David Koes edited subsection_Virtual_Screening_Evaluation_In__.tex  over 8 years ago

Commit id: a4d0c820eb424703edfbccc30654609f70cf3d3c

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In order to investigate the utility of the FOMS approach we consider both the ability of shape constraint filters to generate enriched subsets and quality of shape similarity rankings generated using fragment aligned molecules. We compare to VAMS, which aligns all molecules to a canonical reference system based on their moments of inertia, and rdShape, the shape alignment module of rdkit \cite{rdkit} which dynamically aligns shapes to maximize their overlap. Results are reported using receiver operating characteristic curves which plot the false positive rate (FPR) with respect to the true positive rate (TPR) as the classification sensitivity threshold is changed for a ranking.  \textbf{choice of reference ligand/receptor}  \textbf{shape constraint generation}