Computational Analysis of Binding Interactions between Novel Boronic Acid Derivatives and Urokinase Type Plasminogen Activator (uPA)

Abstract

The plasminogen activator (PA) system is an extracellular proteolytic enzyme system linked with various physiological and pathophysiological processes. A previous literature shows evidence to support that urokinase-type plasminogen activator (uPA) plays a significant role in tumour progression and metastasis. The components of the uPA system show altered expression patterns in several common malignancies, which have identified them as satisfactory diagnostic, prognostic, and therapeutic targets to reduce cancer-associated morbidity and mortality. Proof of uPA inhibition by the seven test ligands have been provided in previous research. However, the binding site and features involved in inhibition of uPA are unknown. Hence it is conducive to design specific inhibitors for the active binding site as an effort to cease the spread further. Fitting computational techniques are used for achieving set objectives. Structure based and ligand based computational techniques and quantum mechanical technique such as Density Functional Theory (DFT) are applied for the characterisation of binding energy and to observe interactions between novel boronic acid derivatives and urokinase-type plasminogen activator. Molecular Operating Environment (MOE) and Gold softwares were used for Molecular Docking simulations and generated results were compared to those of the previous study. The focus was to determine residues of uPA which are involved in high affinity binding to these seven inhibitors. MOE was used for designing pharmacophore model that highlights the descriptors that play important role in high affinity binding of the most promising ligand to receptor protein. Quantum mechanical studies were applied to the test ligand with most favourable binding interactions with the receptor protein, the ligand-protein complex as well as the receptor protein as it is equally important to perform calculations on each structure. Results presented here combine experimental and theoretical works for crafting uPA inhibitors in cancer treatment through a better understanding of the binding interaction of uPA and its inhibitors. Ligand SR3 was chosen as most suitable inhibitor among seven compounds based on docking results obtained through MOE and GOLD with score -3.2481 kcal/mol and 46.4523 kcal/mol respectively. These seven ligands were used for generating pharmacophore model through random selection with genetic algorithm by xiv MOE having sensitivity of 79% towards the test set, specificity of 78% towards test set and 51% calculated Mathews coefficient correlation. The ready model can be verified for liability through experimental methods. In Computational Quantum mechanical studies hybrid functional B3LYP in conjunction with basis set LANL2DZ of Density Functional Theory (DFT) on the extracted model of uPA binding site with ligand SR3 were applied based upon the electron density of uPA to find the binding energy of active ligand. A -2 charge is present on ASP189 of the binding cavity throughout the DFT simulations. From the computational analysis Geometric optimization (opt) gave values of 53.9 and single point energy (SPE) as -66.3 with self-consistent reaction field (SCRF) with calculated value of -49.0. Hence it is concluded that SR3 shows better binding with uPA binding pocket and there is a negative two charge on it ASP189 amino acid residue in the binding pocket.