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.

PMID: 36969452
Funding: - Department of Science and Technology, Hubei Provincial People's Government: 2019CFA069 - National Natural Science Foundation of China: 31971150

Links