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Proteomics for Drug Discovery

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Cover of 'Proteomics for Drug Discovery'

Table of Contents

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    Book Overview
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    Chapter 1 A Photoaffinity Labeling-Based Chemoproteomics Strategy for Unbiased Target Deconvolution of Small Molecule Drug Candidates
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    Chapter 2 Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins
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    Chapter 3 Monitoring Dynamic Changes of the Cell Surface Glycoproteome by Quantitative Proteomics
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    Chapter 4 High-Resolution Parallel Reaction Monitoring with Electron Transfer Dissociation for Middle-Down Proteomics: An Application to Study the Quantitative Changes Induced by Histone Modifying Enzyme Inhibitors and Activators
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    Chapter 5 Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery
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    Chapter 6 Target Identification Using Cell Permeable and Cleavable Chloroalkane Derivatized Small Molecules
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    Chapter 7 Microfluidics-Mass Spectrometry of Protein-Carbohydrate Interactions: Applications to the Development of Therapeutics and Biomarker Discovery
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    Chapter 8 Studying Protein–Protein Interactions by Biotin AP-Tagged Pulldown and LTQ-Orbitrap Mass Spectrometry
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    Chapter 9 Post-Translational Modification Profiling-Functional Proteomics for the Analysis of Immune Regulation
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    Chapter 10 Reverse Phase Protein Arrays and Drug Discovery
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    Chapter 11 Probing Protein Kinase-ATP Interactions Using a Fluorescent ATP Analog
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    Chapter 12 Preparation of Disease-Related Protein Assemblies for Single Particle Electron Microscopy
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    Chapter 13 Identification of Lipid Binding Modulators Using the Protein-Lipid Overlay Assay
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    Chapter 14 Resazurin Live Cell Assay: Setup and Fine-Tuning for Reliable Cytotoxicity Results
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    Chapter 15 Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows
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    Chapter 16 Method to Identify Silent Codon Mutations That May Alter Peptide Elongation Kinetics and Co-translational Protein Folding
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    Chapter 17 In Silico Design of Anticancer Peptides
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    Chapter 18 Docking and Virtual Screening in Drug Discovery
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    Chapter 19 Bioinformatics Resources for Interpreting Proteomics Mass Spectrometry Data
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    Chapter 20 Erratum to: Probing Protein Kinase-ATP Interactions Using a Fluorescent ATP Analog
Attention for Chapter 16: Method to Identify Silent Codon Mutations That May Alter Peptide Elongation Kinetics and Co-translational Protein Folding
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Chapter title
Method to Identify Silent Codon Mutations That May Alter Peptide Elongation Kinetics and Co-translational Protein Folding
Chapter number 16
Book title
Proteomics for Drug Discovery
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7201-2_16
Pubmed ID
Book ISBNs
978-1-4939-7200-5, 978-1-4939-7201-2
Authors

Ronald Worthington, Elijah Ball, Brentsen Wolf, Gregory Takacs, Worthington, Ronald, Ball, Elijah, Wolf, Brentsen, Takacs, Gregory

Abstract

Due to the redundancy of the protein genetic code, mutational changes in the second or third nucleotide of an existing codon may not change the amino acid specification of the resulting modified codon. When peptide primary sequence is unchanged by mutation, that mutation is assumed to have no functional consequences. However, for one key gene involved in drug transport, MDR-1, several silent, synonymous mutations have been shown to alter protein structure and substrate affinity (Kimchi-Sarfaty et al., Science 315:525-528, 2007). The mechanism of these changes, in the absence of primary amino acid sequence changes, appears to be the change in abundance of the transfer RNA molecules complementary to the mutated, although synonymous, new codon. Transfer RNA abundance is proportional to the frequency of each codon as found in human protein coding DNA (Sharp et al., Nucleic Acids Res 14(13):5125-5143, 1986). These frequencies have been mapped for many thousands of human proteins (Nakamura et al., Nucleic Acids Res 28:292, 2000). This method analyzes silent codon mutations in whole genome data. Where there are large changes in codon frequency resulting from codon sequence mutation, the affected proteins are mapped to potential disease pathways, in the context of clinical phenotypes associated with the patient genome data.

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Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Professor 3 60%
Student > Master 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 1 20%
Biochemistry, Genetics and Molecular Biology 1 20%
Medicine and Dentistry 1 20%
Unknown 2 40%