Esperanza Rivera‐de‐Torre

This paper presents a rapid, automation-friendly pipeline for characterizing de novo protein binders without cell culture or purification, achieving binding affinity and kinetics in three days.

This study shows that mRNA-delivered consensus allergens induce neutralizing IgG responses against multiple food and pollen allergens, offering a safer and broader allergy immunotherapy approach.

This paper develops a pipeline combining yeast screening and AlphaFold3 to accelerate discovery of multi-target antibodies, finding that structural predictions improve binding specificity and solubility.

This study designs a protein that precisely controls Gremlin-1 antagonism by releasing BMPs, revealing the role of interface rigidity in antagonist function.

The paper determines the structures of two actinoporins in a membrane environment using cryogenic electron microscopy, revealing their pore-forming mechanism through intermediate states.

This paper designs de novo pMHC binders using generative models to create T cell-based cancer therapeutics with high specificity and minimal cross-reactivity.

InstaNovo is a transformer model for de novo peptide sequencing that outperforms existing methods, enabling accurate identification of peptides and discovery of novel sequences and organisms.