Application of Molecular Modeling to Urokinase Inhibitors Development

Abstract

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 develop the new selective uPA inhibitors using computer-aided structural based drug design methods. Investigation involves the following stages: computer modeling of the protein active site, development and validation of computer molecular modeling methods: docking (SOL program), postprocessing (DISCORE program), direct generalized docking (FLM program), and the application of the quantum chemical calculations (MOPAC package), search of uPA inhibitors among molecules from databases of ready-made compounds to find new uPA inhibitors, and design of new chemical structures and their optimization and experimental examination. On the basis of known uPA inhibitors and modeling results, 18 new compounds have been designed, calculated using programs mentioned above, synthesized, and tested in vitro. Eight of them display inhibitory activity and two of them display activity about 10 μM.

Epitopes rationally selected through computational analyses induce T‐cell proliferation in mice and are recognized by serum from individuals infected with Schistosoma mansoni

“…The three‐dimensional structures of six most promiscuous epitopes were built and optimized using an extended conformation . The structure optimization process was applied to correct the geometric distortion in the molecules . Another important step performed before molecular docking was the solvation of the structures.…”

“…In this work, we used semiempirical methods for this purpose. Semiempirical methods use information obtained from experimental data and make the optimization of large structures possible, providing relatively accurate data in a short time …”

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms

“…This force field is not worse than many other popular force fields such as: AMBER [46], [47], OPLS-AA [48], CHARMM [49] etc. MMFF94 is implemented in the SOL docking program [10] used successfully for new inhibitors' development [50], [51], [52]. Moreover, it has been recently shown that the docking paradigm is true for some protein-ligand complexes, if the energy of the complex is calculated in the frame of the MMFF94 force field in vacuum [5].…”

Accuracy comparison of several common implicit solvent models and their implementations in the context of protein-ligand binding

“…good correspondence of the calculated hydration energies to experimentally measured ones for a set of more than 400 small molecules [26]. Taking into account that DISOLV and MCBHSOLV programs are used successfully for new inhibitors development [32–34] at the post-processing stage [10] and in the gridless docking procedure [35] in the frame of the MMFF94 force field [31] there is a need to compare results of DISOLV and MCBHSOLV calculations with ones performed with other implicit solvent programs and parameterization methods [14, 20–22, 25] for same sets of molecules. Here we will also examine a relatively recent addition to the family of GB models, GBNSR6, which has already demonstrated high accuracy in estimates of hydration free energies of small molecules [14].…”

“…Also, other studies [37, 38] demonstrated that calculation of small molecules solvation energies allows one to test whether the given parameterization is adequate, and to improve the underlying methods and force fields. In this respect, the novel quantum-chemical semi-empirical PM7 method [39] included in the MOPAC package [40] is becoming popular recently for new inhibitors development at the postprocessing stage [32, 33, 41]. Due to the unprecedentedly wide range of molecules used for the parameterization of the PM7 method and due to including corrections on dispersion interactions as well as ones for hydrogen and halogen bonds PM7 is significantly superior to previous semi-empirical methods in respect of calculation accuracy, especially for intermolecular interactions [39], including those semi-empirical methods used for the atomic charge calculations in some force fields, e.g.…”