Details

Chemoinformatics for Drug Discovery


Chemoinformatics for Drug Discovery


1. Aufl.

von: Jürgen Bajorath

111,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 25.09.2013
ISBN/EAN: 9781118743096
Sprache: englisch
Anzahl Seiten: 432

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Beschreibungen

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.
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 C ritical 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 (SAR s) 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
“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)
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.
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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