Design of Novel Chemotherapeutic Agents Targeting Checkpoint Kinase 1 Using 3D-QSAR Modeling and Molecular Docking Methods.

BACKGROUND: Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs. OBJECTIVE: Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors. METHODS: 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock. RESULTS: The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively. CONCLUSION: A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.

Molecular insights on TNKS1/TNKS2 and inhibitor-IWR1 interactions.

Tankyrases (TNKS) belong to the poly(ADP-ribose)polymerase (PARP) protein super family and play a vital role in the Wnt/ß-catenin signaling pathway. TNKS is a potential target for therapeutic intervention against various cancers, heritable diseases (e.g. cherubism) and implications in the replication of herpes simplex virus (HSV). The recent discovery of the structure of TNKS with an IWR1 inhibitor has provided insight into the binding modes which are specific for the TNKS protein which will aid in the development of drugs that are specific for the TNKS protein. The current study investigates molecular interactions between the induced pocket of TNKS1 and TNKS2 with an IWR1 compound using computational approaches. Molecular docking analysis of IWR1 at the induced pocket of TNKS1 and TNKS2 was performed. The resulting protein-ligand complexes were simulated for a timescale of 100 ns. Results revealed the stable binding of IWR1 at the induced pocket of TNKS1 and TNKS2 proteins. Apart from active site amino acids, π-π stack paring interactions were also crucial for the protein-ligand binding and stability of the complex. Further, energy-optimized pharmacophore mapping was performed and the resulting pharmacophore model contained a four (TNKS1-IWR1) and five (TNKS2-IWR1) featured sites. Based on the pharmacophore models, the best inhibitors were screened from the ZINC natural product compound database and these could be used as potential drugs against TNKS1 and TNKS2.

Theoretical characterization of galanin receptor type 3 (Gal3 ) and its interaction with agonist (GALANIN) and antagonists (SNAP 37889 and SNAP 398299): an in silico analysis.

In this study, we report on modeling of galanin receptor type 3 and its interaction with agonist and antagonists using in silico methodologies. Comparative structural modeling of galanin receptor type 3 was based on multiple templates. With the availability of reported selective galanin receptor type 3 antagonists, docking was carried out into the predicted binding site. Similarly, galanin, a reported agonist, was also modeled and then docked into the receptor's active site. CoMFA models were developed using ligand-based (q(2)  = 0.537, r(2)  = 0.961, noc = 5), and receptor-guided (docked mode 1: q(2)  = 0.574, r(2)  = 0.946, noc = 5), (docked mode 2: q(2)  = 0.499, r(2)  = 0.954, noc = 5) alignment schemes. CoMFA contour analysis revealed that bulky substitution around the meta position of the phenyl ring, as well as optimal substitution (para) of the phenyl ring, could produce molecules with improved activity. We also found that Gln79, Ile82, Asp86, Trp88, His99, Ile102, Tyr103, Glu170, Pro174, Ala175, Asp185, Arg273, His277, and Tyr281 are crucial, and mutational studies on these residues could be helpful. The results obtained from this study can further be exploited for structure-based drug design and also help the researchers to identify novel antagonists targeting galanin receptor type 3.

Binding site analysis of CCR2 through in silico methodologies: docking, CoMFA, and CoMSIA.

Chemokine receptor (CCR2) is a G protein-coupled receptor that contains seven transmembrane domains. CCR2 is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity and type 2 diabetes. Herein, we report on a binding site analysis of CCR2 through docking and three-dimensional quantitative structure-activity relationship (3D-QSAR). The docking study was performed with modeled receptor (CCR2) using ß2-andrenergic receptor structure as a template. Comparative molecular field analysis (CoMFA)- and comparative molecular similarity indices analysis (CoMSIA)-based 3D-QSAR models were developed using two different schemes: ligand-based (CoMFA; q² =0.820, r² =0.966, r²(pred) = 0.854 and CoMSIA; q² =0.762, r² =0.846, r²(pred) = 0.684) and receptor-guided (CoMFA; q² =0.753, r² =0.962, r²(pred) =0.786, CoMSIA; q² =0.750, r² =0.800, r²(pred)=0.797) methods. 3D-QSAR analysis revealed the contribution of electrostatic and hydrogen bond donor parameters to the inhibitory activity. Contour maps suggested that bulky substitutions on the para position of R¹ substituted phenyl ring, electronegative and donor substitutions on meta (5') and ortho (2') position of R² substituted phenyl ring were favorable for activity. The results correlate well with previous results and newly report additional residues that may be crucial in CCR2 antagonism.

HQSAR study of beta-ketoacyl-acyl carrier protein synthase III (FabH) inhibitors.

The enzyme FabH catalyzes the initial step of fatty acid biosynthesis via a type II fatty acid synthase. The pivotal role of this essential enzyme combined with its unique structural features and ubiquitous occurrence in bacteria has made it an attractive new target for the development of antibacterial and antiparasitic compounds. Predictive hologram quantitative structure activity relationship (HQSAR) model was developed for a series of benzoylamino benzoic acid derivatives acting as FabH inhibitor. The best HQSAR model was generated using atoms and bond types as fragment distinction and 4-7 as fragment size showing cross-validated q2 value of 0.678 and conventional r2 value of 0.920. The predictive ability of the model was validated by an external test set of 6 compounds giving satisfactory predictive r2 value of 0.82. The contribution maps obtained from this model were used to explain the individual atomic contributions to the overall activity. It was confirmed from the contribution map that both ring A and ring C play a vital role for activity. Moreover hydroxyl substitution in the ortho position of ring A is favorable for better inhibitory activity. Therefore the information derived from the contribution map can be used to design potent FabH inhibitors.