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Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

Overview of attention for article published in Frontiers in Pharmacology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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405 Mendeley
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Title
Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design
Published in
Frontiers in Pharmacology, March 2018
DOI 10.3389/fphar.2018.00128
Pubmed ID
Authors

Shaherin Basith, Minghua Cui, Stephani J. Y. Macalino, Jongmi Park, Nina A. B. Clavio, Soosung Kang, Sun Choi

Abstract

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the "golden age for GPCR structural biology." Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand- and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

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X Demographics

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 405 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 405 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 69 17%
Student > Ph. D. Student 65 16%
Student > Master 44 11%
Researcher 33 8%
Student > Doctoral Student 17 4%
Other 35 9%
Unknown 142 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 99 24%
Chemistry 51 13%
Pharmacology, Toxicology and Pharmaceutical Science 34 8%
Agricultural and Biological Sciences 23 6%
Medicine and Dentistry 10 2%
Other 37 9%
Unknown 151 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 26 July 2019.
All research outputs
#4,194,506
of 23,344,526 outputs
Outputs from Frontiers in Pharmacology
#1,848
of 16,803 outputs
Outputs of similar age
#82,601
of 333,139 outputs
Outputs of similar age from Frontiers in Pharmacology
#55
of 365 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,803 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,139 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 365 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.