Building a Hybrid Physical-Statistical Classifier for Predicting the Effect of Variants Related to Protein-Drug Interactions

Keyphrases

• Single nucleotide Variant 100%
• Drug-protein Interaction 100%
• Statistical Classifiers 100%
• Binding Affinity 60%
• Statistical Model 60%
• Drug Efficacy 40%
• Protein-drug Complex 40%
• Genetic Variation 20%
• Binding Data 20%
• Structural Features 20%
• Full Model 20%
• Ligand Binding 20%
• Protein Targeting 20%
• Drug Design 20%
• Genomic Features 20%
• 3D Structure 20%
• Bootstrap 20%
• Hybrid Method 20%
• Area under the Receiver Operating Characteristic (AUROC) 20%
• Training Model 20%
• Model Combining 20%
• Sequence Features 20%
• Structure Feature 20%
• Population Variation 20%
• Physically-based 20%
• Physicochemical Features 20%
• Government Regulators 20%
• Structure-based Docking 20%

Biochemistry, Genetics and Molecular Biology

• Single-Nucleotide Polymorphism 100%
• Drug Interaction 100%
• Binding Affinity 60%
• Drug Efficacy 40%
• Genetic Divergence 20%
• Genetic Variation 20%
• Ligand Binding 20%
• Structural Genomics 20%
• Ligand Structure 20%

Chemistry

• Kd 100%
• Ligand Binding 33%
• Ligand Structure 33%