Rational ligand-based virtual screening and structure-activity relationship studies in the ligand-binding domain of the glucocorticoid receptor-α

Structure-based virtual screening, molecular docking, molecular dynamics simulation and MM/PBSA calculations towards identification of steroidal and non-steroidal selective glucocorticoid receptor modulators

Glucocorticoids have been used in the treatment of many diseases including inflammatory and autoimmune diseases. Despite the wide therapeutic effects of synthetic glucocorticoids, the use of these compounds has been limited due to side effects such as osteoporosis, immunodeficiency, and hyperglycaemia. To this end, extensive studies have been performed to discover new glucocorticoid modulators with the aim of increasing affinity for the receptor and thus less side effects. In the present work, structure-based virtual screening was used for the identification of novel potent compounds with glucocorticoid effects. The molecules derived from ZINC database were screened on account of structural similarity with some glucocorticoid agonists as the template. Subsequently, molecular docking was performed on 200 selected compounds to obtain the best steroidal and non-steroidal conformations. Three compounds, namely ZINC_000002083318, ZINC_000253697499 and ZINC_000003845653, were selected with the binding energies of -11.5, -10.5, and -9.5 kcal/mol, respectively. Molecular dynamic simulations on superior structures were accomplished with the glucocorticoid receptor. Additionally, root mean square deviations, root mean square fluctuation, radius of gyration, hydrogen bonds, and binding-free energy analysis showed the binding stability of the proposed compounds compared to budesonide as an approved drug. The results demonstrated that all the compounds had suitable binding stability compared to budesonide, while ZINC_000002083318 showed a tighter binding energy compared to the other compounds.Communicated by Ramaswamy H. Sarma.

Discovery of novel non-steroidal selective glucocorticoid receptor modulators by structure- and IGN-based virtual screening, structural optimization, and biological evaluation

Glucocorticoids (GCs) are the most commonly used anti-inflammatory drugs. However, their excellent therapeutic effects are often accompanied by undesirable side effects. To discover selective glucocorticoid receptor modulators (SGRMs) that preferentially induce transrepression with little or no transactivation activity, a structure-based virtual screening by combining molecular docking and InteractionGraphNet (IGN) rescoring was performed, and compound HP210 was identified. HP210 did not induce the transactivation functions of GR while still acted on the NF-κB mediated tethered transrepression function (IC₅₀ = 2.32 μM), and suppressed the secretion of pro-inflammation cytokines IL-1β and IL-6. Compared with dexamethasone, HP210 showed no cross activities with phylogenetically related mineralcorticoid receptor and progesterone receptor and no significant effect on osteoprotegerin, exhibiting a reduced side-effect profile. Then, guided by the molecular dynamics simulations and binding free energy calculations, compound HP210_b4 with over two-fold higher transrepression activity (IC₅₀ = 0.99 μM) was discovered. This study reported a group of non-steroidal new-scaffold SGRMs, providing valuable clues for the development of novel anti-inflammatory drugs.

Predicting Potential Endocrine Disrupting Chemicals Binding to Estrogen Receptor α (ERα) Using a Pipeline Combining Structure-Based and Ligand-Based in Silico Methods

The estrogen receptors α (ERα) are transcription factors involved in several physiological processes belonging to the nuclear receptors (NRs) protein family. Besides the endogenous ligands, several other chemicals are able to bind to those receptors. Among them are endocrine disrupting chemicals (EDCs) that can trigger toxicological pathways. Many studies have focused on predicting EDCs based on their ability to bind NRs; mainly, estrogen receptors (ER), thyroid hormones receptors (TR), androgen receptors (AR), glucocorticoid receptors (GR), and peroxisome proliferator-activated receptors gamma (PPARγ). In this work, we suggest a pipeline designed for the prediction of ERα binding activity. The flagged compounds can be further explored using experimental techniques to assess their potential to be EDCs. The pipeline is a combination of structure based (docking and pharmacophore models) and ligand based (pharmacophore models) methods. The models have been constructed using the Environmental Protection Agency (EPA) data encompassing a large number of structurally diverse compounds. A validation step was then achieved using two external databases: the NR-DBIND (Nuclear Receptors DataBase Including Negative Data) and the EADB (Estrogenic Activity DataBase). Different combination protocols were explored. Results showed that the combination of models performed better than each model taken individually. The consensus protocol that reached values of 0.81 and 0.54 for sensitivity and specificity, respectively, was the best suited for our toxicological study. Insights and recommendations were drawn to alleviate the screening quality of other projects focusing on ERα binding predictions.

Investigation on glucocorticoid receptors within platelets from adult patients with immune thrombocytopenia

Objective: The expression of glucocorticoid receptors within platelets from newly diagnosed Immune Thrombocytopenia (ITP) patients in the adult was investigated.Methods: GR expression in platelets from newly diagnosed ITP patients and healthy controls was measured using flow cytometry. Subsequently, platelets RNA and proteins were isolated and used for confirming the flow cytometry results by using RT-qPCR and ELISA.Results: Flow cytometry showed that the percentages of platelets expressing GRα and GRβ from ITP patients were significantly higher than those from healthy controls (P < 0.05). qPCR and ELISA confirmed that GRα and GRβ were increased at both RNA transcription and protein expression levels within platelets from ITP patients compared with healthy controls.Conclusion: We speculated that the up-regulation of glucocorticoid receptor within platelets may be an important biological feature of platelets in patients with ITP, and may also play an important role in the treatment of ITP, which is worthy of further study.

Significance estimation for sequence-based chemical similarity searching (PhAST) and application to AuroraA kinase inhibitors

BACKGROUND

Chemical similarity searching allows the retrieval of preferred screening molecules from a compound database. Candidates are ranked according to their similarity to a reference compound (query). Assessing the statistical significance of chemical similarity scores helps prioritizing significant hits, and identifying cases where the database does not contain any promising compounds.

METHOD

Our text-based similarity measure, Pharmacophore Alignment Search Tool (PhAST), employs pair-wise sequence alignment. We adapted the concept of E-values as significance estimates and employed a sampling technique that incorporates the principle of importance sampling in a Markov chain Monte Carlo simulation to generate distributions of random alignment scores. These distributions were used to compute significance estimates for similarity scores in a preliminary prospective virtual screen for inhibitors of Aurora A kinase.

CONCLUSION

Assessing the significance of compound similarity computed with PhAST allows for a statistically motivated identification of candidate screening compounds. Inhibitors of Aurora A kinase were retrieved from a large compound library.

Virtual screening for the identification of novel nonsteroidal glucocorticoid modulators

In this work, we describe the first application of ligand-based drug design (LBDD) to the derivation of a predictive pharmacophore for the human glucocorticoid receptor (hGR). Creation of a four feature pharmacophore in Catalyst was subsequently validated through a virtual screen of 264000 commercially available compounds. From a selected hit list of 11 diverse compounds, two nonsteroidal molecules demonstrated low micromolar activity against hGR as validated through fluorescence polarization competitive assay. Additionally, these compounds were tested for their trans-repression potential by their ability to inhibit IL-1 induced, IL-6 expression in the human A549 lung epithelial cell line. Co-treatment of A549 with 21 (MDG169) (10 microM) in combination with dexamethasone showed an improved inhibitory effect when compared to dexamethasone alone with the cooperative effect being dependent on the dexamethasone dose. Putative binding orientations in the hGR ligand binding domain crystal structure are presented. These compounds represent novel nonsteroidal hGR modulating scaffolds, rationally identified through ligand-focused computational modeling.