Oliver Morell

The paper develops a computational framework to minimize CD8⁺ T cell immunogenicity in designed proteins while preserving function, using a de novo luciferase as a model.

The paper analyzes 3,766 binders to identify predictive features for experimental success in de novo binder design, showing that AF3-derived metrics improve prediction accuracy.

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.