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Targeting Trafficking in Drug Development

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Cover of 'Targeting Trafficking in Drug Development'

Table of Contents

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    Book Overview
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    Chapter 49 Intracellular Trafficking of Gonadotropin Receptors in Health and Disease
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    Chapter 50 Pharmacological Chaperones as Potential Therapeutic Strategies for Misfolded Mutant Vasopressin Receptors
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    Chapter 55 Natural (and Unnatural) Small Molecules as Pharmacological Chaperones and Inhibitors in Cancer
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    Chapter 57 Investigating Internalization and Intracellular Trafficking of GPCRs: New Techniques and Real-Time Experimental Approaches
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    Chapter 59 Folding Defects Leading to Primary Hyperoxaluria
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    Chapter 60 Targeting of Disordered Proteins by Small Molecules in Neurodegenerative Diseases
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    Chapter 62 The Molecular Physiopathogenesis of Islet Amyloidosis
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    Chapter 64 Pharmacoperones for Misfolded Gonadotropin Receptors
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    Chapter 65 Conserved Oligomeric Golgi and Neuronal Vesicular Trafficking
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    Chapter 67 Heritable Skeletal Disorders Arising from Defects in Processing and Transport of Type I Procollagen from the ER: Perspectives on Possible Therapeutic Approaches
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    Chapter 68 Pharmacological Chaperones: Beyond Conformational Disorders
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    Chapter 71 SLC6 Transporter Folding Diseases and Pharmacochaperoning
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    Chapter 72 Potential Pharmacological Chaperones for Cystathionine Beta-Synthase-Deficient Homocystinuria
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    Chapter 103 Cystic Fibrosis, Cystic Fibrosis Transmembrane Conductance Regulator and Drugs: Insights from Cellular Trafficking
Attention for Chapter 55: Natural (and Unnatural) Small Molecules as Pharmacological Chaperones and Inhibitors in Cancer
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Chapter title
Natural (and Unnatural) Small Molecules as Pharmacological Chaperones and Inhibitors in Cancer
Chapter number 55
Book title
Targeting Trafficking in Drug Development
Published in
Handbook of experimental pharmacology, January 2017
DOI 10.1007/164_2017_55
Pubmed ID
Book ISBNs
978-3-31-974163-5, 978-3-31-974164-2
Authors

Isabel Betancor-Fernández, David J. Timson, Eduardo Salido, Angel L. Pey, Betancor-Fernández, Isabel, Timson, David J., Salido, Eduardo, Pey, Angel L.

Abstract

Mutations causing single amino acid exchanges can dramatically affect protein stability and function, leading to disease. In this chapter, we will focus on several representative cases in which such mutations affect protein stability and function leading to cancer. Mutations in BRAF and p53 have been extensively characterized as paradigms of loss-of-function/gain-of-function mechanisms found in a remarkably large fraction of tumours. Loss of RB1 is strongly associated with cancer progression, although the molecular mechanisms by which missense mutations affect protein function and stability are not well known. Polymorphisms in NQO1 represent a remarkable example of the relationships between intracellular destabilization and inactivation due to dynamic alterations in protein ensembles leading to loss of function. We will review the function of these proteins and their dysfunction in cancer and then describe in some detail the effects of the most relevant cancer-associated single amino exchanges using a translational perspective, from the viewpoints of molecular genetics and pathology, protein biochemistry and biophysics, structural, and cell biology. This will allow us to introduce several representative examples of natural and synthetic small molecules applied and developed to overcome functional, stability, and regulatory alterations due to cancer-associated amino acid exchanges, which hold the promise for using them as potential pharmacological cancer therapies.

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

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Student > Postgraduate 2 13%
Researcher 2 13%
Lecturer 1 6%
Professor 1 6%
Other 3 19%
Unknown 5 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Medicine and Dentistry 3 19%
Agricultural and Biological Sciences 2 13%
Immunology and Microbiology 1 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Other 0 0%
Unknown 5 31%
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 28 October 2017.
All research outputs
#18,575,277
of 23,007,053 outputs
Outputs from Handbook of experimental pharmacology
#506
of 647 outputs
Outputs of similar age
#311,426
of 421,244 outputs
Outputs of similar age from Handbook of experimental pharmacology
#25
of 31 outputs
Altmetric has tracked 23,007,053 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 647 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 421,244 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.