Valentas Brasas

Odin-Multi is a binder design framework that optimizes sequences against multiple targets simultaneously, improving cross-reactivity and specificity compared to single-target methods.

This paper introduces a hybrid quantum-classical pipeline for designing MHC-binding peptides, showing that quantum-derived priors improve the yield of strong binders, especially for understudied HLA alleles.

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.