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Finding Multiactivity Substructures by Mining Databases of Drug-Like Compounds
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Extending the trend vector: The trend matrix and sample-based partial least squares
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Drug-motif-based diverse monomer selection: Method and application in combinatorial chemistry
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CKB − The Compound Knowledge Base: A Text Based Chemical Search System
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Stigmata: An Algorithm To Determine Structural Commonalities in Diverse Datasets
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Chemical Similarity Using Physiochemical Property Descriptors
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RECAPRetrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry
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A Method for Visualizing Recurrent Topological Substructures in Sets of Active Molecules
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The Properties of Known Drugs. 1. Molecular Frameworks
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New 4-Point Pharmacophore Method for Molecular Similarity and Diversity Applications: Overview of the Method and Applications, Including a Novel Approach to the Design of Combinatorial Libraries Containing Privileged Substructures
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Properties of Known Drugs. 2. Side Chains
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Exploring privileged structures: the combinatorial synthesis of cyclic peptides
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Integration of virtual and high-throughput screening
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Computational Approaches Towards the Rational Design of Drug-like Compound Libraries
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Computational Approaches to Fragment and Substructure Discovery and Evaluation
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Docking and Scoring for Structure‐based Drug Design
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The GPCR — 7TM Receptor Target Family
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The Role of Data Mining in the Identification of Bioactive Compounds via High‐Throughput Screening
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Scaffold Mining of Publicly Available Compound Data
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Finding Multiactivity Substructures by Mining Databases of Drug‐Like Compounds.
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The 7 TM G‐Protein‐Coupled Receptor Target Family
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Many drugs contain unique scaffolds with varying structural relationships to scaffolds of currently available bioactive compounds
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3D shape-based analysis of cell line-specific compound response in cancers
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Validation of a Field-Based Ligand Screener Using a Novel Benchmarking Data Set for Assessing 3D-Based Virtual Screening Methods
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Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures
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Calculating Similarities between Biological Activities in the MDL Drug Data Report Database
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Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases
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Boosting Virtual Screening Enrichments with Data Fusion: Coalescing Hits from Two-Dimensional Fingerprints, Shape, and Docking
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CSBB-ConeExclusion, Adapting Structure Based Solution Virtual Screening to Libraries on Solid Support
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Gradual in Silico Filtering for Druglike Substances
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Characteristic Physical Properties and Structural Fragments of Marketed Oral Drugs
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Formal Concept Analysis for the Identification of Molecular Fragment Combinations Specific for Active and Highly Potent Compounds
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Fragment Descriptors in SAR/QSAR/QSPR Studies, Molecular Similarity Analysis and in Virtual Screening
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Molecular similarity: a key technique in molecular informatics
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Chemical substructures that enrich for biological activity
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UFSRAT: Ultra-Fast Shape Recognition with Atom Types –The Discovery of Novel Bioactive Small Molecular Scaffolds for FKBP12 and 11βHSD1
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Topological Fragment Spectra (TFS) Peak Identification System for Chemical Structure Data Mining
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Computational Medicinal Chemistry in Fragment-Based Drug Discovery: What, How and When
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