Drug repurposing for SARS-CoV-2: a high-throughput molecular docking, molecular dynamics, machine learning, and DFT study

Keyphrases

• High-throughput 100%
• Molecular Dynamics 100%
• COVID-19 100%
• Molecular Docking 100%
• Drug Repurposing 100%
• DFT Study 100%
• Machine Learning Experiments 100%
• Docking Molecular 100%
• Dynamic Machine Learning 100%
• Protein-based 66%
• Ligand-protein 66%
• Human Life 33%
• Nanostructures 33%
• Human-made 33%
• Structure-property Relationships 33%
• Density Functional Theory Analysis 33%
• Global Economy 33%
• Recent History 33%
• Binding Site 33%
• World War II 33%
• In Silico 33%
• Binding Energy 33%
• Human Death 33%
• Molecular Dynamics Modeling 33%
• Unique Proteins 33%
• Human Nature 33%
• Multiple Therapy 33%
• Remdesivir 33%
• Emerging Infectious Diseases 33%
• Private Government 33%
• Inhibitor Binding Site 33%
• ZINC Database 33%
• Human Infection 33%
• Ligand Efficacy 33%
• Potential Inhibitors 33%
• Multiple Vaccine 33%
• 1918 Influenza Pandemic 33%
• Drug-likeness Analysis 33%
• Nuclear Bomb 33%
• In Vivo Trial 33%
• Bombing Attacks 33%
• Molecular Dynamics Analysis 33%
• Therapeutic Candidates 33%
• Vaccine Candidate 33%
• Protein Binding Site 33%
• Hydroxychloroquine 33%
• Ritonavir 33%
• Lopinavir 33%

Pharmacology, Toxicology and Pharmaceutical Science

• Binding Site 100%
• SARS Coronavirus 100%
• Drug Repositioning 100%
• Disease 66%
• Infection 66%
• Protein Ligand 66%
• Combination Therapy 33%
• Nanomaterial 33%
• Protein Binding 33%
• Remdesivir 33%
• Ritonavir 33%
• Spanish Influenza 33%
• Hydroxychloroquine 33%
• Dynamic Modeling 33%
• Lopinavir 33%

Biochemistry, Genetics and Molecular Biology

• Dynamics 100%
• SARS Coronavirus 100%
• Docking (Molecular) 100%
• Binding Site 75%
• Protein Ligand 50%
• Computer Model 25%
• Binding Protein 25%
• Binding Energy 25%
• Ritonavir 25%