D3Targets-2019-nCoV

D3Targets-2019-nCoV predicts drug targets and performs molecular docking-based virtual screening against SARS-CoV-2 and human proteins to support COVID-19 drug discovery.

Key Features:

• Drug Target Prediction: Predicts drug targets based on existing drugs or active compounds observed in clinical, in vitro, and in vivo studies.
• Molecular Docking and Lead Identification: Uses molecular docking to identify lead compounds and ligand-binding sites on protein structures.
• Protein Database Coverage: Contains 42 proteins comprising 20 SARS-CoV-2-encoded proteins and 22 human proteins involved in virus infection, replication, and release.
• Structural Conformations and Binding Sites: Incorporates up to 69 protein conformations/structures and annotates 557 potential ligand-binding pockets, identifying binding sites with volumes larger than 200 ų.
• Correlation Annotations: Annotates correlations among protein conformations and binding sites to provide insights into dynamic protein interactions.

Scientific Applications:

• Drug Repurposing: Supports prediction of targets for existing drugs and active compounds to enable repurposing against SARS-CoV-2.
• Lead Compound Discovery: Enables identification of lead compounds by docking candidate ligands to annotated binding pockets.
• Viral Lifecycle Target Analysis: Provides targets spanning viral entry, replication, and release by including both SARS-CoV-2 and relevant human proteins.

Methodology:

Performs molecular docking-based virtual screening; predicts targets using existing drugs and compounds from clinical, in vitro, and in vivo studies; identifies ligand-binding sites on protein structures including pockets >200 ų; analyzes up to 69 conformations and 557 potential ligand-binding pockets; and annotates correlations among conformations and binding sites.