Quick Guideline for Computational Drug Design - Sheikh Arslan Sehgal - E-Book

Quick Guideline for Computational Drug Design E-Book

Sheikh Arslan Sehgal

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Beschreibung

Bioinformatics allows researchers to answer biological questions with advanced computational methods which involves the application of statistics and mathematical modeling. Structural bioinformatics enables the prediction and analysis of 3D structures of

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Seitenzahl: 123

Veröffentlichungsjahr: 2018

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Table of Contents
Welcome
Table of Contents
Title
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
Usage Rules:
Disclaimer:
Limitation of Liability:
General:
FOREWORD
PREFACE
Introduction to Structural Bioinformatics
Abstract
Motivation
BIOINFORMATICS
Bioinformatics Approaches
Static
Dynamic
Structural Bioinformatics
Software and Tools
Open-Source Bioinformatics Software
Web Services in Bioinformatics
Homology Modeling
Steps of Homology Modeling
Template Selection
Target-Template Alignment
Model Construction
Model Assessment (Validation)
Accuracy
Importance of Homology Modeling
Homology Modeling Tools
Sequence Retrieval
UniProtKB
Characterization of Homology Modeling Tools
Structure Prediction Tools
Model Validation Tools
Sequence Analysis Tools
Model Visualization Tools
Virtual Screening and Docking
REFERENCES
Protein Primary Sequence Analysis
Abstract
Motivation
ProtParam Expasy
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Results Interpretation
Conclusion
Limitations of Primary Sequence Analyses
ProtParam Expassy
REFERENCES
Secondary Structure Analyses
Abstract
Motivation
Secondary Structure of Proteins
ProFunc
Brief Instructions
Requirements
Input
Sequence Submission
Accessing of Data
Limitations of Secondary Structure Analyses Tools
ProFunc
REFERENCES
3D Structure Prediction
Abstract
Motivation
Structure Prediction Tools
Phyre2
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Results Interpretation (Results Screen)
Secondary Structure and Disorder Prediction
Domain Analysis
Detailed Template Information
Alignment View
Conclusion
I-TASSER
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation (Output)
Structure Prediction
Top 10 Threading Templates Used by I-TASSER
Top 5 Final Model Predicted by I-TASSER
Structurally Closely Related Protein
Protein Function
Ligand Binding Site
Conclusion
RaptorX
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation (Output)
Input Sequence and Domain Partition
Prediction Results
Detailed Prediction Results
SWISS-MODEL
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation (Results Screen)
Summary
Templates
Models
Conclusion
3D-JIGSAW
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation
Conclusion
IntFOLD2
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation (Output)
Conclusion
HHpred
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation (Output)
Conclusion
M4t
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation (Output)
Conclusion
MODELLER
Introduction
Downloading and Installation
Modeling Steps
Searching for Structures Related to RASSF2
BLAST (Basic Local Alignment Searching Tool)
Template PDB File
Aligning RASSF2 with the Template
Model Building
Limitations of Structure Prediction Tools
Phyre2
I-TASSER
RaptorX
SWISS-MODEL
3D-JIGSAW
IntFOLD2
M4t
MODELLER
REFERENCES
Structure Evaluation
Abstract
Motivation
Model Evaluation Tools
ERRAT
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Results Interpretation (Output)
Conclusion
RAMPAGE
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Results Interpretation
Conclusion
ANOLEA
Introduction
Brief Instructions
Requirements
Input
Results Interpretation
Conclusion
MOL PROBITY
Introduction
Brief Instructions
Requirements
Input
Results Interpretation
Conclusion
VERIFY 3D
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Results Interpretation
Conclusion
PDBsum GENERATE
Introduction
Brief Instructions
Requirements
Input
Sequence Submission
Accessing Data
Results Interpretation
Output
Customization of Plots
Conclusion (Procheck Summary)
RAMACHANDRAN PLOT
Chi-1 Dihedral Angle
Chi-2 Dihedral Angle
All Ramachandrans
Main Chain Parameters
Side Chain Parameters
Main Chain Bond Lengths
Main Chain Bond Angles
Planar Groups
Limitations of Structure Evaluation Tools
ERRAT
RAMPAGE
Verify3D
PDBsum
REFERENCES
Visualization of Predicted Structure
Abstract
Motivation
UCSF Chimera
Introduction
Brief Instructions
Visualization Through Different Options
File Option
Saving the Session Status
Saving Image
Select Option
Structure
Residue
Chemistry
Action
Atoms/Bonds
Ribbon
Showing Surface
Coloring the Secondary Structure Elements
Label Residue
Presets Option
Tools Option
Sequence
Light Adjustment
Interacting Residues Analyses
Energy Minimization
Limitations of Structure Visualization Tools
UCSF Chimera
REFERENCES
Molecular Docking Studies
Abstract
Motivation
Molecular Docking Analyses
AutoDock
AutoDock Applications
AutoDock 4
Requirements
Input
Preparing the Protein
Add Hydrogen’s
Hide Protein
Preparing the Ligand
Opening File
Define Torsions
Save Ligand File
Hide the Ligand
Running AutoGrid Calculation
Open the Protein
Prepare Grid Parameter File
Set Grid Properties
Save the Grid Settings
Preparing the Docking Parameter File (.dpf)
Specifying the Molecule
Specifying the Ligand
Choosing Docking Method
Setting Docking Parameters
Running AutoDock4
Running
Docking Results
AutoDock Vina
Introduction
Getting Started With AutoDock Vina
Protein Preparation
Ligand Preparation
Preparation of PDBqt of Protein
AutoDock Vina for Linux
AutoDock Vina for Windows
GOLD
Introduction
Getting Started with GOLD
Results Interpretation
Limitations of Docking Tools
AutoDock 4
AutoDock Vina
GOLD
REFERENCES

Quick Guideline for Computational Drug Desig

Authors
Sheikh Arslan Sehgal
Department of Biosciences,
COMSATS Institute of Information Technology,
Sahiwal, Pakistan State Key Laboratory of Membrane Biology,
Institute of Zoology; Chinese Academy of Sciences,
Beijing, China University of Chinese Academy of Sciences,
Beijing, China
 Rana Adnan Tahir
Department of Biosciences,
COMSATS Institute of Information Technology,
Sahiwal, Pakistan Beijing Key Laboratory of Separation and Analysis in Biomedical and Pharmaceuticals,
Department of Biomedical Engineering, School of Life Sciences,
Beijing Institute of Technology, China 
A. Hammad Mirza
University of Chinese Academy of Sciences,
Beijing, China National Laboratory of Biomacromolecules,
Institute of Biophysics, Chinese Academy of Sciences,
Beijing, China 
Asif Mir
Department of Bioinformatics and Biotechnology,
International Islamic University,
Islamabad, Pakistan

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FOREWORD

Bioinformatics is an interdisciplinary field which has played central role in the integration of computational techniques to solve biological problems. Computational methods have long been practiced in biology and perhaps, Fibonacci series was the most remarkable historical breakthrough in which Fibonacci used mathematical model for biological systems. Another exemplary work was performed by Gregor Mendel, who identified biological pattern of inheritance by devising Punnett square model for alleles of genes. Mathematical model integration was then continued by Thomas Hunt Morgan and later by his student who managed to group genes locus wise on chromosomes of Drosophila Melanogaster. Population geneticists used allelic frequency model to calculate frequency of most prevalent alleles in a population. With the sequencing of protein amino acids and DNA nucleotides, a new era of mathematical expansion in biology started. Margaret Dayhoff in 1978 designed Point Accepted Mutation (PAM) matrices to find out replacements of amino acids in primary structure of protein through the process of Natural Selection. Smith-Waterman and Needleman-Wunsch algorithms are key algorithms in alignment of gene sequences. In 1992, Henikoff and Henikoff presented Blossum matrix scoring function for protein alignment. Together, these alignment algorithms have currently become basics or starting point of most of the biological experiments. The alignment algorithms have helped us to discover not only mutational differences between sequences of genes but also these algorithms have been implemented to draw evolutionary relationships between living organisms. Martin Karplus, Michael Lavitt, and Arieh Warshel jointly shared 2013 Noble Prize for successful implementation of Mathematical simulation models to biological systems. They started a new era of Structural Biology that tends to find out 3-D structures of Biomolecules and their interactions with each other computationally. The accuracy of simulations is more than 90% that makes it a favorable choice of experiment when X-ray crystallography or NMR data is not available. Molecular docking is another technique that is employed to find out interactions between two biomolecules (preferably Protein-Protein Interactions or Protein-small molecule interactions) with minimum free energy state. Molecular docking has started new era of Computational Biology called Computer Aided Drug Design to design drugs against fatal diseases in exponentially less time.

“Far too many diseases do not have proven preventions or treatments. To make a difference for the millions of Americans who suffer from these diseases, we must gain better insights into the biological, environmental and behavioral factors that drive these diseases. Precision medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in environment, lifestyle and genes for each person.” (On January 20, 2015, President Obama announced the Precision Medicine Initiative® – PMI).

This era belongs to Personalized Medicine or Precision Medicine which collectively integrates all the Bioinformatics methods and analyses techniques including DNA sequences, family history, medical history, and environment to design individual specific medicines that will surely revolutionize lifestyles, lifespan, and thus Medical Science to its new heights. As Bioinformatics methods and techniques are now considered as basic requirements for most of biological experiments, this book will help researchers to have an idea of how to initialize, design and add new layers of knowledge. This book does not cover all, but most of the major domains and utilizes most cited and most used tools and techniques. The material of book has been designed for novices to take them up to pro level in Bioinformatics. Many small tricks have also been discussed that would help researchers to easily understand theory, perform experiment, and analyze results. As a matter of fact, it is believed that this book must be part of every laboratory that needs Bioinformatics analyses for their experiments.

Muhammad Ismail, PhD Director, Institute of Biomedical and Genetic Engineering (IBGE) Islamabad, Pakistan

PREFACE