Abstract
We describe the formalization of the reactive docking protocol, a method developed to model and predict reactions between small molecules and biological macromolecules. The method has been successfully used in a number of applications already, including recapitulating large proteomics datasets, performing structure-reactivity target optimizations and prospective virtual screenings. By modeling a near-attack conformation-like state, no QM calculations are required to model ligand and receptor geometries. Here, we present its generalization using a large dataset containing more than 400 ligand-target complexes, 8 nucleophilic modifiable residue types, and more than 30 warheads. The method correctly predicts the modified residue in ~85% of complexes and shows enrichments comparable to standard focused virtual screenings in ranking ligands. This performance supports this approach for the docking and screening of reactive ligands in virtual chemoproteomics and drug design campaigns.
Supplementary materials
Title
Training and test sets information
Description
The list of 431 PDBs and warheads used to build the datasets
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Title
Summary of the virtual screening results
Description
Average, median, and standard deviation of the docking scores of each solvent-accessible residue considered for the virtual screenings dockings from Resnik et al. (ref.26). In bold are highlighted the covalent residues identified from mass-spec experiments
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