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Chemoinformatics in Drug Discovery, Volume 23

Tudor I. Oprea (Editor), Raimund Mannhold (Series Editor), Hugo Kubinyi (Series Editor), Gerd Folkers (Series Editor)
ISBN: 978-3-527-60420-3
515 pages
March 2006
Chemoinformatics in Drug Discovery, Volume 23 (3527604200) cover image


This handbook provides the first-ever inside view of today's integrated approach to rational drug design. Chemoinformatics experts from large pharmaceutical companies, as well as from chemoinformatics service providers and from academia demonstrate what can be achieved today by harnessing the power of computational methods for the drug discovery process.
With the user rather than the developer of chemoinformatics software in mind, this book describes the successful application of computational tools to real-life problems and presents solution strategies to commonly encountered problems. It shows how almost every step of the drug discovery pipeline can be optimized and accelerated by using chemoinformatics tools -- from the management of compound databases to targeted combinatorial synthesis, virtual screening and efficient hit-to-lead transition.
An invaluable resource for drug developers and medicinal chemists in academia and industry.
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Table of Contents


Chemoinformatics in Lead Discovery
Computational Chemistry, Molecular Complexity and Screening Set Design
Algorithmic Engines in Virtual Screening
Strengths and Limitations of Pharmacophore-Based Virtual Screening

Enhancing Hit Quality and Diversity Within Assay Throughput Constraints
Molecular Diversity in Lead Discovery: From Quantity to Quality
In Silico Lead Optimization

WOMBAT: World of Molecular Bioactivity
Cabinet -
Chemical And Biological Informatics Network
Structure Modification in Chemical Databases
Rational Design of GPCR-specific Combinational Libraries Based on the Concept of Privileged Substructures

A Practical Strategy for Directed Compound Acquisition
Efficient Strategies for Lead Optimization
Chemoinformatic Tools for Library Design and the Hit-to-Lead Process: A User's Perspective
Application of Predictive QSAR Models to Database Mining
Drug Discovery in Academia - a Case Study
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Author Information

Tudor I. Oprea is Professor of Biochemistry and Molecular Biology and Chief, Division of Biocomputing at the University of New Mexico School of Medicine, Albuquerque (USA). He was born in Timisoara (Romania) where he did all his studies including his Ph.D. thesis under the supervision of Francisc Schneider. He was a post-doctoral fellow at Washington University with Garland Marshall, and Los Alamos National Laboratory with Angel Garcia. He worked six years at AstraZeneca in Mölndal (Sweden), before moving to New Mexico as full Professor in 2002. He received the Hansch Award from the QSAR and Modeling Society in 2002. He is interested in chemoinformatics, virtual screening, QSAR, and lead and drug discovery.
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"...a well-written, up-to-date, and practical book for medicinal chemists and computational chemists working in drug discovery."
Journal of Medicinal Chemistry

"The volume is a valuable source of information for readers engaged in all areas of pharmaceutical research and development and medicinal chemistry."
Angewandte Chemie International Edition

"... a unique and richly erudite text premised on a sub-layer of the scientific process ..."
Electric Review

"...truly a delightful beginning and ending to a thoroughly superb reading that is worth the price of admission."
Journal of the American Chemical Society
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