Shangru Li

The paper introduces an in silico screening strategy to optimize stable conformation of anti-SARS-CoV-2 nanobodies through iterative docking and analysis.

NanoBERTa-ASP predicts nanobody-antigen binding sites using a BERT-based model trained specifically on nanobody sequences, achieving high precision and AUC.

Nanotope predicts nanobody paratopes using graph neural networks and sequence/structural features, achieving higher accuracy than traditional methods without requiring antigen data.