Machine Learning-Aided Small-Molecule Virtual Screening: Recent Advances and Future Perspectives
We comprehensively review how AI and machine learning are reshaping small-molecule virtual screening, spanning AI-driven scoring functions, efficient search algorithms, and the paradigm shift toward generative de novo molecular design.
Sep 1, 2026
Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance
We propose pretrained embedding distance (PED), a molecular similarity measure computed directly from pretrained models without task-specific training, effective for both ranking molecules in virtual screening and guiding molecular generation via reward design.
Apr 27, 2026