Molecular docking and 3D-QSAR study on 4-(1H-indazol-4-yl) phenylamino and aminopyrazolopyridine urea derivatives as kinase insert domain receptor (KDR) inhibitors

Design, synthesis and biological evaluations of 2-amino-4-(1-piperidine) pyridine derivatives as novel anti crizotinib-resistant ALK/ROS1 dual inhibitors

ALK and ROS1 kinases have become promising therapeutic targets since Crizotinib was used to treat non-small-cell lung cancer clinically. Aiming to explore new potent inhibitors, a series of 2-amino-4-(1-piperidine) pyridine derivatives that stabilized a novel DFG-shifted conformation in the kinase domain of ALK were designed and synthesized on the base of lead compound A. Biological evaluation highlighted that most of these new compounds could also potently inhibit ROS1 kinase, leading to the promising inhibitors against both ROS1 and ALK. Among them, the representative compound 2e stood out potent anti-proliferative activity against ALK-addicted H3122 and ROS1-addicted HCC78 cell lines (IC₅₀ = 6.27 μM and 10.71 μM, respectively), which were comparable to that of Crizotinib. Moreover, 2e showed impressive enzyme activity against clinically Crizotinib-resistant ALK^L1196M with an IC₅₀ value of 41.3 nM, which was about 2-fold more potent than that of Crizotinib. 2e also showed potent inhibitory activity in about 6-fold superior to Crizotinib (IC₅₀: 104.7 nM vs. 643.5 nM) in Ba/F3 cell line harboring ROS1^G2032R. Furthermore, molecular modeling disclosed that all the representative inhibitors could dock into the active site of ALK and ROS1, which gave a probable explanation of anti Crizotinib-resistant mutants. These results indicated that our work has established a path forward for the generation of anti Crizotinib-resistant ALK/ROS1 dual inhibitors.

Comparative Molecular Field Analysis and Molecular Docking Studies on Quinolinone Derivatives Indicate Potential Hepatitis C Virus Inhibitors

Presently, there are no effective vaccines and anti-virals for the prevention and treatment of Hepatitis C virus infections and hence there is an urgent need to develop potent HCV inhibitors. In this study, we have carried out molecular docking, molecular dynamics and 3D-QSAR on heteroaryl 3-(1,1-dioxo-2H-(1,2,4)-benzothiadizin-3-yl)-4-hydroxy-2(1H)-quinolinone series using NS5B protein. Total of 41 quinolinone derivatives is used for molecular modeling study. The binding conformation and hydrogen bond interaction of the docked complexes were analyzed to model the inhibitors. We identified the molecule XXXV that had a higher affinity with NS5B. The molecular dynamics study confirmed the stability of the compound XXXV-NS5B complex. The developed CoMFA descriptors parameters, which were calculated using a test set of 13 compounds, were statistically significant. Our results will provide useful insights and lead to design potent anti-Hepatitis C virus molecules.

Cheminfomatic-based Drug Discovery of Human Tyrosine Kinase Inhibitors

Receptor Tyrosine Kinases (RTKs) are essential components for regulating cell-cell signaling and communication events in cell growth, proliferation, differentiation, survival and metabolism. Deregulation of RTKs and their associated signaling pathways can lead to a wide variety of human diseases such as immunodeficiency, diabetes, arterosclerosis, psoriasis and cancer. Thus RTKs have become one of the most important drug targets families in recent decade. Pharmaceutical companies have dedicated their research efforts towards the discovery of small-molecule inhibitors of RTKs, many of which had been approved by the U.S. Food and Drug Administration (US FDA) or are currently in clinical trials. The great successes in the development of small-molecule inhibitors of RTKs are largely attributed to the use of modern cheminformatic approaches to identifying lead scaffolds. Those include the quantitative structure-activity relationship (QSAR) modeling, as well as the structure-, and ligand-based pharmacophore modeling techniques in this case. Herein we inspected the literature thoroughly in an effort to conduct a comparative analysis of major findings regarding the essential structure-activity relationships (SARs)/pharmacophore features of known active RTK inhibitors, most of which were collected from cheminformatic modeling approaches.

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

Three dimensional quantitative structure-activity relationship of 5H-Pyrido[4,3-b]indol-4-carboxamide JAK2 inhibitors

Janus kinase 2 (JAK2) is an intracellular nonreceptor tyrosine kinase that belongs to the JAK family of kinases, which play an important role in survival, proliferation, and differentiation of a variety of cells. JAK2 inhibitors are potential drugs for the treatment of myeloproliferative neoplasms. The three dimensional quantitative structure-activity relationships have been studied on a series of JAK2 inhibitors by comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA). The CoMFA model had a cross-validated coefficient q² of 0.633, and the relation non-cross-validated coefficient r² of 0.976. The F value is 225.030. The contributions of steric and electrostatic fields to the activity are 55.2% and 44.8%, respectively. For the CoMSIA study, the q², r², and F values of the model are 0.614, 0.929, and 88.771, respectively. The contributions of steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond donor fields to the activity are 27.3%, 23.9%, 16.4%, 21.7%, and 10.7%, respectively. The CoMFA and CoMSIA models showed strong predictive ability, and the 3D contour plots give the basis on the structure modification of JAK2 inhibitors.

Analysis of Ah receptor binding affinities of polybrominated diphenyl ethers via in silico molecular docking and 3D-QSAR

Polybrominated diphenyl ethers (PBDEs) have become ubiquitous contaminations due to their use as flame retardants. The structural similarity of PBDE to some dioxin-like compounds suggested that they may share similar toxicological effects: they might activate the aryl hydrocarbon receptor (AhR) signal transduction pathway and thus might have adverse effects on wildlife and humans. In this study, in silico computational workflow combining molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) was performed to investigate the binding interactions between PBDEs and AhR and the structural features affecting the AhR binding affinity of PBDE. The molecular docking showed that hydrogen-bond and hydrophobic interactions were the major driving forces for the binding of ligands to AhR, and several key amino acid residues were also identified. The CoMSIA model was developed from the conformations obtained from molecular docking and exhibited satisfactory results as q (2) of 0.605 and r (2) of 0.996. Furthermore, the derived model had good robustness and statistical significance in both internal and external validations. The 3D contour maps generated from CoMSIA provided important structural features influence the binding affinity. The obtained results were beneficial to better understand the toxicological mechanism of PBDEs.

Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on estrogenic activity of hydroxylated polychlorinated biphenyls

Hydroxylated polychlorinated biphenyls (HO-PCBs), major metabolites of PCBs, have been reported to present agonist or antagonist interactions with estrogen receptor α (ERα) and induce ER-mediated responses. In this work, a multistep framework combining molecular docking, molecular dynamics (MD) simulations, and structure-based three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed to explore the influence of structural features on the estrogenic activities of HO-PCBs, and to investigate the molecular mechanism of ERα-ligand interactions. The CoMSIA (comparative molecular similarity indices analysis) model was developed from the conformations obtained from molecular docking. The model exhibited statistically significant results as the cross-validated correlation coefficient q² was 0.648, the non-cross-validated correlation coefficient r² was 0.968, and the external predictive correlation coefficient r(pred)² was 0.625. The key amino acid residues were identified by molecular docking, and the detailed binding modes of the compounds with different activities were determined by MD simulations. The binding free energies correlated well with the experimental activity. An energetic analysis, MM-GBSA energy decomposition, revealed that the van der Waals interaction was the major driving force for the binding of compounds to ERα. The hydrogen bond interactions between the ligands and residue His524 help to stabilize the conformation of ligands at the binding pocket. These results are expected to be beneficial to predict estrogenic activities of other HO-PCB congeners and helpful for understanding the binding mechanism of HO-PCBs and ERα.

De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction

Vascular endothelial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR) have been identified as promising targets for novel anticancer agents. To achieve new potent inhibitors of KDR, we conducted molecular fragment replacement (MFR) studies for the understanding of 3D-QSAR modeling and the docking investigation of arylphthalazines and 2-((1H-Azol-1-yl)methyl)-N-arylbenzamides-based KDR inhibitors. Two favorable 3D-QSAR models (CoMFA with q(2), 0.671; r(2), 0.969; CoMSIA with q(2), 0.608; r(2), 0.936) have been developed to predict the biological activity of new compounds. The new molecular database generated by MFR was virtually screened using Glide (docking) and further evaluated with CoMFA prediction, protein-ligand interaction fingerprint (PLIF) and ADMET analysis. 44 N-(pyridin-4-ylmethyl)aniline derivatives as novel potential KDR inhibitors were finally obtained. In this paper, the work flow developed could be applied to de novo drug design and virtual screening potential KDR inhibitors, and use hit compounds to further optimize and design new potential KDR inhibitors.

Pyrrolo[3,2-d]pyrimidine derivatives as type II kinase insert domain receptor (KDR) inhibitors: CoMFA and CoMSIA studies

Kinase insert domain receptor (KDR) inhibitors have been proved to be very effective anticancer agents. Molecular docking, 3D-QSAR methods, CoMFA and CoMSIA were performed on pyrrolo[3,2-d]pyrimidine derivatives as non-ATP competitive KDR inhibitors (type II). The bioactive conformation was explored by docking one potent compound 20 into the active site of KDR in its DFG-out inactive conformation. The constructed CoMFA and CoMSIA models produced statistically significant results with the cross-validated correlation coefficients q² of 0.542 and 0.552, non-cross-validated correlation coefficients r² of 0.912 and 0.955, and predicted correction coefficients r²_pred of 0.913 and 0.897, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of a series of new potent KDR inhibitors.