Identification of novel discoidin domain receptor 1 (DDR1) inhibitors using E-pharmacophore modeling, structure-based virtual screening, molecular dynamics simulation and MM-GBSA approaches

Dysregulation of the discoidin domain receptor (DDR1), a collagen-activated receptor tyrosine kinase, has been linked to several human cancer diseases including non-small cell lung carcinoma (NSCLC), ovarian cancer, glioblastoma, and breast cancer, in addition to several inflammatory and neurological conditions. Although there are some selective DDR1 inhibitors that have been discovered during the last two decades, a combination of elevated cytotoxicity, kinome selectivity and/or poor DMPK profile has prevented more in-depth studies from being performed. As such, no DDR1 inhibitor has reached clinical investigation to date, forming an urgent need to develop specific DDR1 inhibitor(s) using various drug discovery means. However, the recent discovery of VU6015929, a potent and selective DDR1 kinase inhibitor, with enhanced physiochemical and DMPK properties in addition to its clean kinome profile marked a milestone in the development of DDR1 inhibitors. Herein, VU6015929 was used to construct a 3D e-pharmacophore model which was validated via calculating the difference of score between the active compounds and decoys. The validated e-pharmacophore model was then utilized to screen 20 million drug-like compounds obtained from the freely accessible Zinc database. The generated hits were ranked using high throughput virtual screening technique (HTVS), and the top 8 small molecules were subjected to a molecular docking study and MM-GBSA calculations. Protein-ligand complexes of compounds 1, 2, 3 and the standard compound (VU6015929) were performed for 100 ns and compared with the DDR1 unbound protein state and the DDR1 bound to a co-crystallized ligand. The molecular docking, MD and MM-GBSA outputs revealed compounds 1-3 as potential DDR1 inhibitors, with compound 2 displaying superior binding affinity, comparable binding stability and average binding free energy for the ligand-enzyme complex compared to VU6015929.

Analysis of the Glutamate Agonist LY404,039 Binding to Nonstatic Dopamine Receptor D2 Dimer Structures and Consensus Docking

Dopamine receptor D2 (D2R) plays an important role in the human central nervous system and is a focal target of antipsychotic agents. The D2^HighR and D2^LowR dimeric models previously developed by our group are used to investigate the prediction of binding affinity of the LY404,039 ligand and its binding mechanism within the catalytic domain. The computational data obtained using molecular dynamics simulations fit well with the experimental results. The calculated binding affinities of LY404,039 using MM/PBSA for the D2^HighR and D2^LowR targets were -12.04 and -9.11 kcal/mol, respectively. The experimental results suggest that LY404,039 binds to D2^HighR and D2^LowR with binding affinities (K_i) of 8.2 and 1640 nM, respectively. The high binding affinity of LY404,039 in terms of binding to [³H]domperidone was inhibited by the presence of a guanine nucleotide, indicating an agonist action of the drug at D2^HighR. The interaction analysis demonstrated that while Asp114 was among the most critical amino acids for D2^HighR binding, residues Ser193 and Ser197 were significantly more important within the binding cavity of D2^LowR. Molecular modeling analyses are extended to ensemble docking as well as structure-based pharmacophore model (E-pharmacophore) development using the bioactive conformation of LY404,039 at the binding pocket as a template and screening of small-molecule databases with derived pharmacophore models.