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Fragment-Based Methods in Drug Discovery

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Cover of 'Fragment-Based Methods in Drug Discovery'

Table of Contents

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    Book Overview
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    Chapter 1 Solvation methods for protein-ligand docking.
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    Chapter 2 Binding site druggability assessment in fragment-based drug design.
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    Chapter 3 Generating "fragment-based virtual library" using pocket similarity search of ligand-receptor complexes.
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    Chapter 4 Virtual fragment preparation for computational fragment-based drug design.
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    Chapter 5 Fragment library design: using cheminformatics and expert chemists to fill gaps in existing fragment libraries.
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    Chapter 6 Protocol for fragment hopping.
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    Chapter 7 Site Identification by Ligand Competitive Saturation (SILCS) Simulations for Fragment-Based Drug Design.
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    Chapter 8 A Computational Fragment-Based De Novo Design Protocol Guided by Ligand Efficiency Indices (LEI).
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    Chapter 9 Scoring functions for fragment-based drug discovery.
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    Chapter 10 Computational methods for fragment-based ligand design: growing and linking.
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    Chapter 11 Design strategies for computational fragment-based drug design.
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    Chapter 12 Protein binding site analysis for drug discovery using a computational fragment-based method.
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    Chapter 13 Fragment-based design of kinase inhibitors: a practical guide.
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    Chapter 14 Designing a small molecule erythropoietin mimetic.
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    Chapter 15 Designing an Orally Available Nontoxic p38 Inhibitor with a Fragment-Based Strategy.
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Title
Fragment-Based Methods in Drug Discovery
Published by
Springer New York, February 2015
DOI 10.1007/978-1-4939-2486-8
ISBNs
978-1-4939-2485-1, 978-1-4939-2486-8
Editors

Klon, Anthony E.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Nigeria 1 1%
Unknown 82 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 21%
Student > Ph. D. Student 17 20%
Student > Bachelor 11 13%
Student > Master 11 13%
Professor > Associate Professor 5 6%
Other 13 15%
Unknown 10 12%
Readers by discipline Count As %
Chemistry 20 24%
Biochemistry, Genetics and Molecular Biology 16 19%
Agricultural and Biological Sciences 13 15%
Pharmacology, Toxicology and Pharmaceutical Science 8 9%
Medicine and Dentistry 5 6%
Other 11 13%
Unknown 12 14%