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Proteome Bioinformatics

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Cover of 'Proteome Bioinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Proteome Bioinformatics.
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    Chapter 2 Proteomic Data Storage and Sharing.
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    Chapter 3 Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data.
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    Chapter 4 Label-Based and Label-Free Strategies for Protein Quantitation.
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    Chapter 5 TMT One-Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform.
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    Chapter 6 Unassigned MS/MS Spectra: Who Am I?
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    Chapter 7 Methods to Calculate Spectrum Similarity.
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    Chapter 8 Proteotypic Peptides and Their Applications.
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    Chapter 9 Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test.
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    Chapter 10 De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data.
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    Chapter 11 Phylogenetic Analysis Using Protein Mass Spectrometry.
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    Chapter 12 Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data.
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    Chapter 13 A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes.
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    Chapter 14 Network Tools for the Analysis of Proteomic Data.
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    Chapter 15 Determining the Significance of Protein Network Features and Attributes Using Permutation Testing.
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    Chapter 16 Bioinformatics Tools and Resources for Analyzing Protein Structures.
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    Chapter 17 In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signaling.
Attention for Chapter 17: In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signaling.
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Chapter title
In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signaling.
Chapter number 17
Book title
Proteome Bioinformatics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6740-7_17
Pubmed ID
Book ISBNs
978-1-4939-6738-4, 978-1-4939-6740-7
Authors

Swathik Clarancia Peter, Jayakanthan Mannu, Premendu P. Mathur

Editors

Shivakumar Keerthikumar, Suresh Mathivanan

Abstract

Axl-Gas6 signaling plays an important role in numerous cancers. Axl kinase, a member of receptor tyrosine kinase family is activated by different mechanisms with Gas6 as its major activator. Targeting the Axl with inhibitors may block the binding of Gas6 and further hinders the activation of Axl. This in turn inhibits the Axl-Gas6 signaling. Thus, inhibitors of the Axl kinase may serve as ideal drug candidates for treating many human cancers. In this study we carried out virtual screening of drug-like molecules from ZINC database to identify potential inhibitors for Axl kinase. Our virtual screening study showed that ZINC83758120, ZINC34079369, and ZINC83758121 are potential drug-like lead molecules to inhibit Axl kinase.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 33%
Researcher 1 17%
Other 1 17%
Unknown 2 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 33%
Agricultural and Biological Sciences 1 17%
Unknown 3 50%