energy-Based Models for Binder Design
Divya Nori, Anisha Parsan, Caroline Uhler +1
Protein binder design has been transformed by hallucination-based methods that optimize structure prediction confidence metrics, such as the interface predicted TM-score (ipTM), vi…