A toolkit for covalent docking with GOLD: From automated ligand preparation with KNIME to bound protein-ligand complexes

Abstract

Motivation: Current covalent docking tools have limitations that make them difficult to use for performing large-scale structure-based covalent virtual screening (VS). They require time-consuming tasks for the preparation of proteins and compounds (standardization, filtering according to the type of warheads), as well as for setting up covalent reactions. We have developed a toolkit to help accelerate drug discovery projects in the phases of hit identification by VS of ultra-large covalent libraries and hit expansion by exploration of the binding of known covalent compounds. With this application note, we offer the community a toolkit for performing automated covalent docking in a fast and efficient way. Results: The toolkit comprises a KNIME workflow for ligand preparation and a Python program to perform the covalent docking of ligands with the GOLD docking engine running in a parallelized fashion.