Structural Bioinformatics: Methods and Protocols (Methods in Molecular Biology, 2112)

✍ Scribed by Zoltán Gáspári (editor)

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 265
• Category: Library

✦ Synopsis

This volume looks at the latest techniques used to perform comparative structure analyses, and predict and evaluate protein-ligand interactions. The chapters in this book cover tools and servers such as LiteMol; Bio3D-Web; DALI; CATH; HoTMuSiC, a contact-base protein structure analysis tool known as CAD-Score; PyDockSaxs and HADDOCK; CombDock and DockStar; the BioMagResBank database; as well as BME and CoNSEnsX+. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls.
Cutting-edge and comprehensive, Structural Bioinformatics: Methods and Protocols is a practical guide for researchers to learn more about the aforementioned tools to further enhance their studies in the growing field of structural bioinformatics.
Chapter 13 isavailable open access under a CC-BY 4.0 license via link.springer.com.

✦ Table of Contents

Preface
Contents
Contributors
Chapter 1: Visualization and Analysis of Protein Structures with LiteMol Suite
1 Introduction
2 Materials
2.1 Implementation of LiteMol Suite
3 Methods
3.1 Visualization of Annotations
3.1.1 Annotation of Structure Quality
Visualization of Annotations from VR
Visualization of Annotations from LVR
3.1.2 Sequence Annotation
3.1.3 Annotations of Carbohydrates
3.2 Selection Functionality in the User Interface
3.3 Visualization of Large Structures by Distance-Based Coloring
3.4 CoordinateServer and Its Selection Functionality
3.5 Using DensityServer to Explore Electron Density Data
4 Example Application: Step-by-Step Visual Analysis of Carbohydrate-Binding Protein
5 Notes
References
Chapter 2: Comparative Protein Structure Analysis with Bio3D-Web
1 Introduction
2 Materials
3 Methods
3.1 Overview
3.2 Example Application to Ribose-Binding Protein
3.2.1 SEARCH: Structure Search and Selection
3.2.2 ALIGN: Sequence Alignment and Analysis
3.2.3 FIT: Structure Superposition and Analysis
3.2.4 PCA: Principal Component Analysis
3.2.5 eNMA: Ensemble Normal Mode Analysis
3.2.6 Summary Report Generation
3.3 Conclusion
4 Notes
References
Chapter 3: Using Dali for Protein Structure Comparison
1 Introduction
2 Materials
3 Methods
3.1 Input File
3.2 Structure Data Parsing
3.3 Pairwise Comparison
3.4 Web Server Methods
3.5 Interpretation of the Result
3.6 Dali Comparison with the Locally Installed Standalone Version
4 Notes
References
Chapter 4: Assessing Protein Function Through Structural Similarities with CATH
1 Introduction
2 Methods and Materials for Accessing CATH Data
2.1 The CATH Hierarchy
2.2 The CATH Web Interface
2.2.1 Using a Text Search to Find a Protein in CATH
2.2.2 Using a Structure-Based Search to Identify Related Proteins
2.2.3 Using a Sequence-Based Search to Identify Related Proteins
2.2.4 Homologous Superfamily Data
2.3 Downloading CATH Data
3 Example Applications of the CATH Platform
3.1 Browsing the CATH Classification Hierarchy
3.2 Identifying Structural Relatives of the Protein Atg101
3.3 Functional Analysis of Guanylate Kinase-Like Proteins
4 Concluding Remarks
References
Chapter 5: Protein Thermal Stability Engineering Using HoTMuSiC
1 Introduction
2 HoTMuSiC Key Instrument: The Statistical Potentials
3 HoTMuSiC Harmony: The Artificial Neural Networks
4 HoTMuSiC Sound: The Results
4.1 Performances
4.2 Webserver
4.3 Application to Modeled Structures
4.4 Protein Design with HoTMuSiC Pipeline
4.5 HoTMuSiC-Based Pipeline Applied to Rhizomucor Miehei Lipase
5 Conclusion
References
Chapter 6: Contact Area-Based Structural Analysis of Proteins and Their Complexes Using CAD-Score
1 Introduction
2 CAD-Score Definition
2.1 Contacts
2.2 Structure Scores
2.3 Scores for Interfaces
2.4 CAD-Score Web Server
2.5 Standalone CAD-Score Software
3 CAD-Score Usage
3.1 Installation
3.2 Global Scoring of 3D Structures
3.3 Using Query Codes
3.4 Caching and Reusing Contacts
3.5 Tolerating Non-matching Sequences
3.6 Focused Scoring
3.7 Scoring of Interfaces and Binding Sites
3.8 Evaluation of Homo-Oligomeric Models
3.9 Residue-Level Local Scoring
3.10 Detailed Analysis of Contacts
4 Notes
References
Chapter 7: A Comprehensive Computational Platform to Guide Drug Development Using Graph-Based Signature Methods
1 Introduction
2 Materials
3 Methods
3.1 Performing Automated Docking with EasyVS
3.2 Predicting Protein-Small Molecule Affinity with CSM-lig
3.3 Depicting and Analyzing Protein-Small Molecule Interactions with Arpeggio
3.4 Predicting the Effects of Mutations on Small Molecule Affinity with mCSM-lig
4 Notes
References
Chapter 8: Systematic Exploration of Binding Modes of Ligands on Drug Targets
1 Introduction
2 Materials
2.1 Preparation of Target and Ligand Molecules
2.2 Wrapper
3 Methods
3.1 Overview
3.2 Input Files
3.3 Pre-wrapper.sh
3.4 Wrapper.sh and wrp
3.5 Output, Benchmark
4 Notes
References
Chapter 9: Using MemBlob to Analyze Transmembrane Regions Based on Cryo-EM Maps
1 Introduction
2 Methods
2.1 Input Files for MemBlob
2.2 Overview of the MemBlob Method
2.3 The MemBlob Web Server
2.4 The MemBlob Database
3 Using MemBlob to Identify the TM Region in the Slo2.2 K+-Channel
4 Notes
References
Chapter 10: Structural Characterization of Protein-Protein Interactions with pyDockSAXS
1 Introduction
2 Materials
3 Methods
3.1 Input Files
3.1.1 Default Mode
3.1.2 Advanced Mode
3.2 Using the pyDockSAXS Protocol Web Server
3.2.1 Chain Selection
3.2.2 CRYSOL Parameters Selection
3.2.3 Data Submission
3.3 Results Page
3.4 Output Files
4 Discussion
5 Notes
References
Chapter 11: Protein-Protein Modeling Using Cryo-EM Restraints
1 Introduction
2 Overview
2.1 High-Resolution Atomic Structure Rigid-Body Fitting into Cryo-EM Densities
2.2 Cryo-EM Density Map Cropping
2.3 Protein-Protein HADDOCKing with EM Restraints
2.3.1 Docking Protocol
Rigid-Body Energy Minimization (RBEM, it0)
Semiflexible Simulated Annealing in Torsion Angle Space (TAD/SA, it1)
Restrained Molecular Dynamics in Explicit Solvent (Water)
Scoring
2.3.2 Clustering of Final Solutions
3 Methods
3.1 Preprocessing of the Cryo-EM Map
3.2 Getting Centroid Coordinates by Fitting the Atomic Structure into the New Cryo-EM Map
3.3 Preparation of Input Files
3.4 Docking Two Subunits of the 30S Ribosome with the HADDOCK2.4 Web Server
4 Notes
References
Chapter 12: Modeling of Multimolecular Complexes
1 Introduction
2 Materials
2.1 Software
3 Methods
3.1 Macromolecular Assembly with CombDock
3.1.1 Inputs
3.1.2 All Pairs Docking with PatchDock
3.1.3 Running CombDock
3.1.4 CombDock Output
3.2 Macromolecular Assembly with DockStar
3.2.1 Inputs
3.2.2 Input Pose Generation
3.2.3 Running DockStar
3.2.4 DockStar Output
3.2.5 The TRiC/CCT Example
4 Conclusions
5 Notes
References
Chapter 13: Biological Assembly Comparison with VAST+
1 Introduction
2 Methods
2.1 Clustering by Rotation Matrix Distance
2.2 Refined Alignment
3 Examples
4 Summary
References
Chapter 14: BioMagResBank (BMRB) as a Resource for Structural Biology
1 Introduction
2 Resources
3 Methods
3.1 Data Deposition
3.1.1 PDB OneDep
Entering NMR Data into the Deposition Interface
3.1.2 ADIT-NMR and BMRBdep
Step 1: Preparation for Data Deposition
The BMRB Template Generator
Step 2: Creation of an BMRBdep Session
Step 3: Upload of Deposition Data Files
Step 4: Entering Relevant Data
Step 5: Previewing and Depositing the Entry
Step 6: Receiving a Report from BMRB/PDB
Step 7: Hold and Release of the Entry
3.1.3 PDBj-BMRB SMSDep
3.2 Data Retrieval
3.2.1 Instant Search
3.2.2 Advanced Search
3.2.3 BMRB Query Grid
Cautionary Notes
The NMR Restraints Grid
3.2.4 Data Download
3.3 Data Analysis
3.3.1 Data Conversion
The STARch File Converter
3.3.2 Validation
3.3.3 CS-Rosetta High-Throughput Structure Estimation
3.3.4 Working with NMR-STAR Files
Using the NMR-STAR Interactive Viewer
3.4 Programming Tools
3.4.1 BMRB API
3.4.2 PyNMR-STAR: NMR-STAR Handling Python Programming Library
3.4.3 PyBMRB and RBMRB: Data Retrieval and Visualization Libraries for Python and R
Jupyter Notebooks
References
Chapter 15: Integrating Molecular Simulation and Experimental Data: A Bayesian/Maximum Entropy Reweighting Approach
1 Introduction
2 Theoretical Background
3 Toy Model
4 BME Software
4.1 Requirements, Download and Installation
4.2 Combining NMR Data with MD Simulation of RNA
4.3 Combining SAXS Data with Simulation of Proteins
5 Notes
References
Chapter 16: Evaluation and Selection of Dynamic Protein Structural Ensembles with CoNSEnsX+
1 Introduction
2 Materials
2.1 The CoNSEnsX+ Web Server
2.2 CoNSEnsX+ on GitHub
3 Methods
3.1 Preparation of Input Files
3.2 Brief Overview of Calculating NMR Parameters from the Structures in the Ensemble Submitted
3.3 Output of the CoNSEnsX+ Server for Ensemble Evaluation
3.4 Using the Selection Feature of CoNSEnsX+
3.5 BME Support in CoNSEnsX+
4 Example Application
5 Notes
References
Index