A computational workflow will be implemented sequentially in order to i) identify the most promising binding sites within the WDR domain of LRRK2 through a fragment-based computational screening approach, ii) identify and select fragments with lead-like properties and/or high ligand efficiencies, iii) screen databases using the identified fragments and Lipinsky/Mozziconacci rules, and iv) perform high-throughput docking of the selected molecules in the proposed binding sites. Fragment-based computational screening will use an in-house developed fragment library for setting up several all-atom molecular systems, therefore enabling simulated annealing Molecular Dynamics (MD) simulations (GROMACS) to identify the most promising binding sites within the target. No less than three replicates per system will be performed, and any available experimental information concerning active sites or important residues will be used to analyze the data. Following, all fragments bound to the target will be identified and analysed using multiple approaches (e.g. ligand efficiencies, relative energies of binding, free energy of adsorption using the probability ratio method) and only those characterized as high-affinity binders will be selected for further usage. Next, the selected fragments substructures will be used as filter criteria to retrieve from Enamine Real Database only those molecules with matching substructures, using mainly the Lipinsky Lenient Filter (orally available) or Mozziconacci (drug-likeliness) filters. Prior to the high-throughput docking, all compounds will be checked against undesirable functional groups and/or PAINS substructures. A high-throughput docking approach will be then performed, in the binding sites previously identified, using Autodock VINA for the initial ranking, and gnina, a docking software with integrated support for scoring and optimizing ligands using convolutional neural network to re-rank the molecules and select the best 100 hits. MD simulations will use the all-atom AMBER forcefield, with the apo WDR domain also evaluated prior to any fragment-based MD run. The simulated annealing protocol will be used in both fragments and solvent to prevent non-specific binding, keeping the targets' backbone spatially constrained to prevent any changes in its secondary structure. A blind docking approach using qvina-w will be set up for faster evaluation of any identified binding sites. As an additional quality control concerning hit selection, all hits with common substructures to known inhibitors that targets the closed form of LRRK2 will also be excluded while those resembling known binders will be prioritized. Standard MD simulations will be used to evaluate the stability of the protein-ligand complex and to obtain absolute free energies of binding.
GROMACS, gnina, vina, qvina-w, VMD, Pymol, python