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CRITICAL ASSESSMENT OF COMPUTATIONAL HIT-FINDING EXPERIMENTS

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Challenge #2

Hit Identification
Method type (check all that applies)
High-throughput docking
Physics-based
Hybrid of the above
High-throughput docking + reevaluation of top hits & docked poses
Description of your approach (min 200 and max 800 words)

The hit identification and drug discovery strategy consist in high-throughput docking for the identification of modulators of the NSP13 helicase of SARS-CoV-2.

Large library of commercially available compounds (Enamine) will be downloaded and prepared using the LigPrep preparation workflow from Maestro (Schrödinger, Inc). Briefly, the main tautomers from each compound will be generated and only compounds with reasonable physico-chemical properties will be considered (e.g., molecular weight, HBAcc/HBDon, number of rings, log P/D, PSA, ligand flexibility, as well as number of undefined chiral centers. We will also use our proprietary filters to eliminate reactive and chemically unstable compounds, compounds with undesirable functional groups and Pan-Assay INterfeering Structures (PAINS).

The docking simulations will be performed on several PDB structures (at least 5RLH, 5RLZ, 5RML & 5RMM). These PDB structures contain small organic ligands that will help to define pharmacophore constraints during the virtual screening stage. Thus, by contrast to orphan LRKK2-WDR domain, no blind docking simulation will be performed in the second challenge. Besides, additional binding pockets may also be identified using the SiteMap (Schrödinger, Inc) and MolSoft ICM Pocket Finder tools.

The virtual screening stage will consist in a several-step molecular docking workflow using the popular Glide (Schrödinger, Inc) docking tool. First, all the compounds will be docked using the fast HTVS scoring function. Then, the top 500K compounds will be docked using the SP function. The top 50K compounds will then be docking using the more accurate XP function. For each considered PDB structure, the top 20K poses from SP function and 5K poses from XP scoring functions will be finally merged before the refinement stage.

The extracted poses will be subsequently re-evaluated using the independent SeeSAR (BioSolveIT) tool using the HYDE scoring function with key structural waters added. This structure-based software will be mainly used to discard putative false positives from virtual screening (e.g., poses with either geometry or energy warnings).

Finally, a thorough visual inspection by experienced computational and medicinal chemists over all kept poses will be conducted to select the most promising compounds to be experimentally tested.

What makes your approach stand out from the community? (<100 words)

This approach combines high throughput docking with the re-evaluation of the top potential hit compounds from the VS as a post-processing stage. Besides, a visual analysis stage by molecular modeler and chemists will add some value to the workflow. Finally, only reasonable compounds from both physicochemical and medicinal chemistry point of views will be considered, thanks to the multi-stage ligand preparation workflow. This workflow has previously proven instrumental for in house projects in identification of quality hits.

Method Name
Hybrid: High-throughput docking coupled with reevaluation of top hits & docked poses
Commercial software packages used

Schrodinger's Drug Discovery Suite, BioSolvIT SeeSAR, MolSoft ICM.

Free software packages used

None.

Relevant publications of previous uses by your group of this software/method

We do not usually publish on Hit ID efforts. We publish and patent progress made in Drug Discovery projects.

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