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Macromolecular Modelling and Docking Simulations for the Discovery of Selective GPER Ligands.

ABSTRACT: Estrogens influence multiple physiological processes and are implicated in many diseases as well. Cellular responses to estrogens are mainly mediated by the estrogen receptors (ER)? and ER?, which act as ligand-activated transcription factors. Recently, a member of the G protein-coupled receptor (GPCR) superfamily, namely GPER/GPR30, has been identified as a further mediator of estrogen signalling in different pathophysiological conditions, including cancer. Today, computational methods are commonly used in all areas of health science research. Among these methods, virtual ligand screening has become an established technique for hit discovery and optimization. The absence of an established three-dimensional structure of GPER promoted studies of structure-based drug design in order to build reliable molecular models of this receptor. Here, we discuss the results obtained through the structure-based virtual ligand screening for GPER, which allowed the identification and synthesis of different selective agonist and antagonist moieties. These compounds led significant advances in our understanding of the GPER function at the cellular, tissue, and organismal levels. In particular, selective GPER ligands were critical toward the evaluation of the role elicited by this receptor in several pathophysiological conditions, including cancer. Considering that structure-based approaches are fundamental in drug discovery, future research breakthroughs with the aid of computer-aided molecular design and chemo-bioinformatics could generate a new class of drugs that, acting through GPER, would be useful in a variety of diseases as well as in innovative anticancer strategies.

SUBMITTER: Rosano C

PROVIDER: S-EPMC4706286 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Macromolecular Modelling and Docking Simulations for the Discovery of Selective GPER Ligands.

Rosano Camillo C Ponassi Marco M Santolla Maria Francesca MF Pisano Assunta A Felli Lamberto L Vivacqua Adele A Maggiolini Marcello M Lappano Rosamaria R

The AAPS journal 20151116 1

Estrogens influence multiple physiological processes and are implicated in many diseases as well. Cellular responses to estrogens are mainly mediated by the estrogen receptors (ER)α and ERβ, which act as ligand-activated transcription factors. Recently, a member of the G protein-coupled receptor (GPCR) superfamily, namely GPER/GPR30, has been identified as a further mediator of estrogen signalling in different pathophysiological conditions, including cancer. Today, computational methods are comm ...[more]

PMID: 26573009

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Project description:Our understanding of estrogen (17?-estradiol, E2) receptor biology has evolved in recent years with the discovery and characterization of a 7-transmembrane-spanning G protein-coupled estrogen receptor (GPER/GPR30) and the development of GPER-selective functional chemical probes. GPER is highly expressed in certain breast, endometrial, and ovarian cancers, establishing the importance of noninvasive methods to evaluate GPER expression in vivo. Here, we developed (99m)Tc-labeled GPER ligands to demonstrate the in vivo status of GPER as an estrogen receptor (ER) and for GPER visualization in whole animals. A series of (99m)Tc(I)-labeled nonsteroidal tetrahydro-3H-cyclopenta[c]quinolone derivatives was synthesized utilizing pyridin-2-yl hydrazine and picolylamine chelates. Radioligand receptor binding studies revealed binding affinities in the 10 to 30 nmol/L range. Cell signaling assays previously demonstrated that derivatives retaining a ketone functionality displayed agonist properties, whereas those lacking such a hydrogen bond acceptor were antagonists. In vivo biodistribution and imaging studies performed on mice bearing human endometrial and breast cancer cell xenografts yielded significant tumor uptake (0.4-1.1%ID/g). Blocking studies revealed specific uptake in multiple organs (adrenals, uterus, and mammary tissue), as well as tumor uptake with similar levels of competition by E2 and G-1, a GPER-selective agonist. In conclusion, we synthesized and evaluated a series of first-generation (99m)Tc-labeled GPER-specific radioligands, demonstrating GPER as an estrogen-binding receptor for the first time in vivo using competitive binding principles, and establishing the utility of such ligands as tumor imaging agents. These results warrant further investigation into the role of GPER in estrogen-mediated carcinogenesis and as a target for diagnostic/therapeutic/image-guided drug delivery.These studies provide a molecular basis to evaluate GPER expression and function as an ER through in vivo imaging.

Project description:The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20,000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

Dataset Information

Macromolecular Modelling and Docking Simulations for the Discovery of Selective GPER Ligands.

Publications

Macromolecular Modelling and Docking Simulations for the Discovery of Selective GPER Ligands.

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