Discovery of novel EGFR tyrosine kinase inhibitors by structure-based virtual screening

Discovery of Novel Epidermal Growth Factor Receptor (EGFR) Inhibitors Using Computational Approaches

The epidermal growth factor receptor (EGFR) signaling pathway plays an important role in cell growth, proliferation, differentiation, and other physiological processes, which makes the EGFR a promising target for anticancer therapies. The discovery of novel EGFR inhibitors may provide a solution to the problem of drug resistance. In this work, we performed a ligand-based virtual screening (LBVS) protocol for finding novel EGFR inhibitors from a 5.3 million compound library. First, the 3D shape-based similarity was used to obtain structurally novel EGFR inhibitors. In this study, we tried three queries; two were crystal structures and one was generated from deep generative models of graphs (DGMG). Next, we have built four structure-activity relationship (SAR) models and three quantitative structure-activity relationship (QSAR) models based on an SVM method for further screening of highly active EGFR inhibitors. Experimental validations led to the identification of nine hits out of 18 tested compounds. Among them, hit 1, hit 5, and hit 6 had IC₅₀ values around 80 nM against EGFR whose interactions with EGFR were further investigated by molecular dynamics simulations.

Ligand-Based Pharmacophore Modeling, Molecular Docking, and Molecular Dynamic Studies of Dual Tyrosine Kinase Inhibitor of EGFR and VEGFR2

Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor 2 (VEGFR2) play an important role in cancer growth. Both of them have close relationships. Expression of EGFR will induce an angiogenic factor (VEGF) release for binding with VEGFR2. However, the existence of VEGF up-regulation independent of EGFR leads to cancer cell resistance to anti-EGFR. Therefore, a therapeutic approach targeting EGFR and VEGFR2 simultaneously may improve the outcome of cancer treatment. The present study was designed to identify potential compounds as a dual inhibitor of EGFR and VEGFR2 by the computational method. Firstly, the ligand-based pharmacophore model for each target was setup to screen of ZINC database of purchasable compounds. The hit compounds obtained by pharmacophore screening were then further screened by molecular docking studies. Taking erlotinib (EGFR inhibitor) and axitinib (VEGFR2 inhibitor) as reference drugs, six potential compounds (ZINC08398597, ZINC12047553, ZINC16525481, ZINC17418102, ZINC21942954, and ZINC38484632) were selected based on their docking scores and binding interaction. However, molecular dynamics simulations demonstrated that only ZINC16525481 and ZINC38484632 which have good binding free energy and stable hydrogen bonding interactions with EGFR and VEGFR2. The result represents a promising starting point for developing potent dual tyrosine kinases inhibitor of EGFR and VEGFR2.

Molecular dynamics, MM/PBSA and in vitro validation of a novel quinazoline-based EGFR tyrosine kinase inhibitor identified using structure-based in silico screening

EGFR-TK has been a target strongly associated with the development of NSCLCs. A structure-based virtual screening campaign was launched against EGFR-TK by virtual screening a 3D library of 167 commercially available small molecules downloaded from ChemBridge Corporation. The virtual screen identified 12 virtual hit molecules, which were biologically evaluated against an EGFR-TK inhibitor-sensitive NSCLC cell line, A549. A quinazoline-based molecule 1, was most active and displayed ∼58% cytotoxicity at 20 μM single dose. The mode of cell death suggests molecule 1 induced apoptosis, which is characteristic of EGFR-TK pathway inhibition. A 50 ns MD simulation was conducted on three different systems: free EGFR-TK, molecule 1 complexed to EGFR-TK, and the positive control, lapatinib, complexed to EGFR-TK. The MD simulations showed increase in stabilisation of the EGFR-TK structure for the complexed systems, i.e., lower RMSDs and RMSFs for complexed EGFR-TK structures compared to the free EGFR-TK system. The binding affinities were estimated using MM/PBSA in the last 10 ns of the MD simulation that revealed comparable binding free energies between molecule 1 and lapatinib, ΔG_bind = -25.0 and -23.9 kcal/mol, respectively. Per residue binding free energy decomposition studies revealed non-polar interactions contributed mostly to the binding free energies. Residues Leu718, Arg841 and Phe856 were predicted to contribute most to the binding free energies for molecule 1.

Inhibiting two cellular mutant epidermal growth factor receptor tyrosine kinases by addressing computationally assessed crystal ligand pockets

Aim: Blocking receptor tyrosine kinases is a useful strategy for inhibiting the overexpression of EGFR. However, the quality of crystal pocket is an essential issue for virtually identifying new leads for surviving resistance cancer cells. Results: With the examinating crystal pocket quality by the self-docking root-mean-square deviation (RMSD) calculation, we used the two best kinase pockets of mutant EGFR kinases, T790M/L858R and G719S, for virtual screening. After sorting all the docking poses of the 57,177 library compounds by consensus scores, three evidently blocked cellular EGFR phosphorylation in the H1975 and SW48 cell lines. Conclusion: The computationally assessed qualities of crystal pockets of crystal EGFR kinases can help identify new cellular active and target-specific ligands rapidly and at low cost.

Inhibition of COX-2 and EGFR by Melafolone Improves Anti-PD-1 Therapy through Vascular Normalization and PD-L1 Downregulation in Lung Cancer

Checkpoint blockade therapy has been proven efficacious in lung cancer patients. However, primary/acquired resistance hampers its efficacy. Therefore, there is an urgent need to develop novel strategies to improve checkpoint blockade therapy. Here we tested whether dual inhibition of cyclooxygenase-2 (COX-2) and epidermal growth factor receptor (EGFR) by flavonoid melafolone improves program death 1 (PD-1) checkpoint blockade therapy through normalizing tumor vasculature and PD-1 ligand (PD-L1) downregulation. Virtual screening assay, cellular thermal shift assay, and enzyme inhibition assay identified melafolone as a potential inhibitor of COX-2 and EGFR. In Lewis lung carcinoma (LLC) and CMT167 models, dual inhibition of COX-2 and EGFR by melafolone promoted survival, tumor growth inhibition, and vascular normalization, and ameliorated CD8⁺ T-cell suppression, accompanied by the downregulation of transforming growth factor-β (TGF-β), vascular endothelial growth factor (VEGF), and PD-L1 in the tumor cells. Mechanistically, dual inhibition of COX-2 and EGFR in lung cancer cells by melafolone increased the migration of pericyte, decreased the proliferation and migration of endothelial cells, and enhanced the proliferation and effector function of CD8⁺ T cells through VEGF, TGF-β, or PD-L1 downregulation and PI3K/AKT inactivation. Notably, melafolone improved PD-1 immunotherapy against LLC and CMT167 tumors. Together, dual inhibition of COX-2 and EGFR by melafolone improves checkpoint blockade therapy through vascular normalization and PD-L1 downregulation and, by affecting vessels and immune cells, may be a promising combination strategy for the treatment of human lung cancer.

Synthesis and pharmacological evaluation of novel epidermal growth factor receptor inhibitors against prostate tumor cells

The aim of the present study was to investigate the activities of novel synthetic epidermal growth factor receptor (EGFR) inhibitors (ZINC05463076, ZINC2102846 and ZINC19901103) against prostate tumors, in vitro models and investigate the potential underlying mechanisms. A panel of prostate tumor cell lines (LNCaP, DU-145, PC-3 and LNCaP-AI cells) were used to evaluate antitumor activity of ZINC05463076, ZINC2102846, and ZINC19901103 in vitro. Cell growth and clonal formation were determined by MTT assay and Soft agar colony formation assay, respectively. An EGFR kinase assay following treatment of the compounds was performed by ELISA. Cell cycle-regulating proteins, including cyclin-dependent kinase (CDK)1, CKD2, CKD4 and inhibitory effects of these compounds on downstream signaling were analyzed by western blotting. Flow cytometry was performed to investigate apoptosis and cell cycle phases of the treated cells. It was revealed that all compounds synthesized in the present study demonstrated significant EGFR inhibition abilities, compared with approved EGFR inhibitor drug gefitinib. Treatment of LNCaP, DU-145, PC3 and LNCaP-AI cells with these compounds revealed cell proliferation inhibition and colony formation suppression dose-dependently in vitro. The agents impaired phosphorylation of EGFR and extracellular signal-regulated kinase 1/2 and suppressed their downstream signaling. In addition, these novel synthetic agents decreased the expression level of survivin, which may induce G₁ cell cycle phase arrest and cell apoptosis in PCa cells subsequently. Collectively, ZINC05463076, ZINC2102846 and ZINC19901103 exhibited significant antitumor activity in human prostate tumors in vitro, by inhibiting EGFR and promoting apoptosis, which suggested a rationale for clinical development in prostate tumor therapy.

Docking Screens for Novel Ligands Conferring New Biology

It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.

Virtual screening strategies: recent advances in the identification and design of anti-cancer agents

Virtual screening (VS) is a well-established technique, which is now routinely employed in computer aided drug designing process. VS can be broadly classified into two categories, i.e., ligand-based and structure-based approach. In recent years, VS has emerged as a time saving and cost effective technique, capable of screening millions of compounds in a user friendly manner. In the area of cancer drug design, VS methods have been widely used and helped in identifying novel molecules as potential anti-cancer agents. Both ligand-based VS (LBVS) structure-based VS (SBVS) methods have been highly useful in the identification of a number of potential anti-cancer agents exhibiting activities in nanomolar range. In tune with the rapid progress in the enhancement of computational power, VS has witnessed significant change in terms of speed and hit rate and in future it is expected that VS will be a preferential alternative to high throughput screening (HTS). This review, discusses recent trends and contribution of VS in the area of anti-cancer drug discovery.

Identification of novel kinase inhibitors by targeting a kinase-related apoptotic protein-protein interaction network in HeLa cells

OBJECTIVES

Protein kinases orchestrate activation of signalling cascades in response to extra- and intracellular stimuli for regulation of cell proliferation. They are directly involved in a variety of diseases, particularly cancers. Systems biology approaches have become increasingly important in understanding regulatory frameworks in cancer, and thus may facilitate future anti-cancer discoveries. Moreover, it has been suggested and confirmed that high-throughput virtual screening provides a novel, effective way to reveal small molecule protein kinase inhibitors. Accordingly, we aimed to identify kinase targets and novel kinase inhibitors.

MATERIALS AND METHODS

A series of bioinformatics methods, such as network construction, molecular docking and microarray analyses were performed.

RESULTS

In this study, we computationally constructed the appropriate global human protein-protein interaction network with data from online databases, and then modified it into a kinase-related apoptotic protein-protein interaction network. Subsequently, we identified several kinases as potential drug targets according to their differential expression observed by microarray analyses. Then, we predicted relevant microRNAs, which could target the above-mentioned kinases. Ultimately, we virtually screened a number of small molecule natural products from Traditional Chinese Medicine (TCM)@Taiwan database and identified a number of compounds that are able to target polo-like kinase 1, cyclin-dependent kinase 1 and cyclin-dependent kinase 2 in HeLa cervical carcinoma cells.

CONCLUSIONS

Taken together, all these findings might hopefully facilitate discovery of new kinase inhibitors that could be promising candidates for anti-cancer drug development.

A novel inhibitor of Mammalian triosephosphate isomerase found by an in silico approach

Triosephosphate isomerase (TIM) is an essential, highly conserved component of glycolysis. Tumors are often dependent on glycolysis for energy and metabolite production (the Warburg effect). Glycolysis inhibitors thus show promise as cancer treatments. TIM inhibition, unlike inhibition of other glycolysis enzymes, also produces toxic methylglyoxal targeted to regions of high glycolysis, an effect that might also be therapeutically useful. Thus TIM is an attractive drug target. A total of 338,562 lead-like molecules were analyzed computationally to find TIM inhibitors by an efficient “double screen” approach. The first fragment-sized compounds were studied using structure-based virtual screening to identify binding motifs for mammalian TIM. Subsequently, larger compounds, filtered to meet the binding criteria developed in the first analysis, were ranked using a second round of structure-based virtual screening. A compound was found that inhibited mammalian TIM in vitro in the micromolar range. Docking and molecular dynamics (MD) suggested that the inhibitor made hydrogen bond contacts with TIM catalytic residues. In addition, hydrophobic contacts were made throughout the binding site. All predicted inhibitor-TIM interactions involved TIM residues that were highly conserved. The discovered compound may provide a scaffold for elaboration of other inhibitors.

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

AIM

To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors.

METHODS

One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures.

RESULTS

Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands.

CONCLUSION

The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.

Identification and characterization of bi-thiazole-2,2'-diamines as kinase inhibitory scaffolds

Based on bioinformatics interrogation of the genome, >500 mammalian protein kinases can be clustered within seven different groups. Of these kinases, the mitogen-activated protein kinase (MAPK) family forms part of the CMGC group of serine/threonine kinases that includes extracellular signal regulated kinases (ERKs), cJun N-terminal kinases (JNKs), and p38 MAPKs. With the JNKs considered attractive targets in the treatment of pathologies including diabetes and stroke, efforts have been directed to the discovery of new JNK inhibitory molecules that can be further developed as new therapeutics. Capitalizing on our biochemical understanding of JNK, we performed in silico screens of commercially available chemical databases to identify JNK1-interacting compounds and tested their in vitro JNK inhibitory activity. With in vitro and cell culture studies, we showed that the compound, 4'-methyl-N(2)-3-pyridinyl-4,5'-bi-1,3-thiazole-2,2'-diamine (JNK Docking (JD) compound 123, but not the related compound (4'-methyl-N~2~-(6-methyl-2-pyridinyl)-4,5'-bi-1,3-thiazole-2,2'-diamine (JD124), inhibited JNK1 activity towards a range of substrates. Molecular docking, saturation transfer difference NMR experiments and enzyme kinetic analyses revealed both ATP- and substrate-competitive inhibition of JNK by JD123. In characterizing JD123 further, we noted its ATP-competitive inhibition of the related p38-γ MAPK, but not ERK1, ERK2, or p38-α, p38-β or p38-δ. Further screening of a broad panel of kinases using 10μM JD123, identified inhibition of kinases including protein kinase Bβ (PKBβ/Aktβ). Appropriately modified thiazole diamines, as typified by JD123, thus provide a new chemical scaffold for development of inhibitors for the JNK and p38-γ MAPKs as well as other kinases that are also potential therapeutic targets such as PKBβ/Aktβ.