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Self-focusing virtual screening with active design space pruning. (arXiv:2205.01753v1 [q-bio.QM])
May 5, 2022, 1:11 a.m. | David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
cs.LG updates on arXiv.org arxiv.org
High-throughput virtual screening is an indispensable technique utilized in
the discovery of small molecules. In cases where the library of molecules is
exceedingly large, the cost of an exhaustive virtual screen may be prohibitive.
Model-guided optimization has been employed to lower these costs through
dramatic increases in sample efficiency compared to random selection. However,
these techniques introduce new costs to the workflow through the surrogate
model training and inference steps. In this study, we propose an extension to
the framework …
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