Jürgen Bajorath

Chemoinformatics for Drug Discovery (eBook, PDF)

• Format: PDF

Produktbeschreibung

Chemoinformatics strategies to improve drug discovery results With contributions from leading researchers in academia and the pharmaceutical industry as well as experts from the software industry, this book explains how chemoinformatics enhances drug discovery and pharmaceutical research efforts, describing what works and what doesn't. Strong emphasis is put on tested and proven practical applications, with plenty of case studies detailing the development and implementation of chemoinformatics methods to support successful drug discovery efforts. Many of these case studies depict groundbreaking collaborations between academia and the pharmaceutical industry. Chemoinformatics for Drug Discovery is logically organized, offering readers a solid base in methods and models and advancing to drug discovery applications and the design of chemoinformatics infrastructures. The book features 15 chapters, including: * What are our models really telling us? A practical tutorial on avoiding common mistakes when building predictive models * Exploration of structure-activity relationships and transfer of key elements in lead optimization * Collaborations between academia and pharma * Applications of chemoinformatics in pharmaceutical research--experiences at large international pharmaceutical companies * Lessons learned from 30 years of developing successful integrated chemoinformatic systems Throughout the book, the authors present chemoinformatics strategies and methods that have been proven to work in pharmaceutical research, offering insights culled from their own investigations. Each chapter is extensively referenced with citations to original research reports and reviews. Integrating chemistry, computer science, and drug discovery, Chemoinformatics for Drug Discovery encapsulates the field as it stands today and opens the door to further advances.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 432
• Erscheinungstermin: 13. November 2013
• Englisch
• ISBN-13: 9781118743058
• Artikelnr.: 40020339

Autorenporträt

JÜRGEN BAJORATH, PhD, is Chair of Life Science Informatics at the University of Bonn and also an Affiliate Professor in the Department of Biological Structure at the University of Washington. In addition, he has more than 10 years' experience in drug disovery. His research focuses on the development of computational methods for medicinal chemistry and chemical biology. Dr. Bajorath holds 26 patents, has authored more than 400 scientific articles, and edited four books.

Inhaltsangabe

Preface vii
Contributors xiii
1 What Are Our Models Really Telling Us? A Practical Tutorial on Avoiding
Common Mistakes when Building Predictive Models 1
W. Patrick Walters
2 The Challenge of Creativity in Drug Design 33
Ajay N. Jain
3 A Rough Set Theory Approach to the Analysis of Gene Expression Profiles
51
Joachim Petit, Nathalie Meurice, José Luis Medina-Franco, and Gerald M.
Maggiora
4 Bimodal Partial Least-Squares Approach and Its Application to
Chemogenomics Studies for Molecular Design 85
Kiyoshi Hasegawa and Kimito Funatsu
5 Stability in Molecular Fingerprint Comparison 97
Anthony Nicholls and Brian Kelley
6 Critical Assessment of Virtual Screening for Hit Identification 113
Dagmar Stumpfe and Jürgen Bajorath
7 Chemometric Applications of Naïve Bayesian Models in Drug Discovery:
Beyond Compound Ranking 131
Eugen Lounkine, Peter S. Kutchukian, and Meir Glick
8 Chemoinformatics in Lead Optimization 149
Darren V. S. Green and Matthew Segall
9 Using Chemoinformatics Tools to Analyze Chemical Arrays in Lead
Optimization 179
George Papadatos, Valerie J. Gillet, Christopher N. Luscombe, Iain M.
McLay, Stephen D. Pickett, and Peter Willett
10 Exploration of Structure-Activity Relationships (SARs) and Transfer of
Key Elements in Lead Optimization 205
Hans Matter, Stefan Güssregen, Friedemann Schmidt, Gerhard Hessler,
Thorsten Naumann, and Karl-Heinz Baringhaus
11 Development and Applications of Global ADMET Models: In Silico
Prediction of Human Microsomal Lability 245
Karl-Heinz Baringhaus, Gerhard Hessler, Hans Matter, and Friedemann Schmidt
12 Chemoinformatics and Beyond: Moving from Simple Models to Complex
Relationships in Pharmaceutical Computational Toxicology 267
Catrin Hasselgren, Daniel Muthas, Ernst Ahlberg, Samuel Andersson, Lars
Carlsson, Tobias Noeske, Jonna Stålring, and Scott Boyer
13 Applications of Cheminformatics in Pharmaceutical Research: Experiences
at Boehringer Ingelheim in Germany 291
Bernd Beck, Michael Bieler, Peter Haebel, Andreas Teckentrup, Alexander
Weber, and Nils Weskamp
14 Lessons Learned from 30 Years of Developing Successful Integrated
Cheminformatic Systems 321
Michael S. Lajiness and Thomas R. Hagadone
15 Molecular Similarity Analysis 343
José L. Medina-Franco and Gerald M. Maggiora
Index 401

Rezensionen

"Overall the book is well written, logically following the larger storyline and most of the time offering high quality reviews . . . Personally, I enjoyed reading this book and would recommend it as a general introduction to the subject aimed especially for post-graduate students and non-specialists working in the area of drug design, but also for all of those who just want to update their knowledge." (ChemMedChem, 1 June 2014)