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The Use of Consensus Scoring in Ligand-Based Virtual Screening
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Consensus scoring for ligand/protein interactions
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How Does Consensus Scoring Work for Virtual Library Screening? An Idealized Computer Experiment
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Conditional Probability: A New Fusion Method for Merging Disparate Virtual Screening Results
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Identification of Common Functional Configurations Among Molecules
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Clustering of Large Databases of Compounds: Using the MDL “Keys” as Structural Descriptors
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The Information Content of 2D and 3D Structural Descriptors Relevant to Ligand-Receptor Binding
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Glide: A New Approach for Rapid, Accurate Docking and Scoring. 2. Enrichment Factors in Database Screening
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Consensus Scoring: A Method for Obtaining Improved Hit Rates from Docking Databases of Three-Dimensional Structures into Proteins
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Docking and scoring in virtual screening for drug discovery: methods and applications
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Drug Delivery Systems: Entering the Mainstream
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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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Virtual Screening and Bioactivity Modeling for G Protein‐Coupled Receptors
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The Challenge of Affinity Prediction: Scoring Functions for Structure‐Based Virtual Screening
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Aminopyrimidine Derivatives as Multiflavivirus Antiviral Compounds Identified from a Consensus Virtual Screening Approach
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Novel 2D Fingerprints for Ligand-Based Virtual Screening
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Comprehensive Comparison of Ligand-Based Virtual Screening Tools Against the DUD Data set Reveals Limitations of Current 3D Methods
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FUSING SIMILARITY RANKINGS IN LIGAND-BASED VIRTUAL SCREENING
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Additional file 1 of Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
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Additional file 2 of Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
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Additional file 3 of Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
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