A new descriptor pipeline based on persistent Stanley-Reisner invariants reports slightly better protein-ligand and metalloprotein-ligand affinity predictions than selected older models.
Docking and scor- ing in virtual screening for drug discovery: methods and applications
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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction
A new descriptor pipeline based on persistent Stanley-Reisner invariants reports slightly better protein-ligand and metalloprotein-ligand affinity predictions than selected older models.