Ligand-based virtual screening,molecular docking,QSAR and pharmacophore analysis of quercetin-associated potential novel analogs against epidermal growth factor receptor

The present study was to explore expectation and examination of therapeutic potential quercetin analogs as efficient anticancer agents against human epidermal growth factor receptor (EGFR), which is a consistent hallmark for moderating the non-small-cell lung carcinoma (NSCLC). Here, ligand-based virtual screening, pharmacophore approach and molecular docking were established as rational strategies for recognition of small analogs against the ligand binding domain of EGFR (PDB code: 1XKK). Adverse effects, toxicogenomics and pharmacokinetics reported that 10 candidates showed reliable consequences with less side effects and more efficient for target receptor. Protein–ligand interaction profiles revealed that the probable H-bonds, atomic-π contacts, salt bridges and van der Waals interactions sustain the complexity and stability of receptor structure; thus, they could complicate to generate single alteration acquired for drug resistance. In silico anticancer properties explain the lead scaffolds which are assumed to be flexible and experimentally proved chemicals. The overall consequences indicated that recognized leads could be utilized as reference skeletons for new inhibitors envisaging toward EGFR to ameliorate NSCLC and other malignant disorders.     

Computational screening,ensemble docking and pharmacophore analysis of potential gefitinib analogues against epidermal growth factor receptor

The observable mutated isoforms of epidermal growth factor receptor (EGFR) are important considerable therapeutic benchmarks in moderating the non-small cell lung cancer (NSCLC). Recently, quinazoline-based ATP competitive inhibitors have been developed against the EGFR; however, these imply the mutation probabilities, which contribute to the discovery of high probable novel inhibitors for EGFR mutants. Therefore, SAR-based bioactivity analysis, molecular docking and computational toxicogenomics approaches were performed to identify and evaluate new analogs of gefitinib against the ligand-binding domain of the EGFR double-mutated model. From the diverse groups of molecular clustering and molecular screening strategies, top high-binding gefitinib-analogues were identified and studied against EGFR core cavity through three-phase ensemble docking approach. Resulted high possible leads showed good binding orientations than gefitinib (positive control) thus they were subjected to pharmacophore analysis that possesses possible molecular assets to tight binding with EGFR domain. Residues Ser720, Arg841 and Trp880 were observed as novel hot spots and involved in H-bonds, pi-stacking and π-cation interactions that contribute additional electrostatic potency to sustain stability and complexity of protein-ligand complexes, thus they have ability to profoundly adopted by pharmacophoric features. Furthermore, lead molecules have an inhibition percent probability, anticancer potency, toxic impacts, flexible pharmacokinetics, potential gene-chemical interactions towards EGFR were revealed by computational systems biology tools. Our multiple screening strategies confirmed that the druggable sub-pocket was crucial to strong EGFR-ligand binding. The essential pharmacophoric features of ligands provided viewpoints for new inhibitors envisaging, and predicted scaffolds could used as anticancer agents against selected EGFR mutated isoforms.     

In silico design of potent EGFR kinase inhibitors using combinatorial libraries

This paper is an attempt to design 4-anilinoquinazoline compounds having promising anticancer activities against epidermal growth factor (EGFR) kinase inhibition, using virtual combinatorial library approach. Partial least squares method has been applied for the development of a quantitative structure–activity relationship (QSAR) model based on training and test set approaches. The partial least squares model showed some interesting results in terms of internal and external predictability against EGFR kinase inhibition for such type of anilinoquinazoline derivatives. In virtual screening study, out of 4860 compounds in chemical library, 158 compounds were screened and finally, 10 compounds were selected as promising EGFR kinase inhibitors based on their predicted activities from the QSAR model. These derivatives were subjected to molecular docking study to investigate the mode of binding with the EGFR kinase, and the two compounds (ID 3639 and 3399) showing similar type of docking score and binding patterns with that of the existing drug molecules like erlotinib were finally reported.     

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.     

Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation,protein–ligand interaction fingerprint, 3D pharmacophore,docking and 3D QSAR

Abstract

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein–ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1–p4) and compound q1) were selected for further analysis.

Communicated by Ramaswamy H. Sarma     

Docking and 3D QSAR study of thiourea analogs as potent inhibitors of influenza virus neuraminidase

Surflex-Dock was applied to study interactions between 30 thiourea analogs and neuraminidase (NA). The docking results showed that hydrogen bonding and electrostatic interactions were highly correlated with the activities of neuraminidase inhibitors (NIs), followed by hydrophobic and steric factors. Moreover, there was a strong correlation between the predicted binding affinity (total score) and experimental pIC₅₀ (correlation coefficient r = 0.870; P < 0.0001). A three dimensional holographic vector of atomic interaction field (3D-HoVAIF) was employed to construct a QSAR model. The r ², q ² and r ² _test values of the optimal QSAR model were 0.849, 0.724 and 0.689, respectively. From the QSAR model, it could be seen that electrostatic, hydrophobic and steric interactions were closely related to inhibitory activity, which was consistent with the docking results. Based on the docking and QSAR results, five new compounds with high predicted activities were designed.     

Synthesis of 2-,4,-6-, and/or 7-substituted quinoline derivatives as human dihydroorotate dehydrogenase (hDHODH) inhibitors and anticancer agents: 3D QSAR-assisted design

Following our research for human dihydroorotate dehydrogenase (hDHODH) inhibitors as anticancer agents, herein we describe 3D QSAR-based design, synthesis and in vitro screening of 2-,4,-6-, and/or 7-substituted quinoline derivatives as hDHODH inhibitors and anticancer agents. We have designed 2-,4,-6-, and/or 7-substituted quinoline derivatives and predicted their hDHODH inhibitory activity based on 3D QSAR study on 45 substituted quinoline derivatives as hDHODH inhibitors, and also predicted toxicity. Designed compounds were docked into the binding site of hDHODH. Designed compounds which showed good predictive activity, no toxicity, and good docking score were selected for the synthesis, and in vitro screening as hDHODH inhibitors in an enzyme inhibition assay, and anticancer agents in MTT assay against cancer cell lines (HT-29 and MDA-MB-231). Synthesized compounds 7 and 14 demonstrated IC₅₀ value of 1.56?µM and 1.22?µM, against hDHODH, respectively, and these are our lead compounds for the development of new hDHODH inhibitors and anticancer agents.     

First report on exploring structural requirements of alpha and beta thymidine analogs for PfTMPK inhibitory activity using in silico studies

With the emergence of multi-drug resistance of the currently available antimalarial drugs including the “magic bullet” artemisinin derivatives in the market, there is an urgent need for discovery and development of new potent antimalarial molecules. The present work deals with quantitative structure–activity relationship (QSAR) modeling, pharmacophore mapping and docking studies of a series of 35 thymidine analogs as inhibitors of Plasmodium falciparum thymidylate kinase (PfTMPK), an enzyme that catalyzes phosphorylation of thymidine monophosphate (TMP) to thymidine diphosphate (TDP). The models were validated both internally and externally and significant statistical results were obtained, indicating the robustness and reliability of the developed models. The docking study was performed using the LigandFit option of receptor–ligand interactions protocol section available in Discovery Studio 2.1 where lower RMSD values (0.6931 Å) between the co-crystallized ligand and re-docked ligand assured that the ligand was bound in the same binding pocket. The QSAR, pharmacophore mapping and docking studies provide an understanding of important structural requirements or essential molecular properties, or features of molecules, and important binding interactions, and provide an important guidance for the chemist to synthesis of new molecules with improved PfTMPK inhibitory activity profile. This work revealed the importance of –NH-fragment, electrophilicity of the molecules and the number of oxygen atom towards the PfTMPK inhibitory activity of the molecules. To the best of our knowledge, this work presents the first QSAR and pharmacophore report for thymidine analogs which may serve as an efficient tool for the design and synthesis of potent molecules as PfTMPK inhibitors to address the increasing threat of multi-drug resistance against P. falciparum.     

Pharmacophore modeling, 3D-QSAR,and in silico ADME prediction of N-pyridyl and pyrimidine benzamides as potent antiepileptic agents

Biological mechanism attributing mutations in KCNQ2/Q3 results in benign familial neonatal epilepsy (BFNE), a rare form of epilepsy and thus neglected. It offers a potential target for antiepileptic drug discovery. In the present work, a pharmacophore-based 3D-QSAR model was generated for a series of N-pyridyl and pyrimidine benzamides possessing KCNQ2/Q3 opening activity. The pharmacophore model generated contains one hydrogen bond donor (D), one hydrophobic (H), and two aromatic rings (R). They are the crucial molecular write-up detailing predicted binding efficacy of high affinity and low affinity ligands for KCNQ2/Q3 opening activity. Furthermore, it has been validated by using a biological correlation between pharmacophore hypothesis-based 3D-QSAR variables and functional fingerprints of openers responsible for the receptor binding and also by docking of these benzamides into the validated homology model. Excellent statistical computational tools of QSAR model such as good correlation coefficient (R^2?>^?0.80), higher F value (F?>?39), and excellent predictive power (Q²?>?0.7) with low standard deviation (SD <0.3) strongly suggest that the developed model could be used for prediction of antiepileptic activity of newer analogs. A preliminary pharmacokinetic profile of these derivatives was also performed on the basis of QikProp predictions.     

In silico QSAR studies of anilinoquinolines as EGFR inhibitors

Members of the epidermal growth factor receptor (EGFR) family of proteins are frequently overactive in solid tumors. A relatively new therapeutic approach to inhibit the kinase activity is the use of ATP-competitive small molecules. In silico techniques were employed to identify the key interactions between inhibitors and their protein receptors. A series of EGFR inhibitory anilinoquinolines was studied within the framework of hologram quantitative structure activity relationship (HQSAR), density functional theory (DFT)-based QSAR, and three-dimensional (3D) QSAR (CoMFA/CoMSIA). The HQSAR analysis implied that substitutions at certain sites on the inhibitors play an important role in EGFR inhibition. DFT-based QSAR results suggested that steric and electronic interactions contributed significantly to the activity. Ligand-based 3D-QSAR and receptor-guided 3D-QSAR analyses such as CoMFA and CoMSIA techniques were carried out, and the results corroborated the previous two approaches. The 3D QSAR models indicated that steric and hydrophobic interactions are dominant, and that substitution patterns are an important factor in determining activity. Molecular docking was helpful in identifying a bioactive conformer as well as a plausible binding mode. The docked geometry-based CoMFA model with steric and electrostatic fields effect gave q ² = 0.66, r ² = = 0.94 with r ² _predictive = 0.72. Similarly, CoMSIA with hydrophobic field gave q ² = 0.59, r ² = 0.85 with r ² _predictive = 0.63. Bulky groups around site 3 of ring “C”, and hydrophilic and bulky groups at position 6 of ring “A” are desirable, with a hydrophobic and electron-donating group at site 7 of ring “A” being helpful. Accordingly, potential EGFR inhibitors may be designed by modification of known inhibitors.     

Computational and Biochemical Discovery of RSK2 as a Novel Target for Epigallocatechin Gallate (EGCG)

The most active anticancer component in green tea is epigallocatechin-3-gallate (EGCG). Protein interaction with EGCG is a critical step for mediating the effects of EGCG on the regulation of various key molecules involved in signal transduction. By using computational docking screening methods for protein identification, we identified a serine/threonine kinase, 90-kDa ribosomal S6 kinase (RSK2), as a novel molecular target of EGCG. RSK2 includes two kinase catalytic domains in the N-terminal (NTD) and the C-terminal (CTD) and RSK2 full activation requires phosphorylation of both terminals. The computer prediction was confirmed by an in vitro kinase assay in which EGCG inhibited RSK2 activity in a dose-dependent manner. Pull-down assay results showed that EGCG could bind with RSK2 at both kinase catalytic domains in vitro and ex vivo. Furthermore, results of an ATP competition assay and a computer-docking model showed that EGCG binds with RSK2 in an ATP-dependent manner. In RSK2^+/+ and RSK2^-/- murine embryonic fibroblasts, EGCG decreased viability only in the presence of RSK2. EGCG also suppressed epidermal growth factor-induced neoplastic cell transformation by inhibiting phosphorylation of histone H3 at Ser10. Overall, these results indicate that RSK2 is a novel molecular target of EGCG.     

Identification of novel drug-resistant EGFR mutant inhibitors by in silico screening using comprehensive assessments of protein structures

EGFR is a target protein for the treatment of non small cell lung cancer (NSCLC). The mutations associated with the activation of EGFR kinase activity, such as L858R and G719S, destabilize the inactive conformation of EGFR and are closely linked with the development of NSCLC. The additional T790M mutation reportedly causes drug resistance against the commercially available EGFR inhibitors, gefitinib and erlotinib. In this study, we searched for novel G719S/T790M EGFR inhibitors by a new in silico screening strategy, using two datasets. The results of in silico screening using protein-ligand docking are affected by the selection of 3D structure of the target protein. As the first strategy, we chose the 3D structures for in silico screening by test dockings using the G719S/T790M crystal structure, its molecular dynamics snapshots, and known inhibitors of the drug-resistant EGFR. In the second strategy, we selected the 3D structures by test dockings using all of the EGFR structures, regardless of the mutations, and all of the known EGFR inhibitors. Using each of the 3D structures selected by the strategies, 1000 compounds were chosen from the 71,588 compounds. Kinase assays identified 15 G719S/T790M EGFR inhibitors, including two compounds with novel scaffolds. Analyses of their structure-activity relationships revealed that interactions with the mutated Met790 residue specifically increase the inhibitory activity against G719S/T790M EGFR.     

Contrasting Effects of the Cytotoxic Anticancer Drug Gemcitabine and the EGFR Tyrosine Kinase Inhibitor Gefitinib on NK Cell-Mediated Cytotoxicity via Regulation of NKG2D Ligand in Non-Small-Cell Lung Cancer Cells

IntroductionSeveral cytotoxic anticancer drugs inhibit DNA replication and/or mitosis, while EGFR tyrosine kinase inhibitors inactivate EGFR signalling in cancer cell. Both types of anticancer drugs improve the overall survival of the patients with non-small-cell lung cancer (NSCLC), although tumors often become refractory to this treatment. Despite several mechanisms by which the tumors become resistant having been described the effect of these compounds on anti-tumor immunity remains largely unknown.MethodsThis study examines the effect of the cytotoxic drug Gemcitabine and the EGFR tyrosine kinase inhibitor Gefitinib on the expression of NK group 2 member D (NKG2D) ligands as well as the sensitivity of NSCLC cells to the NK-mediated lysis.ResultsWe demonstrate that Gemcitabine treatment leads to an enhanced expression, while Gefitinib downregulated the expression of molecules that act as key ligands for the activating receptor NKG2D and promote NK cell-mediated recognition and cytolysis. Gemcitabine activated ATM and ATM- and Rad-3-related protein kinase (ATR) pathways. The Gemcitabine-induced phosphorylation of ATM as well as the upregulation of the NKG2D ligand expression could be blocked by an ATM-ATR inhibitor. In contrast, Gefitinib attenuated NKG2D ligand expression. Silencing EGFR using siRNA or addition of the PI3K inhibitor resulted in downregulation of NKG2D ligands. The observations suggest that the EGFR/PI3K pathway also regulates the expression of NKG2D ligands. Additionally, we showed that both ATM-ATR and EGFR regulate MICA/B via miR20a.ConclusionIn keeping with the effect on NKG2D expression, Gemcitabine enhanced NK cell-mediated cytotoxicity while Gefitinib attenuated NK cell killing in NSCLC cells.     

Discovery of benzimidazole derivatives as novel multi-target EGFR, VEGFR-2 and PDGFR kinase inhibitors

Multi-target EGFR, VEGFR-2 and PDGFR inhibitors are highly useful anticancer agents with improved therapeutic efficacies. In this work, we used two virtual screening methods, support vector machines (SVM) and molecular docking, to identify a novel series of benzimidazole derivatives, 2-aryl benzimidazole compounds, as multi-target EGFR, VEGFR-2 and PDGFR inhibitors. 2-Aryl benzimidazole compounds were synthesized and their biological activities against a tumor cell line HepG-2 and specific kinases were evaluated. Among these compounds, compounds 5a and 5e exhibited high cytotoxicity against HepG-2 cells with IC?? values at ～2 μM. Further kinase assay study showed that compound 5a have good EGFR inhibitory activity and moderate VEGFR-2 and PDGFR inhibitory activities, while 5e have moderate EGFR inhibitory activity and slightly weaker VEGFR-2 and PDGFR inhibitory activities. Molecular docking analysis suggested that compound 5a more tightly interacts with EGFR and PDGFR than compound 5e. Our study discovered a novel series of benzimidazole derivatives as multi-target EGFR, VEGFR-2 and PDGFR kinases inhibitors.     

Designing of benzothiazole derivatives as promising EGFR tyrosine kinase inhibitors: a pharmacoinformatics study

Abstract

Benzothiazole derivatives represent an important class of therapeutic chemical agents and are widely used for interesting biological activities and therapeutic functions including anticancer, antitumor and antimicrobial. In this study, we have performed similarity/substructure-based search of eMolecule database to find out promising benzothiazole derivatives as EGFR tyrosine kinase inhibitors. Several screening criteria that included molecular docking, pharmacokinetics and synthetic accessibility were used on initially derived about 7000 molecules consisting of benzothiazole as major component. Finally, four molecules were found to be promising EGFR tyrosine kinase inhibitors. The best docked pose of each molecule was considered for binding interactions followed by molecular dynamics (MD) and binding energy calculation. Molecular docking clearly showed the final proposed derivatives potential to form a number of binding interactions. MD simulation trajectories undoubtedly indicated that the EGFR protein becomes stable when proposed derivatives bind to the receptor cavity. Strong binding affinity was found for all molecules toward the EGFR which was substantiated by the binding energy calculation using the MM-PBSA approach. Therefore, proposed benzothiazole derivatives may be promising EGFR tyrosine kinase inhibitors for potential application as cancer therapy.

Communicated by Ramaswamy H. Sarma     

In silico studies on potential MCF-7 inhibitors: a combination of pharmacophore and 3D-QSAR modeling,virtual screening,molecular docking,and pharmacokinetic analysis

Gallic acid and its derivatives exhibit a diverse range of biological applications, including anti-cancer activity. In this work, a data-set of forty-six molecules containing the galloyl moiety, and known to show anticarcinogenic activity against the MCF-7 human cancer cell line, have been chosen for pharmacophore modeling and 3D-Quantitative Structure Activity Relationship (3D-QSAR) studies. A tree-based partitioning algorithm has been used to find common pharmacophore hypotheses. The QSAR model was generated for three, four, and five featured hypotheses with increasing PLS factors and analyzed. Results for five featured hypotheses with three acceptors and two aromatic rings were the best out of all the possible combinations. On analyzing the results, the most robust (R^2?=?.8990) hypothesis with a good predictive power (Q^2?=?.7049) was found to be AAARR.35. A good external validation (R² = .6109) was also obtained. In order to design new MCF-7 inhibitors, the QSAR model was further utilized in pharmacophore-based virtual screening of a large database. The predicted IC₅₀ values of the identified potential MCF-7 inhibitors were found to lie in the micromolar range. Molecular docking into the colchicine domain of tubulin was performed in order to examine one of the probable mechanisms. This revealed various interactions between the ligand and the active site protein residues. The present study is expected to provide an effective guide for methodical development of potent MCF-7 inhibitors.     

Interaction of an anticancer benzopyrane derivative with DNA: Biophysical,biochemical, and molecular modeling studies

BackgroundSIMR1281 is a potent anticancer lead candidate with multi- target activity against several proteins; however, its mechanism of action at the molecular level is not fully understood. Revealing the mechanism and the origin of multitarget activity is important for the rational identification and optimization of multitarget drugs.MethodsWe have used a variety of biophysical (circular dichroism, isothermal titration calorimetry, viscosity, and UV DNA melting), biochemical (topoisomerase I & II assays) and computational (molecular docking and MD simulations) methods to study the interaction of SIMR1281 with duplex DNA structures.ResultsThe biophysical results revealed that SIMR1281 binds to dsDNA via an intercalation-binding mode with an average binding constant of 3.1 × 10⁶ M⁻¹. This binding mode was confirmed by the topoisomerases' inhibition assays and molecular modeling simulations, which showed the intercalation of the benzopyrane moiety between DNA base pairs, while the remaining moieties (thiazole and phenyl rings) sit in the minor groove and interact with the flanking base pairs adjacent to the intercalation site.ConclusionsThe DNA binding characteristics of SIMR1281, which can disrupt/inhibit DNA function as confirmed by the topoisomerases' inhibition assays, indicate that the observed multi-target activity might originate from ligand intervention at nucleic acids level rather than due to direct interactions with multiple biological targets at the protein level.General significanceThe findings of this study could be helpful to guide future optimization of benzopyrane-based ligands for therapeutic purposes.     

2-(Substituted phenyl)amino analogs of 1-methoxyspirobrassinol methyl ether: Synthesis and anticancer activity

New analogs of indole phytoalexin 1-methoxyspirobrassinol methyl ether have been designed by replacement of its 2-methoxy group with 2-(substituted phenyl)amino group. Synthesized by spirocyclization methodology, trans- and cis-diastereoisomers of target compounds were isolated and evaluated as potential anticancer and antimicrobial agents. Their molecular geometries were refined by ab initio minimizations. Pharmacophore modeling and QSAR studies were performed in order to correlate their molecular structure and biological activity.