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Consensus virtual screening approaches to predict protein ligands
A. Kukol
School of Life and Medical Sciences
Biosciences Research Group
Centre for Research in Mechanisms of Disease and Drug Discovery
Department of Clinical, Pharmaceutical and Biological Science
Research output
:
Contribution to journal
›
Article
›
peer-review
58
Citations (Scopus)
607
Downloads (Pure)
Overview
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Keyphrases
AutoDock Vina
100%
Protein-ligand
100%
Virtual Screening
100%
Screening Approach
100%
Receptor Targets
66%
Rescoring
66%
Receptor-based Virtual Screening
33%
Reliable Performance
33%
High-affinity Ligands
33%
AutoDock
33%
Cost Savings
33%
Small Databases
33%
Consensus Algorithm
33%
Binding Energy
33%
Decoy
33%
Goal Consensus
33%
Octanol
33%
Autodock 4.2
33%
Consensus Methods
33%
Drug Loading Capacity
33%
Partition Coefficient
33%
Early Enrichment
33%
Efficiency Index
33%
Docking Algorithms
33%
Individual Algorithms
33%
Pharmacology, Toxicology and Pharmaceutical Science
Virtual Screening
100%
Protein Ligand
100%
Receptor
100%
Octanol
33%
Biochemistry, Genetics and Molecular Biology
Protein Ligand
100%
AutoDock
100%
Drug Efficacy
20%
Partition Coefficient
20%
Small Molecule
20%
Octanol
20%
Binding Energy
20%
Immunology and Microbiology
Drug Efficacy
100%
Partition Coefficient
100%
Chemistry
Virtual Screening
100%
Octanol-Water Partition Coefficient
50%
Binding Energy
50%
Agricultural and Biological Sciences
Receptor
100%
Octanol
33%
Binding Energy
33%