Structure/Ligand-based Drug Design and Structure Bioinformatics | Basics, Concepts, Methods, and Applications

Shuxing Zhang

ISBN 10: 3639164156 / ISBN 13: 9783639164152

Published by VDM Verlag Dr. Müller, 2009

About this Item

Structure/Ligand-based Drug Design and Structure Bioinformatics | Basics, Concepts, Methods, and Applications | Shuxing Zhang | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639164152 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.

Seller Inventory # 101553683

Bibliographic Details

• Title: Structure/Ligand-based Drug Design and Structure Bioinformatics | Basics, Concepts, Methods, and Applications
• Publisher: VDM Verlag Dr. Müller
• Publication Date: 2009
• Language: English
• ISBN 10: 3639164156
• ISBN 13: 9783639164152
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 174 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Drug discovery and development is a very expensive and time-consuming process. To improve the efficiency of the pipeline, Computer-Aided Drug Design (CADD) has become increasingly important over the years. CADD represents an interplay paradigm between in-depth in silico studies and the follow-up wet-lab validations. However we have not achieved true synergy among various computational subdisciplines, such as cheminformatics and bioinformatics. This book, therefore, focuses on the design, development and applications of novel approaches for CADD and protein structure bioinformatics. These approaches were developed in the areas of both ligand-based and structure-based drug design. In addition, Simplicial Neighborhood Analysis of Protein Packing (SNAPP) has been employed for the analysis of protein flexibility. This has resulted in powerful and cutting-edge computational tools for the rational drug design and the prediction of unintuitive consequences of targeted therapeutics. The work should help shed some light on this exciting field, and should be especially useful to professionals in computational drug discovery and other biomedical research-related areas.

About the Author

Shuxing Zhang, Ph.D.: Studied Computational Drug Discovery and Medicinal Chemistry at the University of North Carolina at Chapel Hill. Currently Assistant Professor in the Department of Experimental Therapeutics and Director of Molecular Modeling Core Facility at M.D. Anderson Cancer Center, Houston, USA.