Main description:

This thorough book provides a collection of techniques used in the emerging field of computational chemogenomics, which is an integration of chemoinformatics, bioinformatics, computer science, statistics, automated pattern recognition and modeling, database usage with data retrieval, and systems integration. Beginning with a section on public chemogenomic data resources, the volume continues by delving into the fundamentals of chemoinformatics, bioinformatics, and chemogenomic data processing. After the reader is comfortable with a core skillset, the volume introduces techniques to analyze specific proteins or compound structures and statistical pattern recognition techniques. Later chapters describe the future of chemogenomics including applications to medical care. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that serves as an ideal guide in the lab.
Practical and authoritative, Computational Chemogenomics will greatly aid experimental sciences who are novices to data processing and modeling, as well as those with computationally-oriented backgrounds wishing to engage in this scientific area, which is continually growing and expected to contribute to industry, academic, and government research projects.

Contents:

Part I: Data Resources for Computational Chemogenomics

1. A Survey of Web-Based Chemogenomic Data Resources

Rasel Al Mahmud, Rifat Ara Najnin, and Ahsan Habib Polash

2. Finding Potential Multi-Target Ligands Using PubChem

Sunghwan Kim, Benjamin A. Shoemaker, Evan E. Bolton, and Stephen H. Bryant

Part II: Fundamental Data Processing

3. Fundamental Bioinformatic and Chemoinformatic Data Processing

J.B. Brown

4. Parsing Compound-Protein Bioactivity Tables

J.B. Brown

5. Impact of Molecular Descriptors on Computational Models

Francesca Grisoni, Viviana Consonni, and Roberto Todeschini

6. Physicochemical Property Labels as Molecular Descriptors for Improved Analysis of Compound-Protein and Compound-Compound Networks

Masaaki Kotera

7. Core Statistical Methods for Chemogenomic Data

Christin Rakers

Part III: Structural Analysis Methods in 2D and 3D

8. Structure-Based Detection of Orthosteric and Allosteric Pockets at Protein-Protein Interfaces

Franck Da Silva and Didier Rognan

9. Single Binding Pockets versus Allosteric Binding

Kun Song and Jian Zhang

10. Mapping Biological Activities to Different Types of Molecular Scaffolds: Exemplary Application to Protein Kinase Inhibitors

Dilyana Dimova and Jurgen Bajorath

11. SAR Matrix Method for Large-Scale Analysis of Compound Structure-Activity Relationships and Exploration of Multi-Target Activity Spaces

Ye Hu and Jurgen Bajorath

Part IV: Statistical Pattern Recognition

12. Linear and Kernel Model Construction Methods for Predicting Drug-Target Interactions in a Chemogenomic Framework

Yoshihiro Yamanishi

13. Selection of Informative Examples in Chemogenomic Datasets

Daniel Reker and J.B. Brown

Part V: Emerging Topics

14. A Platform for Comprehensive Genomic Profiling in Human Cancers and Pharmacogenomics Therapy Selection

Tadayuki Kou, Masashi Kanai, Mayumi Kamada, Masahiko Nakatsui, Shigemi Matsumoto, Yasushi Okuno, and Manabu Muto

15. The Future of Computational Chemogenomics

Edgar Jacoby and J.B. Brown