The project will begin with a structure-based analysis of the RNA binding cavity of NSP13, based on the crystal structure 7KRN, using molecular dynamics simulations together with in-house program PyRod [1,2] to sample interaction points in the binding pocket. Briefly, PyRod traces water molecules in protein binding cavities and generates dynamic maps describing the interaction patterns of the water molecules with respect to the protein. This identifies water molecules whose displacement with appropriate ligand moieties should result in a more favorable free energy upon ligand binding, thus increasing the chance of identifying high-affinity ligands. The results from these analyses will be used to generate 3D pharmacophore features for 3D pharmacophore-based virtual screening of the Enamine Real database [3]. As a second approach, we will derive structure-based 3D pharmacophores of the co-crystallized ligands VXG, VXD and VWM of the 5RMM, 5RML and 5RLZ crystal structures respectively. Those will be aligned to the 3D pharmacophores generated by PyRod to optimize our screening pharmacophore. The initial list of hit compounds will firstly be filtered via molecular docking into the binding cavity and subsequent scoring of the docking poses against the initial screening pharmacophore [4-11]. The compounds will then further be filtered by the ACS substructure filter to remove pan-assay interference compounds (PAINS), and by chemical diversity via Tanimoto coefficients based on Morgan fingerprints of the hits. The final filtering step will comprise visual inspection to ensure shape complementarity of hits to the binding cavity.
