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Practical Model Selection for Prospective Virtual Screening
2018
Journal of Chemical Information and Modeling
Virtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the data set and evaluation strategy. We consider a wide range of ligand-based machine learning and docking-based approaches for virtual screening on two protein-protein interactions, PriA-SSB and RMI-FANCM, and present a strategy for choosing which algorithm is best for prospective compound prioritization. Our
doi:10.1021/acs.jcim.8b00363
pmid:30500183
pmcid:PMC6351977
fatcat:4cqp6nqkfrf3hdetp42rmwgaey