Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking
By Francesco Gentile, Jean Charle Yaacoub, James Gleave, Michael Fernández, Anh-Tien Ton, Fuqiang Ban, Abraham Stern, Artem Cherkasov. 2022
310 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology
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In Computational Theory and Mathematics
In Materials Chemistry
In Molecular Biology
Citations in the corpus
- TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction (2022, methodology): “On the computational side, molecular docking is a commonly-used method for predicting the protein-ligand complex structures the corresponding binding affinities Trott and Olson [2010], Friesner et al. [2004], Ackloo et al. [2022], Gentile et al. [2022].”
- Artificial intelligence in drug development (2025, unknown): “The rapid expansion of compound libraries necessitates accelerated virtual screening of ultra-large libraries 41 , prompting advancements in AI technologies for ligand docking 42,43 .”