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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 14: Resazurin Live Cell Assay: Setup and Fine-Tuning for Reliable Cytotoxicity Results
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Chapter title
Resazurin Live Cell Assay: Setup and Fine-Tuning for Reliable Cytotoxicity Results
Chapter number 14
Book title
Proteomics for Drug Discovery
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7201-2_14
Pubmed ID
Book ISBNs
978-1-4939-7200-5, 978-1-4939-7201-2
Authors

José Á. Rodríguez-Corrales, Jatinder S. Josan

Abstract

In vitro cytotoxicity tests allow for fast and inexpensive screening of drug efficacy prior to in vivo studies. The resazurin assay (commercialized as Alamar Blue(®)) has been extensively utilized for this purpose in 2D and 3D cell cultures, and high-throughput screening. However, improper or lack of assay validation can generate unreliable results and limit reproducibility. Herein, we report a detailed protocol for the optimization of the resazurin assay to determine relevant analytical (limits of detection, quantification, and linear range) and biological (growth kinetics) parameters, and, thus, provide accurate cytotoxicity results. Fine-tuning of the resazurin assay will allow accurate and fast quantification of cytotoxicity for drug discovery. Unlike more complicated methods (e.g., mass spectrometry), this assay utilizes fluorescence spectroscopy and, thus, provides a less costly alternative to observe changes in the reductase proteome of the cells.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 10 19%
Researcher 8 15%
Student > Master 6 12%
Student > Ph. D. Student 6 12%
Lecturer 5 10%
Other 4 8%
Unknown 13 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 27%
Medicine and Dentistry 6 12%
Chemistry 4 8%
Agricultural and Biological Sciences 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 5 10%
Unknown 18 35%