This reference provides a comprehensive overview of computational modelling and simulation for theoretical and practical biomedical research. The book explains basic concepts of computational biology and data modelling for learners and early career researchers.
Chapters cover these topics:
- An introduction to computational tools in biomedical research
- Computational analysis of biological data
- Algorithm development for computational modelling and simulation
- The roles and application of protein modelling in biomedical research
- Dynamics of biomolecular ligand recognition
- Key features include a simple, easy-to-understand presentation, detailed explanation of important concepts in computational modeling and simulations and references.
Readership:
- Undergraduates and graduates in life sciences, bioinformatics, data science, computer science and biomedical engineering courses. Early career researchers.
Table of Contents
PREFACE- LIST OF CONTRIBUTORS
- DEDICATION
- RESEARCH
- Chong Lee Ng and Yee Siew Choong
- INTRODUCTION
- ROLES OF COMPUTATIONAL TOOLS IN SEQUENCE ALIGNMENT AND
- STRUCTURAL STUDIES
- General Applications of Computational Tools in Sequence and Structural Studies
- Studying the Interactions between Antibody against MDM2 Antigen
- Repurposing Existing Approved Drugs against SARS-CoV2 Proteins
- ROLES OF COMPUTATIONAL TOOLS IN UNDERSTANDING PROTEIN DYNAMICS
- General Applications of Computational Molecular Dynamic Simulation
- Computational Optimization of Antibody Affinity toward Heat Shock Protein
- (HSP16.3) Antigen
- Elucidating the Catalytic Reaction of Isocitrate Lyase in Mycobacterium tuberculosis
- ROLES OF COMPUTATIONAL TOOLS IN CELLULAR ACTIVITY AND SYSTEM
- BIOLOGY
- Application of Computational Tools in Predictions of Cellular Activity and System Biology
- Changes in p53 Protein Expression Affects the Cellular Apoptosis
- Computational Pharmacokinetic Prediction of Anticancer Phytocompounds
- CONCLUDING REMARKS
- ACKNOWLEDGEMENT
- REFERENCES
- Lilach Soreq and Wael Mohamed
- INTRODUCTION
- GENOMIC DATA ANALYSIS
- Genetic Analyses of Expression Data
- Circular RNAs
- RNA Interference
- BDNF
- Public Database for Genomics Data
- BIG DATA IN LIFE SCIENCE
- Use of Disease Mice Model as a Comparative Model
- DIRECT ADMINISTRATION OF SIRNA FOR THERAPEUTICS
- Huntington’s Disease (HD)
- Amyotrophic Lateral Sclerosis (ALS) Disease
- CRISPR Gene Therapy
- Human iPSC-Derived Sensory Neurons
- NOVEL CLASSES OF NON-CODING RNAS
- DEEP BRAIN STIMULATION (DBS) AND PARKINSON’S DISEASE (PD)
- APPLICATIONS OF RNA INTERFERENCE-BASED THERAPEUTICS
- Antisense-Based Therapeutics
- Multiple Sclerosis
- Post-traumatic Stress Disorder (PTSD)
- CONCLUSION AND PERSPECTIVES
- FUNDING
- REFERENCES
- SIMULATION
- Nordina Syamira Mahamad Shabudin and Ahmad Naqib Shuid
- INTRODUCTION
- Computational Tertiary Structure Prediction Protocol
- Free Modelling Approach for Tertiary Protein Structure Prediction
- Bhageerath-H
- RaptorX-Contact
- Template-Based Tertiary Protein Structure Modelling
- Threading
- NDThreader
- Homology Modeling
- IntFOLD6-TS
- Protein Structure Refinement
- Molecular Dynamic Simulation for Protein Refinement
- Refinement programs Link/Address
- Molecular Dynamic Approaches for Protein Refinement
- Quality Assessment of Predicted Tertiary Protein Structure
- The Single-Model Based Quality Assessment Approach - ProQ2
- The Cluster-Based Quality Assessment Approach
- The Quasi-single Model Quality Assessment Approach
- The Artificial Neural Network (ANN) and Deep Learning-Based Model Quality
- Assessment - ModFOLD8
- Deoxyribonucleic Acid Sequencing
- The Cluster-Based Quality Assessment Approach
- Hashed-Based Genome Mapping
- The Suffix-Tree Approach
- Burrow-Wheeler Transform Approach
- The Fast Fourier Transform Approach
- The Approximate Matching Approach
- The Smith-Waterman and Needleman-Wunsch Approach
- The Coevolutionary Neural Network (CNN) Approach
- The Mechanism of Docking Protocol
- The Search Algorithm
- The Rigid Body Docking and Flexible-ligand Docking Body
- The Systematic Search Algorithm
- The Exhaustive Search Algorithm
- The Fragment-Based Algorithm
- The Incremental Algorithm
- The Distance Geometry
- The Fast Shape Matching
- The Stochastic or Random Search Methods
- Monte-Carlo Simulation
- The Genetic Algorithm
- The Tabu Search Algorithm
- The Molecular Dynamic Simulation Approaches
- The Scoring Function
- The Force Field-Based Scoring
- The Empirical Scoring
- The Knowledge-based scoring
- The Consensus-Based Scoring
- CONCLUSION
- FUNDING
- REFERENCES
- BIOMEDICAL RESEARCH
- Chong Lee Ng, Tze Yin Lee, Nur Naili Irsyada Binti Zulkfli, Theam Soon Lim and Yee
- Siew Choong
- INTRODUCTION
- THE EFFECTS OF PROTEIN MUTATION
- PROTEIN STRUCTURE DETERMINATION BY EXPERIMENTAL METHODS
- Protein Sequencing
- X-ray Crystallography
- Nuclear Magnetic Resonance (NMR) Spectroscopy
- Cryogenic-Electron Microscopy (Cryo-EM)
- Advantages and Limitations in Protein Structure Determination by Experimental Methods
- The advantages and Limitations of X-ray Crystallography
- The advantages and limitations of NMR spectroscopy
- The advantages and limitations of cryo-EM
- COMPUTATIONAL METHODS IN PROTEIN STRUCTURE PREDICTION
- Ab Initio Method
- Comparative Modeling
- Threading Method
- Limitations in Protein Structure Determination by Computational Methods
- APPLICATIONS OF PROTEIN MODELING IN BIOMEDICAL RESEARCH
- Screening of Phytochemicals as Anti-Viral Agents against NSP1 Protein in SARS-CoV-2
- Investigating the Interactions between DNA-Binding Motif of Transcription Factors and DNA
- Optimization of the Binding Affinity of Antibody toward Heat Shock Protein
- Studying the Interactions between S-Protein Variants from SARS-CoV-2 and Human
- Angiotensin-Converting Enzyme (hACE2)
- CONCLUDING REMARKS
- ACKNOWLEDGEMENT
- REFERENCES
- Ilija Cvijetić, Dušan Petrović and Mire Zloh
- INTRODUCTION
- PHARMACOPHORE MODELING
- Dynamic Pharmacophores
- MOLECULAR DOCKING
- MOLECULAR DYNAMICS WITH ENHANCED SAMPLING
- PERSPECTIVES
- CONCLUSION
- ACKNOWLEDGEMENT
- REFERENCES
- SUBJECT INDEX