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[资源] Computer-Aided Drug Discovery

Computer-Aided Drug Discovery
Humana Press | Pharmacology & Toxicology | July 8, 2016 | ISBN-10: 1493935194 | 290 pages | pdf | 7.74 mb

Editors: Zhang, Wei (Ed.)
Features practical, hands-on instruction for the use of CADD systems
Includes tips from experts in the field to ensure successful implementation
Focuses on the vital early stages of the drug discovery process

This detailed volume examines computer-aided drug discovery (CADD), a crucial component of modern drug discovery programs that is widely utilized to identity and optimize bioactive compounds for the development of new drugs. With a focus on the methods that are commonly used in the early stage of drug discovery, chapters explore computer simulation, structure prediction, conformational sampling, binding site mapping, docking and scoring, in silico screening, and fragment-based drug design. In addition to the state-of-the-art theoretical concept, this book also includes step-by-step, readily reproducible computational protocols as well as examples of various CADD strategies. The limitations and potential pitfalls of different computational methods are discussed by experts, and tips and advice for their applications are suggested.

Practical and thorough, Computer-Aided Drug Discovery serves as an ideal addition to the Methods in Pharmacology and Toxicology series, guiding researchers toward their lab’s goals with this exciting and versatile technology.

Contents
Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Molecular Dynamics Simulations and Computer-Aided Drug Discovery. . . . . . . . . . 1
Ryan C. Godwin, Ryan Melvin, and Freddie R. Salsbury Jr.
A Review of Evolutionary Algorithms for Computing Functional
Conformations of Protein Molecules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Amarda Shehu
Incorporating Receptor Flexibility into Structure-Based Drug Discovery . . . . . . . . . 65
Chung F. Wong
Understanding Water and Its Many Roles in Biological Structure:
Ways to Exploit a Resource for Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Mostafa H. Ahmed, Alessio Amadasi, Alexander S. Bayden,
Derek J. Cashman, Pietro Cozzini, Chenxiao Da, Deliang L. Chen,
Micaela Fornabaio, Vishal N. Koparde, Andrea Mozzarelli,
Hardik I. Parikh, Aurijit Sarkar, J. Neel Scarsdale,
Francesca Spyrakis, J. Andrew Surface, Ashutosh Tripathi,
Saheem A. Zaidi, and Glen E. Kellogg
CAVITY: Mapping the Druggable Binding Site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Weilin Zhang, Yaxia Yuan, Jianfeng Pei, and Luhua Lai
Methods for Detecting Protein Binding Interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Nurit Haspel
MDock: An Ensemble Docking Suite for Molecular Docking, Scoring
and In Silico Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Chengfei Yan and Xiaoqin Zou
Pharmacophore Modeling: Methods and Applications. . . . . . . . . . . . . . . . . . . . . . . . . . 167
David Ryan Koes
Computational Fragment-Based Drug Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
Chunquan Sheng, Guoqiang Dong, and Chen Wang
Applications of the Fragment Molecular Orbital Method
to Drug Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Michael P. Mazanetz, Ewa Chudyk, Dmitri G. Fedorov,
and Yuri Alexeev
Recent Advances in the Open Access Cheminformatics Toolkits,
Software Tools, Workflow Environments, and Databases . . . . . . . . . . . . . . . . . . . . . . . 257
Pravin Ambure, Rahul Balasaheb Aher, and Kunal Roy
Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297



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