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Exploring the chemical space of peptides for drug discovery: a focus on linear and cyclic penta-peptides

Overview of attention for article published in Molecular Diversity, February 2018
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Title
Exploring the chemical space of peptides for drug discovery: a focus on linear and cyclic penta-peptides
Published in
Molecular Diversity, February 2018
DOI 10.1007/s11030-018-9812-9
Pubmed ID
Authors

Bárbara I. Díaz-Eufracio, Oscar Palomino-Hernández, Richard A. Houghten, José L. Medina-Franco

Abstract

Peptide and peptide-like structures are regaining attention in drug discovery. Previous studies suggest that bioactive peptides have diverse structures and may have physicochemical properties attractive to become hit and lead compounds. However, chemoinformatic studies that characterize such diversity are limited. Herein, we report the physicochemical property profile and chemical space of four synthetic linear and cyclic combinatorial peptide libraries. As a case study, the analysis was focused on penta-peptides. The chemical space of the peptide and N-methylated peptides libraries was compared to compound data sets of pharmaceutical relevance. Results indicated that there is a major overlap in the chemical space of N-methylated cyclic peptides with inhibitors of protein-protein interactions and macrocyclic natural products available for screening. Also, there is an overlap between the chemical space of the synthetic peptides with peptides approved for clinical use (or in clinical trials), and to other approved drugs that are outside the traditional chemical space. Results further support that synthetic penta-peptides are suitable compounds to be used in drug discovery projects.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 14%
Researcher 5 14%
Student > Doctoral Student 4 11%
Student > Bachelor 3 9%
Professor 3 9%
Other 9 26%
Unknown 6 17%
Readers by discipline Count As %
Chemistry 12 34%
Biochemistry, Genetics and Molecular Biology 6 17%
Pharmacology, Toxicology and Pharmaceutical Science 3 9%
Agricultural and Biological Sciences 2 6%
Engineering 2 6%
Other 3 9%
Unknown 7 20%
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 24 February 2018.
All research outputs
#18,589,103
of 23,025,074 outputs
Outputs from Molecular Diversity
#331
of 470 outputs
Outputs of similar age
#335,145
of 446,267 outputs
Outputs of similar age from Molecular Diversity
#3
of 5 outputs
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So far Altmetric has tracked 470 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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