SCARdock
SCARdock implements the steric-clashes alleviating receptor (SCAR) strategy to screen and repurpose covalent ligands and prioritize covalent warheads for targeted protein residues.
Key Features:
- SCAR strategy: Implements the steric-clashes alleviating receptor (SCAR) approach for structure-based screening of covalent ligands.
- Curated Complex Structures: Provides a manually curated collection of 954 protein–covalent ligand complex structures.
- Experimentally Confirmed Covalent Warheads: Includes a curated set of 68 experimentally verified covalent warheads that target 11 residues.
- Prefiltered Virtual Compounds: Contains 690,018 purchasable virtual compounds prefiltered and classified based on the inclusion of experimentally verified warheads.
- Screening protocol: Applies a protocol for identifying and prioritizing covalent inhibitors against specified protein targets.
Scientific Applications:
- Covalent ligand discovery: Structure-based screening to identify candidate covalent inhibitors and ligands.
- Warhead selection and prioritization: Selection and ranking of covalent warheads for targeting specific residues.
- Compound repurposing: Repurposing purchasable virtual compounds as potential covalent therapeutics.
- Structure–activity analysis: Use of curated complex structures to analyze protein–ligand interactions for covalent binding.
Methodology:
Implements the steric-clashes alleviating receptor (SCAR) strategy using a manually curated set of 954 complex structures, a curated set of 68 experimentally confirmed warheads targeting 11 residues, and a prefiltered library of 690,018 purchasable virtual compounds classified by warhead inclusion for structure-based screening.
Topics
Details
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Added:
- 8/31/2023
- Last Updated:
- 11/24/2024
Operations
Publications
Song Q, Zeng L, Zheng Q, Liu S. SCARdock: A Web Server and Manually Curated Resource for Discovering Covalent Ligands. ACS Omega. 2023;8(11):10397-10402. doi:10.1021/acsomega.2c08147. PMID:36969452. PMCID:PMC10034828.