Elucidating inhibitory models of the inhibitors of epidermal growth factor receptor by docking and 3D-QSAR

Epidermal growth factor receptor (EGFR) protein tyrosine kinases (PTKs) are attractive targets for anti-tumor drug design. Although thousands of their ligands have been studied as potential inhibitors against PTKs, there is no QSAR study that covers different kinds of inhibitors with observable structural diversity. However, by using this approach, we could mine far more useful information. Hence in order to better understand the binding model and the relationship between the physicochemical properties and the inhibitory activities of different kind of various inhibitors, molecular docking and 3D-QSAR, viz. CoMFA and CoMSIA, were combined to study 124 reported inhibitors with different scaffolds. Based on the docked binding conformations, highly reliable and predictive 3D-QSAR models were derived, which reveal how steric, electrostatic, and hydrophobic interactions contribute to inhibitors' bioactivities. This result also demonstrates that it is possible to include different kinds of inhibitors with observable structural diversity into one 3D-QSAR study. Therefore, this study not only casts light on binding mechanism between EGFR and its inhibitors, but also provides new hints for de novo design of new EGFR inhibitors with observable structural diversity.     

Molecular modeling studies,synthesis and biological evaluation of dabigatran analogues as thrombin inhibitors

In this work, 48 thrombin inhibitors based on the structural scaffold of dabigatran were analyzed using a combination of molecular modeling techniques. We generated three-dimensional quantitative structure–activity relationship (3D-QSAR) models based on three alignments for both comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) to highlight the structural requirements for thrombin protein inhibition. In addition to the 3D-QSAR study, Topomer CoMFA model also was established with a higher leave-one-out cross-validation q² and a non-cross-validation r², which suggest that the three models have good predictive ability. The results indicated that the steric, hydrophobic and electrostatic fields play key roles in QSAR model. Furthermore, we employed molecular docking and re-docking simulation explored the binding relationship of the ligand and the receptor protein in detail. Molecular docking simulations identified several key interactions that were also indicated through 3D-QSAR analysis. On the basis of the obtained results, two compounds were designed and predicted by three models, the biological evaluation in vitro (IC₅₀) demonstrated that these molecular models were effective for the development of novel potent thrombin inhibitors.     

3D QSAR CoMFA/CoMSIA, molecular docking and molecular dynamics studies of fullerene-based HIV-1 PR inhibitors

For the first time, a set of experimentally reported [60] fullerene derivatives were subjected to the 3D-QSAR/CoMFA and CoMSIA studies. The aim of this study is to propose a series of novel [60] fullerene-based inhibitors with optimal binding affinity for the HIV-1 PR enzyme. The position of the template molecule at the cavity of HIV-1 PR was optimized and 3D QSAR models were developed. Relative contributions of steric/electrostatic fields of the 3D-QSAR/CoMFA and CoMSIA models have shown that steric effects govern the bioactivity of the compounds, but electrostatic interactions play also an important role.The de novo drug design Leapfrog simulations provided a series of novel compounds with predicted improved inhibition effect.     

Understanding the structure-activity and structure-selectivity correlation of cyclic guanine derivatives as phosphodiesterase-5 inhibitors by molecular docking, CoMFA and CoMSIA analyses

Molecular docking and 3D-QSAR analyses were performed to understand how PDE5 and PDE6 interact with a series of (49) cyclic guanine derivatives. Using the conformations of the compounds revealed by molecular docking, CoMFA and CoMSIA analyses resulted in the first quantitative structure-activity relationship (QSAR) and first quantitative structure-selectivity relationship (QSSR) models (with high cross-validated correlation coefficient q(2) and conventional correlation coefficient r(2) values) for predicting the inhibitory activity against PDE5 and the selectivity against PDE6. The high q(2) and r(2) values, along with further testing, indicate that the obtained 3D-QSAR and 3D-QSSR models will be valuable in predicting both the inhibitory activity and selectivity of cyclic guanine derivatives for these protein targets. A set of 3D contour plots drawn based on the 3D-QSAR and 3D-QSSR models reveal some useful clues to improve both the activity and selectivity by modifying structures of the compounds. It has been demonstrated that both the steric and electrostatic factors should appropriately be taken into account in future rational design and development of more active and more selective PDE5 inhibitors for the therapeutic treatment of erectile dysfunction (ED).