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Computational Methods for GPCR Drug Discovery

Overview of attention for book
Cover of 'Computational Methods for GPCR Drug Discovery'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Current and Future Challenges in GPCR Drug Discovery
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    Chapter 2 Characterization of Ligand Binding to GPCRs Through Computational Methods
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    Chapter 3 Breakthrough in GPCR Crystallography and Its Impact on Computer-Aided Drug Design
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    Chapter 4 A Structural Framework for GPCR Chemogenomics: What’s In a Residue Number?
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    Chapter 5 GPCR Homology Model Generation for Lead Optimization
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    Chapter 6 GPCRs: What Can We Learn from Molecular Dynamics Simulations?
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    Chapter 7 Methods of Exploring Protein–Ligand Interactions to Guide Medicinal Chemistry Efforts
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    Chapter 8 Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method
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    Chapter 9 Molecular Basis of Ligand Dissociation from G Protein-Coupled Receptors and Predicting Residence Time
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    Chapter 10 Methodologies for the Examination of Water in GPCRs
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    Chapter 11 Methods for Virtual Screening of GPCR Targets: Approaches and Challenges
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    Chapter 12 Approaches for Differentiation and Interconverting GPCR Agonists and Antagonists
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    Chapter 13 Opportunities and Challenges in the Discovery of Allosteric Modulators of GPCRs
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    Chapter 14 Challenges and Opportunities in Drug Discovery of Biased Ligands
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    Chapter 15 Synergistic Use of GPCR Modeling and SDM Experiments to Understand Ligand Binding
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    Chapter 16 Computational Support of Medicinal Chemistry in Industrial Settings
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    Chapter 17 Investigating Small-Molecule Ligand Binding to G Protein-Coupled Receptors with Biased or Unbiased Molecular Dynamics Simulations
  19. Altmetric Badge
    Chapter 18 Ligand-Based Methods in GPCR Computer-Aided Drug Design
  20. Altmetric Badge
    Chapter 19 Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery
  21. Altmetric Badge
    Chapter 20 Cheminformatics in the Service of GPCR Drug Discovery
  22. Altmetric Badge
    Chapter 21 Modeling and Deorphanization of Orphan GPCRs
Attention for Chapter 9: Molecular Basis of Ligand Dissociation from G Protein-Coupled Receptors and Predicting Residence Time
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Chapter title
Molecular Basis of Ligand Dissociation from G Protein-Coupled Receptors and Predicting Residence Time
Chapter number 9
Book title
Computational Methods for GPCR Drug Discovery
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7465-8_9
Pubmed ID
Book ISBNs
978-1-4939-7464-1, 978-1-4939-7465-8
Authors

Dong Guo, Adriaan P. IJzerman

Abstract

G protein-coupled receptors (GPCRs) are integral membrane proteins and represent the largest class of drug targets. During the past decades progress in structural biology has enabled the crystallographic elucidation of the architecture of these important macromolecules. It also provided atomic-level visualization of ligand-receptor interactions, dramatically boosting the impact of structure-based approaches in drug discovery. However, knowledge obtained through crystallography is limited to static structural information. Less information is available showing how a ligand associates with or dissociates from a given receptor, whose importance is in fact increasingly recognized by the drug research community. Owing to recent advances in computer power and algorithms, molecular dynamics stimulations have become feasible that help in analyzing the kinetics of the ligand binding process. Here, we review what is currently known about the dynamics of GPCRs in the context of ligand association and dissociation, as determined through both crystallography and computer simulations. We particularly focus on the molecular basis of ligand dissociation from GPCRs and provide case studies that predict ligand dissociation pathways and residence time.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 30%
Researcher 4 20%
Student > Doctoral Student 2 10%
Student > Master 2 10%
Student > Bachelor 1 5%
Other 1 5%
Unknown 4 20%
Readers by discipline Count As %
Chemistry 4 20%
Agricultural and Biological Sciences 3 15%
Biochemistry, Genetics and Molecular Biology 2 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Psychology 1 5%
Other 3 15%
Unknown 6 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2017.
All research outputs
#15,484,498
of 23,009,818 outputs
Outputs from Methods in molecular biology
#5,388
of 13,157 outputs
Outputs of similar age
#269,723
of 442,310 outputs
Outputs of similar age from Methods in molecular biology
#596
of 1,498 outputs
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So far Altmetric has tracked 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.