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A Multivariate Approach to Investigate Docking Parameters' Effects on Docking Performance
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Optimization and Validation of a Docking-Scoring Protocol; Application to Virtual Screening for COX-2 Inhibitors
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Comparison of Automated Docking Programs as Virtual Screening Tools
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The Kolmogorov-Smirnov Test for Goodness of Fit
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Multivariate assessment of virtual screening experiments
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VoteDock: Consensus docking method for prediction of protein–ligand interactions
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Outstanding challenges in protein–ligand docking and structure‐based virtual screening
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Effect of preprocessing and simulation parameters on the performance of molecular docking studies
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Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results
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Machine learning optimization of cross docking accuracy
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Targeted scoring functions for virtual screening
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Use of Experimental Design To Optimize Docking Performance: The Case of LiGenDock, the Docking Module of Ligen, a New De Novo Design Program
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Evaluation of Different Virtual Screening Programs for Docking in a Charged Binding Pocket
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Predicting target profiles with confidence as a service using docking scores
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Role of Docking in Anticancer Drug Discovery
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Study of Imidazolium Salt Derivatives as PIK3CA Inhibitors Using a Comprehensive in Silico Method
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Additional file 1 of Predicting target profiles with confidence as a service using docking scores
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