Reactive Docking: a computational method for high-throughput virtual screenings of reactive species


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 material

Training and test sets information
The list of 431 PDBs and warheads used to build the datasets
Summary of the virtual screening results
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

Supplementary weblinks

Meeko: preparation of small molecules for AutoDock
Meeko code repository
AutoDock-GPU: AutoDock for GPUs and other accelerators
AutoDock-GPU code repository