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