Protein structure prediction
著者
書誌事項
Protein structure prediction
（Methods in molecular biology / John M. Walker, series editor, 2165）（Springer protocols）
Humana Press, c2020
4th ed
- : [hardback]
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This thorough new edition explores web servers and software for protein structure prediction and modeling that are freely available to the academic community. Taking into account the numerous advances in the computational protein structure prediction/modeling field, the book includes residue-contact prediction via deep learning, a wide variety of protein docking models, as well as cryo-electron microscopy (cryo-EM) techniques. Written by renowned experts in the field and for the highly successful Methods in Molecular Biology series, chapters include the kind of key detail and implementation advice necessary for researchers to achieve optimal results in their own work.
Authoritative and fully updated, Protein Structure Prediction, Fourth Edition is a practical and immediately useful guide for biology researchers working toward modeling protein structures.
目次
1. Structural Modeling and Ligand Binding Prediction for Analysis of Structure-Unknown and Function-Unknown Proteins Using FORTE Alignment and PoSSuM Pocket Search
Yuko Tsuchiya and Kentaro Tomii
2. The MULTICOM Protein Structure Prediction Server Empowered by Deep Learning and Contact Distance Prediction
Jie Hou, Tianqi Wu, Zhiye Guo, Farhan Quadir, and Jianlin Cheng
3. The Genome3D Consortium for Structural Annotations of Selected Model Organisms
Vaishali P. Waman, Tom L. Blundell, Daniel Buchan, Julian Gough, David Jones, Lawrence Kelley, Alexey Murzin, Arun Prasad Pandurangan, Ian Sillitoe, Michael Sternberg, Pedro Torres, and Christine Orengo
4. Estimating the Quality of 3D Protein Models Using the ModFOLD7 Server
Ali H.A. Maghrabi and Liam J. McGuffin
5. Prediction of Intrinsic Disorder with Quality Assessment Using QUARTER
Zhonghua Wu, Gang Hu, Christopher J. Oldfield, and Lukasz Kurgan
6. Modeling of Three-Dimensional RNA Structures Using SimRNA
Tomasz K. Wirecki, Chandran Nithin, Sunandan Mukherjee, Janusz M. Bujnicki, and Michal J. Boniecki
7. Modeling Protein Homo-Oligomer Structures with GalaxyHomomer Web Server
Minkyung Baek, Taeyong Park, Lim Heo, and Chaok Seok
8. Template-Based Modeling of Protein Complexes Using the PPI3D Web Server
Justas Dapkunas and Ceslovas Venclovas
9. Protein-Protein and Protein-Peptide Docking with ClusPro Server
Andrey Alekseenko, Mikhail Ignatov, George Jones, Maria Sabitova, and Dima Kozakov
10. Modeling of Protein Complexes and Molecular Assemblies with pyDock
Mireia Rosell, Luis Angel Rodriguez-Lumbreras, and Juan Fernandez-Recio
11. A Guide for Protein-Protein Docking Using SwarmDock
Iain H. Moal, Raphael A.G. Chaleil, Mieczyslaw Torchala, and Paul A. Bates
12. Modeling Protein-Protein or Protein-DNA/RNA Complexes Using the HDOCK Webserver
Yumeng Yan and Sheng-You Huang
13. IDP-LZerD: Software for Modeling Disordered Protein Interactions
Charles Christoffer and Daisuke Kihara
14. AnAnaS: Software for Analytical Analysis of Symmetries in Protein Structures
Guillaume Pages and Sergei Grudinin
15. MDockPeP: A Webserver for Blind Prediction of Protein-Peptide Complex Structures
Xianjin Xu and Xiaoqin Zou
16. Protocols for All-Atom Reconstruction and High-Resolution Refinement of Protein-Peptide Complex Structures
Aleksandra Badaczewska-Dawid, Alisa Khramushin, Andrzej Kolinski, Ora Schueler-Furman, and Sebastian Kmiecik
17. DOCKGROUND Tool for Development and Benchmarking of Protein Docking Procedures
Petras J. Kundrotas, Ian Kotthoff, Sherman W. Choi, Matthew M. Copeland, and Ilya A. Vakser
18. Molecular Dynamics Flexible Fitting: All You Want to Know about Resolution Exchange
John W. Vant, Daipayan Sarkar, Chitrak Gupta, Mrinal S. Shekhar, Sumit Mittal, and Abhishek Singharoy
19. Protein Structure Modeling from Cryo-EM Map Using MAINMAST and MAINMAST-GUI Plugin
Genki Terashi, Yuhong Zha, and Daisuke Kihara
20. Protocols for Fast Simulations of Protein Structure Flexibility Using CABS-Flex and SURPASS
Aleksandra Badaczewska-Dawid, Andrzej Kolinski, and Sebastian Kmiecik
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