Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.7
4.6
Journals
Molecules
Special Issues
GPCR Mechanism and Drug Design
molecules-logo
Submit to Molecules Review for Molecules Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

GPCR Mechanism and Drug Design

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: closed (31 May 2019) | Viewed by 26552

Special Issue Editor

Dr. Irina Moreira

E-Mail Website
Guest Editor
1. Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, 3000-456 Coimbra, Portugal
2. Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-535 Coimbra, Portugal
Interests: data science; drug discovery; deep learning; computational chemistry; structural biology; protein–protein complexes; modeling; GPCRs; functional selectivity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Given the central role of G-Protein-Coupled receptors (GPCRs) in an enormous variety of cellular mechanisms in normal physiology and disease, it is not surprising that they are the subject of major mechanistic efforts toward understanding their function and signaling selectivity. New insights have been provided by the recent structures of GPCRs in selected “states” stabilized by a variety of ligands with pharmacologically distinct properties (agonists, inverse agonists, etc.), by nanobodies mimicking signal transducers, by full heterotrimeric G-proteins (GTP-binding protein) and by Arrestin proteins. However, the molecular mechanisms connecting the GPCR structures to these states, and these states to elements of functional mechanisms, are not yet resolved, nor are they likely to be resolved solely from inspection of static crystal structures. This Special Issue aims at addressing this important knowledge gap and collect new reports and insights from computational and experimental researchers on specific problems of great significance in GPCR signaling. The fundamental concept of “functional selectivity” or “ligand bias”, e.g., the molecular mechanisms for selectivity for different pathways and the design of new drugs targeting these pathways, is of enormous interest in molecular pharmacology, cell physiology, and drug development. Contributions to this issue, both in the form of original research or review articles, may cover all aspects of GPCR mechanism and drug design and multidisciplinary studies are particularly welcome.

Dr. Irina S. Moreira
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • G-Protein-Coupled receptors (GPCRs)
  • Molecular Mechanism
  • Functional Selectivity/Ligand Bias
  • Drug Design and Discovery
  • G-protein Coupling
  • Arrestin Coupling
  • In silico approaches in the study of GPCRs
  • Biochemical and Biophysical approaches in the study of GPCRs
  • Big Data in GPCR function/structure

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

21 pages, 11015 KiB  
Article
A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs
by Ambrose Plante, Derek M. Shore, Giulia Morra, George Khelashvili and Harel Weinstein
Molecules 2019, 24(11), 2097; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24112097 - 02 Jun 2019
Cited by 35 | Viewed by 8676
Abstract
G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the [...] Read more.
G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT2A and D2 subtypes of class-A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity. Full article
(This article belongs to the Special Issue GPCR Mechanism and Drug Design)
►▼ Show Figures

Figure 1

26 pages, 4636 KiB  
Article
A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods
by Beatriz Bueschbell, Carlos A. V. Barreto, António J. Preto, Anke C. Schiedel and Irina S. Moreira
Molecules 2019, 24(7), 1196; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24071196 - 27 Mar 2019
Cited by 24 | Viewed by 6064
Abstract
Background: Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific [...] Read more.
Background: Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a molecular basis has not been fully elucidated. Methods: Homology modeling and molecular dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D1-like and D2-like). Fifteen structurally diverse ligands were docked. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for selective binding to DR subtypes. Results: Residues of the aromatic microdomain were shown to be responsible for the majority of ligand interactions established to all DRs. Hydrophobic contacts involved a huge network of conserved and non-conserved residues between three transmembrane domains (TMs), TM2-TM3-TM7. Hydrogen bonds were mostly mediated by the serine microdomain. TM1 and TM2 residues were main contributors for the coupling of large ligands. Some amino acid groups form electrostatic interactions of particular importance for D1R-like selective ligands binding. Conclusions: This in silico approach was successful in showing known receptor-ligand interactions as well as in determining unique combinations of interactions, which will support mutagenesis studies to improve the design of subtype-specific ligands. Full article
(This article belongs to the Special Issue GPCR Mechanism and Drug Design)
►▼ Show Figures

Figure 1

Review

Jump to: Research

21 pages, 1702 KiB  
Review
Utilization of Biased G Protein-Coupled Receptor Signaling towards Development of Safer and Personalized Therapeutics
by Metehan Ilter, Samman Mansoor and Ozge Sensoy
Molecules 2019, 24(11), 2052; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24112052 - 29 May 2019
Cited by 15 | Viewed by 5369
Abstract
G protein-coupled receptors (GPCRs) are involved in a wide variety of physiological processes. Therefore, approximately 40% of currently prescribed drugs have targeted this receptor family. Discovery of β -arrestin mediated signaling and also separability of G protein and β -arrestin signaling pathways have [...] Read more.
G protein-coupled receptors (GPCRs) are involved in a wide variety of physiological processes. Therefore, approximately 40% of currently prescribed drugs have targeted this receptor family. Discovery of β -arrestin mediated signaling and also separability of G protein and β -arrestin signaling pathways have switched the research focus in the GPCR field towards development of biased ligands, which provide engagement of the receptor with a certain effector, thus enriching a specific signaling pathway. In this review, we summarize possible factors that impact signaling profiles of GPCRs such as oligomerization, drug treatment, disease conditions, genetic background, etc. along with relevant molecules that can be used to modulate signaling properties of GPCRs such as allosteric or bitopic ligands, ions, aptamers and pepducins. Moreover, we also discuss the importance of inclusion of pharmacogenomics and molecular dynamics simulations to achieve a holistic understanding of the relation between genetic background and structure and function of GPCRs and GPCR-related proteins. Consequently, specific downstream signaling pathways can be enriched while those that bring unwanted side effects can be prevented on a patient-specific basis. This will improve studies that centered on development of safer and personalized therapeutics, thus alleviating the burden on economy and public health. Full article
(This article belongs to the Special Issue GPCR Mechanism and Drug Design)
►▼ Show Figures

Figure 1

29 pages, 1872 KiB  
Review
Less Exploited GPCRs in Precision Medicine: Targets for Molecular Imaging and Theranostics
by João Franco Machado, Rúben D. Silva, Rita Melo and João D. G. Correia
Molecules 2019, 24(1), 49; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24010049 - 23 Dec 2018
Cited by 12 | Viewed by 5016
Abstract
Precision medicine relies on individually tailored therapeutic intervention taking into account individual variability. It is strongly dependent on the availability of target-specific drugs and/or imaging agents that recognize molecular targets and patient-specific disease mechanisms. The most sensitive molecular imaging modalities, Single Photon Emission [...] Read more.
Precision medicine relies on individually tailored therapeutic intervention taking into account individual variability. It is strongly dependent on the availability of target-specific drugs and/or imaging agents that recognize molecular targets and patient-specific disease mechanisms. The most sensitive molecular imaging modalities, Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET), rely on the interaction between an imaging radioprobe and a target. Moreover, the use of target-specific molecular tools for both diagnostics and therapy, theranostic agents, represent an established methodology in nuclear medicine that is assuming an increasingly important role in precision medicine. The design of innovative imaging and/or theranostic agents is key for further accomplishments in the field. G-protein-coupled receptors (GPCRs), apart from being highly relevant drug targets, have also been largely exploited as molecular targets for non-invasive imaging and/or systemic radiotherapy of various diseases. Herein, we will discuss recent efforts towards the development of innovative imaging and/or theranostic agents targeting selected emergent GPCRs, namely the Frizzled receptor (FZD), Ghrelin receptor (GHSR-1a), G protein-coupled estrogen receptor (GPER), and Sphingosine-1-phosphate receptor (S1PR). The pharmacological and clinical relevance will be highlighted, giving particular attention to the studies on the synthesis and characterization of targeted molecular imaging agents, biological evaluation, and potential clinical applications in oncology and non-oncology diseases. Whenever relevant, supporting computational studies will be also discussed. Full article
(This article belongs to the Special Issue GPCR Mechanism and Drug Design)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop