Statements (55)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Drug discovery method
|
| gptkbp:alsoKnownAs |
gptkb:CADD
|
| gptkbp:application |
gptkb:biotechnology
Pharmaceutical industry |
| gptkbp:benefit |
Improves accuracy of drug candidate selection
Reduces cost of drug development Reduces time for drug discovery |
| gptkbp:challenge |
Data quality
Prediction accuracy Computational limitations Protein flexibility |
| gptkbp:developedBy |
1970s
|
| gptkbp:enables |
Personalized medicine
Rational drug design Target-based drug discovery |
| gptkbp:field |
Pharmaceutical sciences
Medicinal chemistry |
| gptkbp:goal |
Identify new drug candidates
Optimize lead compounds |
| https://www.w3.org/2000/01/rdf-schema#label |
Computer-Aided Drug Design
|
| gptkbp:method |
Ligand-based drug design
Molecular docking Pharmacophore modeling Quantitative structure-activity relationship Structure-based drug design Virtual screening |
| gptkbp:relatedTo |
High-throughput screening
Artificial intelligence in drug discovery Cheminformatics In silico screening |
| gptkbp:requires |
Chemical compound libraries
Computational resources Protein structure data |
| gptkbp:software |
gptkb:GOLD
gptkb:OpenEye gptkb:Chimera gptkb:ROCS gptkb:Discovery_Studio gptkb:AutoDock PyMOL Schrödinger Suite MOE (Molecular Operating Environment) |
| gptkbp:uses |
gptkb:Bioinformatics
Machine learning Computational chemistry Deep learning Molecular modeling ADMET prediction De novo drug design Fragment-based drug design Homology modeling Molecular dynamics simulation QSAR modeling |
| gptkbp:bfsParent |
gptkb:CADD
|
| gptkbp:bfsLayer |
7
|