CONICET | Buscador de Institutos y Recursos Humanos

Nowadays, computational chemistry is a useful tool to identify and/or optimize novel and selective ligands for a particular protein. Docking programs are usually successful in reproduce the crystallographic binding mode, whereas scoring functions are much less successful to identify the corresponding "bioactive" binding mode. Therefore, it is important to determine which is the best docking protocol for the studied protein before performing computational simulations. Our study is focused on Checkpoint kinase 1 (Chk1), a serine/threonine protein kinase which plays a key role in DNA damage-induced checkpoints. It has been demonstrated that ChK1 inhibitors have potential to widen the therapeutic window for clinically-utilized DNA damaging agents in p53-deficient tumors.In this work we present the application of DockBench, a useful tool developed by Molecular Modeling Section group (Università degli Studi di Padova), to compare the performances of different docking/scoring combinations using the best 20 crystal structures of the protein Chk1 in complex with inhibitors. To evaluate the performance of each protocol, the presented tool uses a novel consensus-based function defined as "Protocol Score" based on RMSD average value and the number of conformations generated by docking algorithm having a RMSD lower than the crystal structure resolution (R).After the benchmark analysis GOLD-goldscore combination was appointed as the best protocol to perform a virtual screening to evaluate pyrazoloquinolinones as Chk1 inhibitors. Docking results were analyzed using Heat Maps and Interaction Energy Fingerprints graphs to evaluate mainly the electrostatic and hydrophobic interactions with key active site residues. In conclusion, a benchmark analysis was used to find the best docking protocol to perform the study of pyrazoloquinolinones as Chk1 inhibitors. After docking analysis the most promising compounds were selected to continue with other studies.