Chemoinformatics

Chemoinformatics strategies to improve drug discoveryresults

With contributions from leading researchers in academia and thepharmaceutical industry as well as experts from the softwareindustry, this book explains how chemoinformatics enhances drugdiscovery and pharmaceutical research efforts, describing whatworks and what doesn't. Strong emphasis is put on tested and provenpractical applications, with plenty of case studies detailing thedevelopment and implementation of chemoinformatics methods tosupport successful drug discovery efforts. Many of these casestudies depict groundbreaking collaborations between academia andthe pharmaceutical industry.

Chemoinformatics for Drug Discovery is logicallyorganized, offering readers a solid base in methods and models andadvancing to drug discovery applications and the design ofchemoinformatics infrastructures. The book features 15 chapters, including:

• What are our models really telling us? A practical tutorial onavoiding common mistakes when building predictive models
• Exploration of structure-activity relationships and transfer ofkey elements in lead optimization
• Collaborations between academia and pharma
• Applications of chemoinformatics in pharmaceuticalresearch--experiences at large international pharmaceuticalcompanies
• Lessons learned from 30 years of developing successfulintegrated chemoinformatic systems

Throughout the book, the authors present chemoinformaticsstrategies and methods that have been proven to work inpharmaceutical research, offering insights culled from their owninvestigations. Each chapter is extensively referenced withcitations to original research reports and reviews.

Integrating chemistry, computer science, and drug discovery, Chemoinformatics for Drug Discovery encapsulates the fieldas it stands today and opens the door to further advances.