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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 18: Docking and Virtual Screening in Drug Discovery
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Chapter title
Docking and Virtual Screening in Drug Discovery
Chapter number 18
Book title
Proteomics for Drug Discovery
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7201-2_18
Pubmed ID
Book ISBNs
978-1-4939-7200-5, 978-1-4939-7201-2
Authors

Maria Kontoyianni

Abstract

Stages in a typical drug discovery organization include target selection, hit identification, lead optimization, preclinical and clinical studies. Hit identification and lead optimization are very much intertwined with computational modeling. Structure-based virtual screening (VS) has been a staple for more than a decade now in drug discovery with its underlying computational technique, docking, extensively studied. Depending on the objective, the parameters for VS may change, but the overall protocol is very straightforward. The idea behind VS is that a library of small compounds are docked into the binding pocket of a protein (e.g., receptor, enzyme), a number of solutions per molecule, among the top-ranked, are being returned, and a choice is made on the fraction of compounds to be moved forward for testing toward hit identification. The underlying principle of VS is that it differentiates between active and inactive compounds, thus reducing the number of molecules moving forward and possibly offering a complementary tool to high-throughput screening (HTS). Best practices in library selection, target preparation and refinement, criteria in selecting the most appropriate docking/scoring scheme, and a step-wise approach in performing Glide VS are discussed.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 296 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
France 1 <1%
Unknown 294 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 39 13%
Student > Ph. D. Student 34 11%
Student > Master 33 11%
Researcher 16 5%
Student > Doctoral Student 10 3%
Other 35 12%
Unknown 129 44%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 49 17%
Chemistry 36 12%
Pharmacology, Toxicology and Pharmaceutical Science 23 8%
Agricultural and Biological Sciences 22 7%
Immunology and Microbiology 8 3%
Other 27 9%
Unknown 131 44%