A new topological transformer (TopoFormer) has been developed to integrate NLP models and a multiscale topology technique, allowing for the conversion of 3D protein-ligand complexes into NLP-admissible sequences. This approach has shown promising results in scoring accuracy and performance in various benchmark datasets, and has the potential to be applied to other high-dimensional structured data.
