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Computational Modeling of Drugs Against Alzheimer’s Disease

  • Book
  • © 2018

Overview

Editors:
  1. Kunal Roy

    1. Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

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  • Includes cutting-edge methods and protocols
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

Part of the book series: Neuromethods (NM, volume 132)

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Table of contents (21 protocols)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. An Introduction to the Disease

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Alzheimer’s Disease Therapy: Present and Future Molecules

      • Awanish Kumar, Ashwini Kumar
      Pages 3-22

  3. Computational Modeling Methods for Anti-Alzheimer Agents

    1. Front Matter

      Pages 23-23
      Download chapter PDF

    2. Recent Advances in Computational Approaches for Designing Potential Anti-Alzheimer’s Agents

      • Sergi Gómez-Ganau, Jesús Vicente de Julián-Ortiz, Rafael Gozalbes
      Pages 25-59

    3. Computer-Aided Drug Design Approaches to Study Key Therapeutic Targets in Alzheimer’s Disease

      • Agostinho Lemos, Rita Melo, Irina S. Moreira, M. Natália D. S. Cordeiro
      Pages 61-106

    4. Virtual Screening in the Search of New and Potent Anti-Alzheimer Agents

      • Livia Basile
      Pages 107-137

    5. Molecular Field Topology Analysis (MFTA) in the Design of Neuroprotective Compounds

      • Eugene V. Radchenko, Vladimir A. Palyulin, Nikolay S. Zefirov
      Pages 139-159

  4. Modeling of Ligands Acting Against Specific Anti-Alzheimer Drug Targets

    1. Front Matter

      Pages 161-161
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    2. Galantamine Derivatives as Acetylcholinesterase Inhibitors: Docking, Design, Synthesis, and Inhibitory Activity

      • Irini Doytchinova, Mariyana Atanasova, Georgi Stavrakov, Irena Philipova, Dimitrina Zheleva-Dimitrova
      Pages 163-176

    3. Modeling of BACE-1 Inhibitors as Anti-Alzheimer’s Agents

      • Odailson Santos Paz, Thamires Quadros Froes, Franco Henrique Leite, Marcelo Santos Castilho
      Pages 177-206

    4. Design of Anti-Alzheimer’s Disease Agents Focusing on a Specific Interaction with Target Biomolecules

      • Yoshio Hamada, Kenji Usui
      Pages 207-228

    5. Molecular Docking and Molecular Dynamics Simulation to Evaluate Compounds That Avoid the Amyloid Beta 1-42 Aggregation

      • Maricarmen Hernández Rodríguez, Leticia Guadalupe Fragoso Morales, José Correa Basurto, Martha Cecilia Rosales Hernández
      Pages 229-248

    6. In Silico Strategies to Design Small Molecules to Study Beta-Amyloid Aggregation

      • Praveen P. N. Rao, Deguo Du
      Pages 249-261

    7. Computational Approaches to Understand Cleavage Mechanism of Amyloid Beta (Aβ) Peptide

      • Kailas Dashrath Sonawane, Maruti Jayaram Dhanavade
      Pages 263-282

    8. Computational Modeling of Gamma-Secretase Inhibitors as Anti-Alzheimer Agents

      • Prabu Manoharan, Nanda Ghoshal
      Pages 283-303

    9. Molecular Modeling of Tau Proline-Directed Protein Kinase (PDPK) Inhibitors

      • Carlos Navarro-Retamal, Julio Caballero
      Pages 305-345

    10. Computational Modelling of Kinase Inhibitors as Anti-Alzheimer Agents

      • Mange Ram Yadav, Mahesh A. Barmade, Rupesh V. Chikhale, Prashant R. Murumkar
      Pages 347-417

    11. Computational Modeling of Drugs for Alzheimer’s Disease: Design of Serotonin 5-HT6 Antagonists

      • Ádám A. Kelemen, Stefan Mordalski, Andrzej J. Bojarski, György M. Keserű
      Pages 419-461

    12. Computational Modeling of Diagnostic Imaging Agents for Alzheimer’s Disease: Molecular Imaging Agents for the In Vivo Detection of Amyloid Plaques in Alzheimer’s Disease

      • Dionysia Papagiannopoulou, Dimitra Hadjipavlou-Litina
      Pages 463-479
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Keywords

About this book

This volume describes different computational methods encompassing ligand-based approaches (QSAR, pharmcophore), structure-based approaches (homology modeling, docking, molecular dynamics simulation), and combined approaches (virtual screening) with applications in anti-Alzheimer drug design. Different background topics like molecular etiologies of Alzheimer’s disease, targets for new drug development, and different cheminformatic modeling strategies are covered for completeness. Special topics like multi-target drug development, natural products, protein misfolding, and nanomaterials are also included in connection with computational modeling of anti-Alzheimer drug development. In Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. 

Cutting-edge and authoritative, Computational Modeling of Drugs Against Alzheimer’s Disease is a valuable resource for learningabout the latest computational techniques used to study this disease. 



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Editors and Affiliations

  • Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

    Kunal Roy

About the editor

Dr. Kunal Roy is a Professor in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India. He has been a recipient of Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Fellowship (University of Manchester, 2013). The field of his research interest is QSAR and Molecular Modeling with application in Drug Design and Ectoxicological Modeling. Dr. Roy has published more than 250 research papers in refereed journals (current SCOPUS h index 35). He has also coauthored two QSAR related books, edited two QSAR books and published ten book chapters. Dr. Roy serves in different capacities in the Editorial Boards of several International Journals.

Bibliographic Information

  • Book Title: Computational Modeling of Drugs Against Alzheimer’s Disease

  • Editors: Kunal Roy

  • Series Title: Neuromethods

  • DOI: https://doi.org/10.1007/978-1-4939-7404-7

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2018

  • Hardcover ISBN: 978-1-4939-7403-0Published: 29 September 2017

  • Softcover ISBN: 978-1-4939-8475-6Published: 10 August 2018

  • eBook ISBN: 978-1-4939-7404-7Published: 27 September 2017

  • Series ISSN: 0893-2336

  • Series E-ISSN: 1940-6045

  • Edition Number: 1

  • Number of Pages: XVII, 645

  • Number of Illustrations: 64 b/w illustrations, 158 illustrations in colour

  • Topics: Neurosciences

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