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How Frequently Are Pan-Assay Interference Compounds Active? Large-Scale Analysis of Screening Data Reveals Diverse Activity Profiles, Low Global Hit Frequency, and Many Consistently Inactive Compounds | Journal of Medicinal Chemistry
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Structure-based discovery of nonopioid analgesics acting through the α2A-adrenergic receptor | Science
IJMS | Free Full-Text | Potential Novel Thioether-Amide or Guanidine-Linker Class of SARS-CoV-2 Virus RNA-Dependent RNA Polymerase Inhibitors Identified by High-Throughput Virtual Screening Coupled to Free-Energy Calculations | HTML
Inhibition of neuronal FLT3 receptor tyrosine kinase alleviates peripheral neuropathic pain in mice | Nature Communications
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Machine learning classification can reduce false positives in structure-based virtual screening | PNAS
Virtual Libraries for Docking Methods: Guidelines for the Selection and the Preparation - ScienceDirect
Highly Promiscuous Small Molecules from Biological Screening Assays Include Many Pan-Assay Interference Compounds but Also Candidates for Polypharmacology | Journal of Medicinal Chemistry
Chemoinformatics-based enumeration of chemical libraries: a tutorial | Journal of Cheminformatics | Full Text
Highly Promiscuous Small Molecules from Biological Screening Assays Include Many Pan-Assay Interference Compounds but Also Candidates for Polypharmacology | Journal of Medicinal Chemistry
Machine learning classification can reduce false positives in structure-based virtual screening | PNAS
IJMS | Free Full-Text | Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein–Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design | HTML
Chemoinformatics-based enumeration of chemical libraries: a tutorial | Journal of Cheminformatics | Full Text
Chemoinformatics-based enumeration of chemical libraries: a tutorial | Journal of Cheminformatics | Full Text
