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

Quantitative structure-activity relationship and ADME prediction studies on series of spirooxindoles derivatives for anti-cancer activity against colon cancer cell line HCT-116

Forty-one derivatives of spirooxindoles, active against HCT-116 colon cancer cells, underwent pharmacophore-based 3D-QSAR analysis to understand their correlation with anti-cancer activity. The study identified a seven-point pharmacophore model (ADHHRRR1) and QSAR models, offering insights for lead optimization and novel analogue design, thus advancing anti-cancer drug discovery. This research underscores the value of molecular modeling in elucidating structure-activity relationships and enhancing drug development efforts.

Toward structure-based drug design against the epidermal growth factor receptor (EGFR)

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Structural variations in EGFR should not be ignored in structure-based drug design.

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Main variations involve inward and outward folding of C-helix in the kinase N-lobe.

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Origins of variations are mutations and drug R-groups but not the drug core.

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Comparative modeling, fitting and clustering are imperative steps in EGFR drug design.

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Alternatively, volume and shape of binding site can be used to filter ligands against structures.

Most of the available crystal structures of epidermal growth factor receptor (EGFR) kinase domain, bound to drug inhibitors, originated from ligand-based drug design studies. Here, we used variations in 110 crystal structures to assemble eight distinct families highlighting the C-helix orientation in the N-lobe of the EGFR kinase domain. The families shared similar mutational profiles and similarity in the ligand R-groups (chemical composition, geometry, and charge) facing the C-helix, mutation sites, and DFG domain. For structure-based drug design, we recommend a systematic decision-making process for choice of template, guided by appropriate pairwise fitting and clustering before the molecular docking step. Alternatively, the binding site shape/volume can be used to filter and select the compound libraries.

Drug design by machine-trained elastic networks: predicting Ser/Thr-protein kinase inhibitors' activities

An elastic network model (ENM) represents a molecule as a matrix of pairwise atomic interactions. Rich in coded information, ENMs are hereby proposed as a novel tool for the prediction of the activity of series of molecules, with widely different chemical structures, but a common biological activity. The new approach is developed and tested using a set of 183 inhibitors of serine/threonine-protein kinase enzyme (Plk3) which is an enzyme implicated in the regulation of cell cycle and tumorigenesis. The elastic network (EN) predictive model is found to exhibit high accuracy and speed compared to descriptor-based machine-trained modeling. EN modeling appears to be a highly promising new tool for the high demands of industrial applications such as drug and material design.

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.

Epidermal growth factor receptor: Structure-function informing the design of anticancer therapeutics

Research on the epidermal growth factor (EGF) family and the family of receptors (EGFR) has progressed rapidly in recent times. New crystal structures of the ectodomains with different ligands, the activation of the kinase domain through oligomerisation and the use of fluorescence techniques have revealed profound conformational changes on ligand binding. The control of cell signaling from the EGFR-family is complex, with heterodimerisation, ligand affinity and signaling cross-talk influencing cellular outcomes. Analysis of tissue homeostasis indicates that the control of pro-ligand processing is likely to be as important as receptor activation events. Several members of the EGFR-family are overexpressed and/or mutated in cancer cells. The perturbation of EGFR-family signaling drives the malignant phenotype of many cancers and both inhibitors and antagonists of signaling from these receptors have already produced therapeutic benefits for patients. The design of affibodies, antibodies, small molecule inhibitors and even immunotherapeutic drugs targeting the EGFR-family has yielded promising new approaches to improving outcomes for cancer patients. In this review, we describe recent discoveries which have increased our understanding of the structure and dynamics of signaling from the EGFR-family, the roles of ligand processing and receptor cross-talk. We discuss the relevance of these studies to the development of strategies for designing more effective targeted treatments for cancer patients.

Screening of multi-targeted natural compounds for receptor tyrosine kinases inhibitors and biological evaluation on cancer cell lines, in silico and in vitro

Receptors for growth factors encompass within the superfamily of receptor tyrosine kinases and are known to regulate numerous biological processes including cellular growth, proliferation, metabolism, survival, cell differentiation and apoptosis. These receptors have recently caught the attention of the researchers as an attractive target to combat cancer owing to the evidence suggesting their over-expression in cancer cells. Therefore, we studied receptor-based molecular docking of IR (PDB; 3ETA), IGF1R (PDB; 1K3A), EGFR (PDB; 1M17), VEGFIR (PDB; 3HNG), and VEGFIIR (PDB; 2OH4) against natural compounds. Further, in vitro investigation of the biological effect of lead molecules in an array of cancer cell lines was done. All selected natural compounds were docked with the X-ray crystal structure of selected protein by employing GLIDE (Grid-based Ligand Docking with Energetics) Maestro 9.6. InterBioScreen natural compounds docked with each selected protein molecules by using GLIDE high throughput virtual screening. On the basis of Gscore, we select 20 compounds along with 68 anticancer compounds for GLIDE extra precision molecular docking. It was discovered in this study that compound epigallocatechin gallate (EGCG) yielded magnificent Gscore with IGF1R (PDB; 1K3A) and VEGFIIR (PDB; 2OH4), and protein-ligand interactions are chart out. Effect of EGCG on biological activity such as mRNA expression of selected protein, cell proliferation, oxidative stress, and cell migration was reported after the 48 h treatments in cancer cell lines. The RT-PCR densitometric bands analysis showed that compound EGCG reduced the mRNA expression of IGF1R, VEGFIIR, and mTOR at 80 μM concentration. Moreover, EGCG significantly reduced cell proliferation and ROS generation after 48 h treatments. Our result also indicated a reduction in the potential for cell migration that might show in vivo anti-metastasis activity of EGCG.

Qualitative and quantitative structure-activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals

In this study, structure-activity relationship (SAR) models have been established for qualitative and quantitative prediction of the blood-brain barrier (BBB) permeability of chemicals. The structural diversity of the chemicals and nonlinear structure in the data were tested. The predictive and generalization ability of the developed SAR models were tested through internal and external validation procedures. In complete data, the QSAR models rendered ternary classification accuracy of >98.15%, while the quantitative SAR models yielded correlation (r(2)) of >0.926 between the measured and the predicted BBB permeability values with the mean squared error (MSE) <0.045. The proposed models were also applied to an external new in vitro data and yielded classification accuracy of >82.7% and r(2) > 0.905 (MSE < 0.019). The sensitivity analysis revealed that topological polar surface area (TPSA) has the highest effect in qualitative and quantitative models for predicting the BBB permeability of chemicals. Moreover, these models showed predictive performance superior to those reported earlier in the literature. This demonstrates the appropriateness of the developed SAR models to reliably predict the BBB permeability of new chemicals, which can be used for initial screening of the molecules in the drug development process.