Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery

ISBN 10: 1522501150 / ISBN 13: 9781522501152

Published by Medical Information Science Reference, 2016

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Investigates the evolution of pharmaceutical design and computational approaches in the field of molecular docking. Highlighting theoretical backgrounds and emergent research in the area of computer-assisted drug design, this publication is a pivotal source.

Seller Inventory # 448009938

Bibliographic Details

• Title: Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery
• Publisher: Medical Information Science Reference
• Publication Date: 2016
• Language: English
• ISBN 10: 1522501150
• ISBN 13: 9781522501152
• Binding: Gebunden
• Condition: New

About this title

Synopsis

The role of technology in the medical field has resulted in significant developments within the pharmaceutical industry. Computational approaches have emerged as a crucial method in further advancing drug design and development. Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery presents emerging research on the application of computer-assisted design methods for drugs, emphasizing the benefits and improvements that molecular docking has caused within the pharmaceutical industry. Focusing on validation methods, search algorithms, and scoring functions, this book is a pivotal resource for professionals, researchers, students, and practitioners in the field of theoretical and computational chemistry.

About the Author

Siavoush Dastmalchi graduated as Doctor of Pharmacy from Tabriz University of Medical Sciences (TUMS). Then he moved to Sydney where he received his PhD from the Faculty of Pharmacy at the University of Sydney in 2002. Since then he has worked as a full academic in the Medicinal Chemistry Department at the School of Pharmacy, TUMS, teaching medicinal chemistry, instrumental drug analysis and bioinformatics to graduate and postgraduate students. He is currently the Director of the Biotechnology Research Centre at TUMS where he leads his research team mainly with interests in molecular modelling, structural biology, and chemo-bioinformatics for their application to drug discovery.

Maryam Hamzeh-Mivehroud is an assistant professor who graduated as Doctor of Pharmacy from Tabriz University of Medical Sciences in 2004 and received her PhD in Medicinal Chemistry from this university in 2011. Since then she has worked as a full academic member in the Medicinal Chemistry Department at the School of Pharmacy, and teaches medicinal chemistry at the undergraduate and postgraduate levels. Her main research interests are focused on QSAR and molecular modelling based on various description selection algorithms and machine learning methods. She is also professional in working with modelling and statistical softwares such as GROMACS, GOLD, AMBER, GOLPE, MOE, etc.

Babak Sokouti has over 17 years IT technical management and consulting experience, including managing and maintaining sophisticated network infrastructures. He has obtained Bachelor of Science in Electrical Engineering with a specialization in Control from Isfahan University of Technology, Isfahan, Iran; a Master of Science in Electrical Engineering with a specialization in Electronics (with background of biomedical engineering) from Tabriz Branch, Islamic Azad University, Tabriz, Iran; a Master of Science in Information Security with Distinction from Royal Holloway University of London, London, UK; and obtained PhD in Bioinformatics from Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. In addition, he has obtained IT industry certifications including MCP, MCSA 2003, MCDBA 2000, MCSE 2003, and MCTS 2008. His research interests include cryptographic algorithms, information security, network security and protocols, image processing, protein structure prediction, and hybrid intelligent neural network systems based on genetic algorithms.