Montader Ali

The paper evaluates AI-based antibody-antigen structure prediction methods, finding that confidence scores often fail to distinguish correct from incorrect pairings, even with increased sampling.

This paper introduces NbForge, a nanobody folding model that improves prediction of HCDR3 blueprint and disulphide bonds, achieving accuracy comparable to large predictors with faster speed.

This study improves nanobody structure prediction by using synthetic data and a classifier to filter structural accuracy, achieving better results than existing methods with lower computational cost.

The paper introduces SpyBLI, a cell-free pipeline for rapid, accurate binding kinetics measurement from crude samples, demonstrating its applicability with nanobodies and scFvs.