Computational characterization of the interactions between novel Boronic Acid derivatives with urokinase-type plasminogen activator (uPA) and their binding energy

Abstract

1.AbstractUrokinase type plasminogen activator is expected to play a significant role in metastasis therefore various inhibitors are being prepared for this target protein. However, the binding site with residues that are involved in binding and inhibition is unidentified. Hence, comprehensive computational techniques are applied for finding the binding pocket, important amino acid residues and for the characterization of the binding energy of the best ligand among seven novel boronic acid derivative inhibitors within the binding pocket. Among seven test compounds, C14H21BN2O2S showed best results in structure based molecular docking through Molecular Operating Environment (MOE) and GOLD suit with −3.2481 kcal/mol binding affinity and 46.4523 GOLD Score. C14H21BN2O2S also showed high binding affinity within the binding pocket in DFT (Density Functional Theory) studies. DFT was carried out using hybrid functional B3LYP in combination with basis set LANL2DZ level of density functional theory on the extracted geometry of bound ligand C14H21BN2O2S to the binding pocket of uPA with a −2 charge on amino-acid residue ASP189. Computational analysis values on Geometric Optimization (opt), Single Point Energy (SPE) and Self-Consistent Reaction Field (SCRF) were 53.9, −66.3 and −49.0 respectively. Hence it is concluded that C14H21BN2O2S shows better binding with uPA binding pocket when there is a negative two charge on it ASP189 amino acid residue in the binding pocket. These seven ligands were also used for generating pharmacophore model through random selection with genetic algorithm by MOE having sensitivity of 79% towards the test set, specificity of 78% towards test set and 51% calculated Matthews coefficient correlation.2.Author SummaryBoronic-acid based proteasome inhibitor like Bortezomib and Ixazomib are Food and Drug Administration (FDA) approved drugs, which are being used for fighting cancer. They can be considered as a template for understanding the pharmacokinetics and role of Boronic-acid ligands in the process. Boron-based warheads with stabilised functionality along with reduced toxicity are beneficent therapeutically. We have utilized computational quantum mechanical techniques in predicting binding free energies for ligands and proteins in a solvent environment. Instead of providing precise estimations, these techniques are more suitable for prediction purposes. The main challenge is developing inhibitors for uPA sub-sites that have high selectivity, potency, and improved pharmacokinetic properties. We have used Molecular docking and ligand-based techniques to analyze the binding interactions between seven ligands and uPA. Among these ligands, C14H21BN2O2Sis identified as the most appropriate inhibitor based on scores and its interactions with specific receptor amino acid residues. Computational quantum mechanical studies are conducted using electron density and hybrid functional B3LYP to determine the binding energy. A pharmacophore model is designed to identify crucial descriptors and search for compounds that can effectively inhibit uPA. The model’s accuracy is assessed through QSAR analysis, which reveals favorable hydrogen bond donor and acceptor groups as well as aromatic hydrophobic rings in proximity to the ligands. The designed model demonstrates good sensitivity, specificity, and calculated Matthews coefficient correlation.