Chemoinformatics for Drug Discovery
Jürgen Bajorath
Wiley
<p><b>Chemoinformatics strategies to improve drug discovery results</b></p><p>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. <p><i>Chemoinformatics for Drug Discovery</i> 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: <ul><li>What are our models really telling us? A practical tutorial on avoiding common mistakes when building predictive models</li><li>Exploration of structure-activity relationships and transfer of key elements in lead optimization</li><li>Collaborations between academia and pharma</li><li>Applications of chemoinformatics in pharmaceutical researchexperiences at large international pharmaceutical companies</li><li>Lessons learned from 30 years of developing successful integrated chemoinformatic systems</li></ul><p>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. <p>Integrating chemistry, computer science, and drug discovery, <i>Chemoinformatics for Drug Discovery</i> encapsulates the field as it stands today and opens the door to further advances.Content: <br>Chapter 1 WHAT ARE OUR MODELS REALLY TELLING US? A PRACTICAL TUTORIAL ON AVOIDING COMMON MISTAKES WHEN BUILDING PREDICTIVE MODELS (pages 1–31): W. Patrick Walters<br>Chapter 2 THE CHALLENGE OF CREATIVITY IN DRUG DESIGN (pages 33–50): Ajay N. Jain<br>Chapter 3 A ROUGH SET THEORY APPROACH TO THE ANALYSIS OF GENE EXPRESSION PROFILES (pages 51–83): Joachim Petit, Nathalie Meurice, José Luis Medina‐Franco and Gerald M. Maggiora<br>Chapter 4 BIMODAL PARTIAL LEAST‐SQUARES APPROACH AND ITS APPLICATION TO CHEMOGENOMICS STUDIES FOR MOLECULAR DESIGN (pages 85–95): Kiyoshi Hasegawa and Kimito Funatsu<br>Chapter 5 STABILITY IN MOLECULAR FINGERPRINT COMPARISON (pages 97–112): Anthony Nicholls and Brian Kelley<br>Chapter 6 CRITICAL ASSESSMENT OF VIRTUAL SCREENING FOR HIT IDENTIFICATION (pages 113–130): Dagmar Stumpfe and Jürgen Bajorath<br>Chapter 7 CHEMOMETRIC APPLICATIONS OF NAÏVE BAYESIAN MODELS IN DRUG DISCOVERY (pages 131–148): Eugen Lounkine, Peter S. Kutchukian and Meir Glick<br>Chapter 8 CHEMOINFORMATICS IN LEAD OPTIMIZATION (pages 149–178): Darren V. S. Green and Matthew Segall<br>Chapter 9 USING CHEMOINFORMATICS TOOLS TO ANALYZE CHEMICAL ARRAYS IN LEAD OPTIMIZATION (pages 179–204): George Papadatos, Valerie J. Gillet, Christopher N. Luscombe, Iain M. McLay, Stephen D. Pickett and Peter Willett<br>Chapter 10 EXPLORATION OF STRUCTURE–ACTIVITY RELATIONSHIPS (SARs) AND TRANSFER OF KEY ELEMENTS IN LEAD OPTIMIZATION (pages 205–243): Hans Matter, Stefan Güssregen, Friedemann Schmidt, Gerhard Hessler, Thorsten Naumann and Karl‐Heinz Baringhaus<br>Chapter 11 DEVELOPMENT AND APPLICATIONS OF GLOBAL ADMET MODELS (pages 245–265): Karl‐Heinz Baringhaus, Gerhard Hessler, Hans Matter and Friedemann Schmidt<br>Chapter 12 CHEMOINFORMATICS AND BEYOND (pages 267–290): Catrin Hasselgren, Daniel Muthas, Ernst Ahlberg, Samuel Andersson, Lars Carlsson, Tobias Noeske, Jonna Stålring and Scott Boyer<br>Chapter 13 APPLICATIONS OF CHEMINFORMATICS IN PHARMACEUTICAL RESEARCH (pages 291–320): Bernd Beck, Michael Bieler, Peter Haebel, Andreas Teckentrup, Alexander Weber and Nils Weskamp<br>Chapter 14 LESSONS LEARNED FROM 30 YEARS OF DEVELOPING SUCCESSFUL INTEGRATED CHEMINFORMATIC SYSTEMS (pages 321–341): Michael S. Lajiness and Thomas R. Hagadone<br>Chapter 15 MOLECULAR SIMILARITY ANALYSIS (pages 343–399): José L. Medina‐Franco and Gerald M. Maggiora