Using our Binary Star platform, we will employ a comprehensive computational protocol to enable the discovery and optimization of novel lead compounds for the ADPr site of SARS-CoV-2 Nsp3 macrodomain (Mac1). We will run a target analysis workflow (target validation and identification step) for the experimentally determined high-resolution structures of SARS-CoV-2 Nsp3 Mac1, to choose a suitable structure for the virtual screening campaign. Protein structures will be prepared with Maestro´s Protein Preparation Wizard to resolve clashes and missing atoms. Protonation states of the titratable residues will be assigned using the PROPKA tool. By leveraging the Binary Star database (a carefully curated library of the REAL Enamine database), we will generate a targeted sub-library for designing small-molecule Nsp3 Mac1 binders. This sub-library will include only PAINS-free molecules (to reduce the risk of confronting false positives) with good ADMET properties (e.g., molecules with favourable cell permeability, acceptable aqueous solubility, and elimination of compounds with potential toxicophores). Also, carboxylic acid-containing compounds will be filtered out from the sub-library. It should be mentioned that about 400 million compounds from the REAL Enamine database will be preprocessed and filtered using in-house scripts to build up the Binary Star database (3D ready-to-dock SDF format). Our in silico pipeline will involve pharmacophoric modelling, which will be followed by molecular docking for virtual screening. Common pharmacophore hypotheses will be created using a diverse set of known Nsp3 Mac1 cognate ligands with the perception of pharmacophore features coming from the recognition of key receptor-ligand interactions based on 3D experimentally determined structures of SARS-CoV-2 Nsp3 Mac1. Subsequently, molecular docking will be done using the standard precision (SP) Glide docking score. The top 1000 docked compounds will be re-docked using extra-precision (XP) Glide docking score including strain energy corrections.  The top hits from the virtual screening will be clustered into groups based on their scaffold similarity. Next, all-atom molecular dynamics (MD) simulations will be conducted to study the relative stability of the receptor–ligand interactions of the top hits. Finally, to prioritize compounds for in vitro testing, we will utilize more rigorous and expensive alchemical free energy perturbation (FEP) calculations (following the protocol reported by Jiang et al, DOI: 10.1021/acs.jcim.9b00362) to accurately predict the potency of the selected top binders. This comprehensive in silico protocol is expected to provide potent and novel candidates of SARS-CoV-2 Nsp3 Mac1 that can be further experimentally validated and optimized through biochemical assays.

First of all, we will use a carefully curated library of drug-like molecules that are PAINS-free and with good ADME properties. Second, leveraging the available information of known actives, we will perform enrichment calculations for the high-throughput virtual screening. Finally, to increase the hit rate of the selected top molecules, we will perform MD simulations followed by rigorous FEP calculations. We believe that this detailed protocol will provide potent drug candidates of SARS-CoV-2 Mac1. 

A comprehensive computational protocol that includes: De novo design, high-throughput docking, MD simulations, and FEP calculations.

Schrödinger 

AMBER.

NAMD

VMD

CHARMM-GUI

 

 

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Abu-Saleh, A.A.A; Awad, I.E.; Yadav, A.; Poirier, R.A. (2020), Discovery of Potent Inhibitors for SARS-CoV-2’s Main Protease by Ligand-based/Structure-based Virtual Screening, MD Simulations, and Binding Energy Calculations. Physical Chemistry Chemical Physics 22, 23099-23106. DOI: 10.1039/D0CP04326E

Awoonor-Williams, E. and Abu-Saleh, A.A.A. (2021), Covalent and non-covalent binding free energy calculations for peptidomimetic inhibitors of SARS-CoV-2 main protease. Physical Chemistry Chemical Physics 23, 6746-6757. DOI: 10.1039/D1CP00266J

Preetleen Kathuria; Prebhleen Singh; Purshotam Sharma, and Stacey D. Wetmore; Replication of the Aristolochic Acid I Adenine Adduct (ALI-N6-A) by a Model Translesion Synthesis DNA Polymerase: Structural Insights on the Induction of Transversion Mutations from Molecular Dynamics Simulations. Chem. Res. Toxicol. 2020, 33, 10, 2573–2583. DOI: 10.1021/acs.chemrestox.0c00183