Yusuf O. Adeshina

PLINDER provides a large, annotated PLI dataset with diverse annotations and improved evaluation splits to better assess computational methods for drug design.

PINDER provides a benchmark dataset for evaluating protein-protein interaction docking models, revealing overestimation of performance on leaky test sets and showing improvements with interface-clustered training.

The paper introduces a machine learning classifier for virtual screening that reduces false positives by using a novel training dataset and shows promising results in identifying active compounds.