E. Katkova Docking and postprocessing: application to design of urokinase inhibitors // 2nd French-Russian Workshop on Chemoinformatics and Bioinformatics, Kazan, September 17th 2012, p.16.

Urokinase-type plasminogen activator (uPA) plays an important role in the regulation of diverse physiologic and pathologic processes. Experimental research has shown that elevated uPA expression is associated with cancer progression, metastasis, and shortened survival in patients, whereas suppression of proteolytic activity of uPA leads to evident decrease of metastasis. Therefore, uPA has been considered as a promising molecular target for development of anticancer drugs. The present study sets out to investigate the new selective uPA inhibitors using a molecular modeling and computer drug design, particularly docking. Docking is a method which predicts the preferred orientation of ligand in an active site of a protein. Knowledge of the preferred orientation may be used to predict the strength of association or binding affinity between two molecules using for example scoring functions. Investigation involves following stages: computer modeling of the protein active site, development of docking methods positioning of known and potential inhibitors in the protein active site, validation of the docking program to work with the active site of uPA, postprocessing, search for uPA inhibitors among molecules from databases of ready compounds to find new uPA inhibitors, their optimization and experimental examination of new compounds. Docking was performed by the original docking program SOL using genetic algorithm and MMFF94 force field for energy calculations. Native uPA-ligand complexes from Protein Data Bank show good results in validation. Nevertheless to exclude some false-positive and false-negative results we also use postprocessing, which was carried out by program DISCORE for local optimization of complex and more accurate definition of scoring function. On the following stage compounds from ZINC database, ACB Blocks database and NCI Diversity database were docked. Calculations were performed on supercomputers Lomonosov and Chebyshev. About 800000 compounds were investigated. Compounds were ranged by scoring-functions and the ones with high computed activity were ordered and tested in vitro, and 14 of 40 show experimental activity. On basis of known uPA inhibitors and analysis of experimental results new compounds were also proposed, docked with SOL, processed with DISCORE, synthesized and tested in vitro. Five compounds of 20 give positive results in uPA inhibition. The present work has been supported by Lomonosov Moscow State University in the frame of postgenom project, grant RFFI 10-07-00595a and by Dimonta, Ltd.

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