title: 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)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 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.
authors.affiliation: UOS Proteomics IRCCS AOU San Martino- IST National Institute for Cancer Research, Largo R. Benzi 10, 16132, Genoa, Italy. camillo.rosano@gmail.com.
authors.forename: Camillo
authors.initials: C
authors.lastname: Rosano
authors.affiliation: UOS Proteomics IRCCS AOU San Martino- IST National Institute for Cancer Research, Largo R. Benzi 10, 16132, Genoa, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Ponassi
authors.affiliation: Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, via Bucci, 87036, Rende, Cosenza, Italy.
authors.forename: Maria Francesca
authors.initials: MF
authors.lastname: Santolla
authors.affiliation: Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, via Bucci, 87036, Rende, Cosenza, Italy.
authors.forename: Assunta
authors.initials: A
authors.lastname: Pisano
authors.affiliation: Department of Orthopedical Surgery, University of Genoa, Largo R. Benzi 10, 16132, Genoa, Italy.
authors.forename: Lamberto
authors.initials: L
authors.lastname: Felli
authors.affiliation: Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, via Bucci, 87036, Rende, Cosenza, Italy.
authors.forename: Adele
authors.initials: A
authors.lastname: Vivacqua
authors.affiliation: Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, via Bucci, 87036, Rende, Cosenza, Italy. marcellomaggiolini@yahoo.it.
authors.forename: Marcello
authors.initials: M
authors.lastname: Maggiolini
authors.affiliation: Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, via Bucci, 87036, Rende, Cosenza, Italy.
authors.forename: Rosamaria
authors.initials: R
authors.lastname: Lappano
mesh_terms: D000818:Animals; D019295:Computational Biology; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D046911:Macromolecular Substances / Q000737:chemistry*; D062105:Molecular Docking Simulation / Q000379:methods*; D043562:Receptors, G-Protein-Coupled / Q000187:drug effects* / Q000378:metabolism*; D013329:Structure-Activity Relationship
chemical_list: D046911:Macromolecular Substances; D043562:Receptors, G-Protein-Coupled
keywords: GPCRs; GPER; drug design; molecular modelling; structural bioinformatics