Computational Drug Discovery and Design
Methods and Protocols
(Sprache: Englisch)
This Methods in Molecular Biology(TM) volume offers protocols for investigating biomedical applications for drug developments based on computational chemistry. Includes step-by-step, readily reproducible computational protocols, and key tips on troubleshooting.
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Produktinformationen zu „Computational Drug Discovery and Design “
This Methods in Molecular Biology(TM) volume offers protocols for investigating biomedical applications for drug developments based on computational chemistry. Includes step-by-step, readily reproducible computational protocols, and key tips on troubleshooting.
Klappentext zu „Computational Drug Discovery and Design “
Due to the rapid and steady growth of available low-cost computer power, the use of computers for discovering and designing new drugs is becoming a central topic in modern molecular biology and medicinal chemistry. In Computational Drug Discovery and Design: Methods and Protocols expert researchers in the field provide key techniques to investigate biomedical applications for drug developments based on computational chemistry. These include methods and techniques from binding sites prediction to the accurate inclusion of solvent and entropic effects, from high-throughput screening of large compound databases to the expanding area of protein-protein inhibition, toward quantitative free-energy approaches in ensemble-based drug design using distributed computing. Written in the highly successful Methods in Molecular Biology¿ series format, chapters include introductions to their respective topics, reference to software and open source analysis tools, step-by-step, readily reproducible computational protocols, and key tips on troubleshooting and avoiding known pitfalls. Thorough and intuitive, Computational Drug Discovery and Design: Methods and Protocols aids scientists in the continuing study of state-of-the-art concepts and computer-based methodologies.
Inhaltsverzeichnis zu „Computational Drug Discovery and Design “
Part I: Drug Binding Site Prediction, Design, and Descriptors1. A Molecular Dynamics Ensemble-based Approach for the Mapping of Druggable Binding SitesAnthony Ivetac and J, Andrew McCammon2. Analysis of Protein Binding Sites by Computational Solvent Mapping David R. Hall, Dima Kozakov, and Sandor Vajda3. Evolutionary Trace for Prediction and Redesign of Protein Functional Sites Angela Wilkins, Serkan Erdin, Rhonald Lua, and Olivier Lichtarge4. Information Entropic Function for Molecular Descriptor Profiling Anne Mai Wasswrmann, Britta Nisius, Martin Vogt, and Jürgen BajorathPart II: Virtual Screening of Large Compound Libraries: Including Molecular Flexibility5. Expanding the Conformational Selection Paradigm in Protein-Ligand DockingGuray Kuzu, Ozlem Keskin, Attila Gursoy, and Ruth Nussinov6. Flexibility Analysis of Biomacromolecules with Application to Computer-aided Drug DesignSimone Fulle and Holger Gohlke7.On the Use of Molecular Dynamics Receptor Conformations for Virtual ScreeningSara Nichols, Riccardo Baron, and J. Andrew McCammon8. Virtual Ligand Screening Against Comparative Protein Structure ModelsHao Fan, John J. Irwin, and Andrej Sali9.AMMOS Software: Method and ApplicationTania Pencheva, David Lagorce, Ilza Pajeva, Bruno O. Villoutreix, and Maria A. Miteva10.Rosetta Ligand Docking with Flexible XML ProtocolsGordon Lemmon and Jens Meiler11.Normal Mode-Based Approaches in Receptor Ensemble DockingClaudio N. Cavasotto12. Application of Conformational Clustering in Protein-Ligand DockingGiovanni Bottegoni, Walter Rocchia, and Andrea Cavalli13. How to Benchmark Methods for Structure-based Virtual Screenin of Large Compound LibrariesAndrew J. Christofferson and Niu HuangPart III: Prediction of Protein-Protein Docking and Interactions14. AGGRESCAN: Method, Application, and Perspectives for Drug DesignNatalia S. de Groot, Virginia Castillo, Ricardo Graña, and Salvador Ventura Zamora 15. ATTRACT and PTOOLS: Open Source Programs for Protein-protein
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DockingSebastian Schneider, Adrien Saladin, Chantal Prevost, and Martin Zacharias 16. Prediction of Interacting Protein Residues using Sequence and Structure DataVedran Franke, Mile Sikic, and Kristian VlahovicekPart IV: Rescoring Docking Predictions17. MM-GB/SA Rescoring of Docking PosesCristiano R.W. Guimarães 18. A Case Study of Scoring and Rescoring in Peptide DockingZunnan Huang and Chung Wong19. The Solvated Interaction Energy (SIE) Method for Scoring Binding Affinities Traian Sulea and Enrico Purisima 20. Linear Interaction Energy (LIE): Method and Applications in Drug Design Hugo Guitiérrez-de-Terán and Johan ÅqvistPart V: Crucial Neglected Effects: Entropy, Solvent, and Protonation21. Estimation of Conformational Entropy in Protein-Ligand Interactions: A Computational PrespectiveAnton Polyansky, Ruben Zubac, and Bojan Zagrovic 22. Explicit Treatment of Water Molecules in Data-driven Protein-protein Docking: The Solvated HADDOCKing ApproachPanagotis L. Kastritis, Aalt D.J. van Dijk, and Alexandre M.J.J. Bonvin 23. Protein¿water Interactions in MD Simulations: POPS/POPSCOMP Solvent Accessibility Analysis, Solvation Forces and Hydration SitesArianna Fornili, Flavia Autore, Nesrine Chakroun, Pierre Martinez, and Franca Fraternali 24. Computing the Thermodynamic Contributions of Interfacial WaterZheng Li and Themis Lazaridis 25. Assignment of Protonation States in Proteins and Ligands: Combining pKa Prediction with Hydrogen Bonding Network OptimizationElmar Krieger, Rob Hooft, Roland Dunbrack, and Barbara KriegerPart VI: Toward the Use of Robust Free Energy Methods in Drug Design 26. Best Practices in Free Energy Calculations for Drug DesignMichael Shirts 27. Independent-Trajectory Thermodynamic Integration:A Practical Guide to Protein-Drug Binding FreeEnergy Calculations Using Distributed ComputingMorgan Lawrenz, Riccardo Baron, Yi Wang, and J. Andrew McCammon 28. Free Energy Calculations from One-step PerturbationsChris Oostenbrink 29. Using Metadynamics and Path Collective Variables to Study Ligand Binding and Induced Conformational TransitionsNeva Beker and Francesco L. Gervasio 30. Accelerated Molecular Dynamics In Computational Drug DesignJeff Wereszczynski and J. Andrew McCammonPart VII: Biomedical Applications31. Molecular Dynamics Applied in Drug Discovery: the Case of HIV-1 ProteaseYi Shang and Carlos Simmerling 32. Decomposing the Energetic Impact of Drug-Resistant Mutations: The Example of HIV-1 Protease-DRV BindingYufeng Cai and Celia Schiffer 33. Virtual Screening Helps Experiment Design: Application to the Akt Phosphatase PHLPPBill Sinko, Emma Sierecki, Cesar A.F. de Oliveira, and J. Andrew McCammon 34. Molecular-Level Simulation of Pandemic Influenza GlycoproteinsRommie Amaro and Wilfred W. Li 35. Homology Modeling of Cannabinoid Receptor: Discovery of Cannabinoid Analogues for Therapeutic UseChia-en Chang, Rizi Ai, Michael Gutierrez, and Michael J. Marsella 36. High-throughput Virtual Screening Lead to Discovery of Non-peptidic Inhibitors of West Nile Virus NS3 ProteaseDanzhi Huang
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Bibliographische Angaben
- 2011, XVII, 628 Seiten, Masse: 18,3 x 26 cm, Gebunden, Englisch
- Herausgegeben: Riccardo Baron
- Verlag: Springer, Berlin
- ISBN-10: 1617794643
- ISBN-13: 9781617794643
- Erscheinungsdatum: 21.12.2011
Sprache:
Englisch
Rezension zu „Computational Drug Discovery and Design “
From the reviews:"Given that computational drug design is a rapidly expanding area of research, this book fills a niche that makes it useful for both novices and the more experienced in the field. ... this is a practical manual, refitted with many protocols and examples, of how to employ the new techniques being developed by experts in the expanding field of computational drug discovery." (Jed N. Lampe, Doody's Book Reviews, July, 2012)
Pressezitat
From the reviews:"Given that computational drug design is a rapidly expanding area of research, this book fills a niche that makes it useful for both novices and the more experienced in the field. ... this is a practical manual, refitted with many protocols and examples, of how to employ the new techniques being developed by experts in the expanding field of computational drug discovery." (Jed N. Lampe, Doody's Book Reviews, July, 2012)
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