LIT-PCBA

LIT-PCBA is a benchmark dataset used to evaluate the performance of models in predicting drug-target interactions (DTIs) through virtual screening tasks.

Papers using LIT-PCBA (6)

Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers2024 · 3 citesStructure-Aware Contrastive Learning with Fine-Grained Binding Representations for Drug Discovery2025 · 1 citesCompositional Flows for 3D Molecule and Synthesis Pathway Co-design2025 · 1 citesScaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT2024 · 2 citesConditional Chemical Language Models are Versatile Tools in Drug Discovery2025S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search2024