Chemoinformatics in Drug Discovery

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.

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 M÷lndal (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 cheminformatics, virtual screening, QSAR, and lead and drug discovery. 18 02 Cheminformatics experts from large pharmaceutical companies, as well as from cheminformatics service providers and from academia demonstrate what can be achieved today by harnessing the power of computational methods for the drug discovery process.<br> <br> From the contents:<br> <br> * Cheminformatics in Lead Discovery<br> * Molecular Complexity and Screening Set Design<br> * Algorithmic Engines in Virtual Screening<br> * Pharmacophore-Based Virtual Screening<br> * Enhancing Hit Quality and Diversity<br> * Molecular Diversity in Lead Discovery<br> * In Silico Lead Optimization<br> * Using Databases and Libraries<br> * Combinational Libraries Based on Privileged Substructures<br> * Strategies for Directed Compound Acquisition<br> * Predictive QSAR Models in Database Mining<br> * Drug Discovery in Academia - a Case Study<br> <br> With the user rather than the developer of cheminformatics software in mind, the successful application of computational tools for commonly encountered tasks is described in detail, and numerous real life examples are given. An invaluable resource for drug developers and medicinal chemists in academia and industry.<br>