-
Browse Book Series
- Adhesion and Adhesives: Fundamental and Applied Aspects
- Advances in Additive Manufacturing Technologies
- Advances in Antenna, Microwave and Communication Engineering
- Advances in Biofeedstocks and Biofuels
- Advances in Cyber Security
- Advances in Data Engineering and Machine Learning
- Advances in Disease Diagnosis, Drug Delivery and Treatment
- Advances in E-Mobility
- Advances in Hydrogen Production and Storage
- Advances in Intelligent and Scientific Computing (AISC)
- Advances in Learning Analytics for Intelligent Cloud-IoT Systems
- Advances in Membrane Processes
- Advances in Nanotechnology and Applications
- Advances in Natural Gas Engineering
- Advances in Pipes and Pipelines
- Advances in Production Engineering
- Advances in Solar Cell Materials and Storage
- Advances in Surface Engineering and Materials Processing
- Applied Functional Materials
- Artificial Intelligence and Soft Computing for Industrial Transformation
- Astrobiology Perspectives on Life in the Universe
- Bioprocessing in Food Science
- Computational Intelligence and Biomedical Engineering
- Computational Intelligence in Industrial Mathematics
- Concise Introductions to AI and Data Science
- Cyber Systems and Quantum Engineering
- Decentralized Systems and Next-Generation Internet
- Diatoms: Biology and Applications
- Digital Convergence in Engineering Systems
- Emerging Trends in Medicinal and Pharmaceutical Chemistry
- Engineering Systems Design for Sustainable Development
- Fintech in a Sustainable Digital Society
- Human Centric Sustainability and Next Generation Technology
- Industry 5.0 Transformation Applications
- Infectious and Rare Diseases
- Innovations in Materials and Manufacturing
- Leading-Edge Breakthroughs in Artificial Intelligence
- Lifeline Molecules: Exploring Antioxidants and Their Impact
- Machine Learning in Biomedical Science and Healthcare Informatics
- Marine Nanoscience and Nanotechnology
- Materials Degradation and Failure
- Mathematics and Computer Science
- Next-Generation Computing and Communication Engineering
- Performability Engineering Series
- Robotics and Automation for Modern Applications
- Rotating Machinery Fundamentals and Advances
- Semiconductor Devices and Their Applications
- Separation Science
- Studies in Computational Intelligence and Smart Technologies
- Sustainable Biopolymer Technologies and Applications
- Sustainable Computing and Optimization
- Thermoplastic Bionanocomposites Series
- Transformative Innovations in Materials Science
Browse Subject Areas
For Authors
Submit a ProposalNatural Compounds and Alternative Therapies for Hepatitis
One Line Description
Unlock the future of hepatitis-specific drug discovery with this comprehensive, one-stop guide that bridges the gap between natural pharmacology and cutting-edge AI to master phytochemical hepatitis treatment research.
Description
The computational analysis of phytochemicals against hepatitis is an actively evolving field in biomedical and pharmaceutical sciences that resides at the intersection of infectious disease research, natural product pharmacology, and computational biology. This method uses plant-derived compounds for their efficiency against different types of hepatitis, especially viral strains including hepatitis A, B, C, D, and E.
This study represents a perspective change for drug discovery within the framework of disciplinary development, toward both in silico and in vivo methodologies. This book serves as a comprehensive guide to this new strategy for drug formulation. It provides a fundamental understanding of hepatitis and its pathogenesis, as well as the potential of phytochemicals for treatment due to their molecular docking capabilities. The text will further explore recent advances in this innovative field, including the use of pharmacology, machine learning, and artificial intelligence to create new drugs for hepatitis. Using real-world case studies and expert insights into emerging technologies, this guide stands apart as a one-stop reference for the role of phytochemicals in drug development for hepatitis.
Back to Top
The computational analysis of phytochemicals against hepatitis is an actively evolving field in biomedical and pharmaceutical sciences that resides at the intersection of infectious disease research, natural product pharmacology, and computational biology. This method uses plant-derived compounds for their efficiency against different types of hepatitis, especially viral strains including hepatitis A, B, C, D, and E.
This study represents a perspective change for drug discovery within the framework of disciplinary development, toward both in silico and in vivo methodologies. This book serves as a comprehensive guide to this new strategy for drug formulation. It provides a fundamental understanding of hepatitis and its pathogenesis, as well as the potential of phytochemicals for treatment due to their molecular docking capabilities. The text will further explore recent advances in this innovative field, including the use of pharmacology, machine learning, and artificial intelligence to create new drugs for hepatitis. Using real-world case studies and expert insights into emerging technologies, this guide stands apart as a one-stop reference for the role of phytochemicals in drug development for hepatitis.
Back to Top
Author / Editor Details
Subrat Kumar Pattanayak, PhD is part of the faculty in the Department of Chemistry a the National Institute of Technology, Raipur, India. He has published 35 papers in reputed international journals and conferences and 25 book chapters in addition to partiipating in more than 85 symposia. His research interests include understanding the structure, dynamics, and hydrogen bond properties of solvent roles in proteins at different thermodynamic conditions through molecular dynamics simulation and probing the binding efficacy of wild-type and mutant proteins with phytochemicals.
Subrat Kumar Pattanayak, PhD is part of the faculty in the Department of Chemistry a the National Institute of Technology, Raipur, India. He has published 35 papers in reputed international journals and conferences and 25 book chapters in addition to partiipating in more than 85 symposia. His research interests include understanding the structure, dynamics, and hydrogen bond properties of solvent roles in proteins at different thermodynamic conditions through molecular dynamics simulation and probing the binding efficacy of wild-type and mutant proteins with phytochemicals.
Back to Top
Table of Contents
1. Hepatitis: A Comprehensive Overview of Types, Causes, and Treatment Strategies
Avijit Biswal and Maheswata Moharana
1.1 Introduction
1.2 Types of Hepatitis
1.2.1 Viral Hepatitis (Types, Causes, Diagnosis)
1.2.2 Non-Viral Hepatitis (Types, Cause, Diagnosis)
1.2.3 Treatment Strategies of Viral and Non-Viral Hepatitis and Challenges
1.3 Conclusions and Future Perspective
References
2. Molecular Biology of Liver Diseases: Hepatitis B, Hepatitis C, and Hepatitis E Viruses
Swetanshu, Harshita Rana and Pratichi Singh
2.1 Introduction
2.1.1 Virology and Genetic Organization
2.2 Mechanisms of Viral Entry and Intracellular Replication
2.2.1 HBV Entry and Replication
2.2.2 HCV Replication and Entry
2.2.3 HEV Entry and Replication
2.3 Virus–Host Interactions and Immune Evasion
2.3.1 HBV-Host Interactions
2.3.2 HCV–Host Interactions
2.3.3 HEV–Host Interactions
2.4 Host Immune and Molecular Responses
2.4.1 Innate Immune Responses
2.4.2 Adaptive Immune Responses
2.5 Molecular Stress Responses and Pathology
2.6 Fibrosis and Hepatocellular Carcinoma
2.6.1 HBV and Fibrosis/HCC
2.6.2 HCV and Fibrosis/HCC
2.6.3 HEV and Liver Diseases
2.7 Therapeutic Implications
2.7.1 HBV Therapies
2.7.2 HCV Therapies
2.7.3 HEV Therapies
2.8 Conclusion
References
3. Epigenetics and Genetic Factors in Hepatitis Disease
Anu Bansal
3.1 Introduction
3.1.1 Global Health Impact
3.1.2 Beyond Viral Etiology: Role of Host Factors
3.2 Host Genetic Predisposition in Hepatitis
3.2.1 HLA and Immune Response Genes
3.2.2 Cytokine Gene Polymorphisms
3.2.3 Toll-Like Receptors (TLRs)
3.2.4 PNPLA3 and Other Metabolic Genes
3.3 Epigenetic Mechanisms in Hepatitis Pathogenesis
3.3.1 DNA Methylation
3.3.2 Histone Modifications
3.3.3 Non-Coding RNAs
3.4 Epigenetic Modifications in Chronic Hepatitis B and C Infection
3.4.1 HBV Epigenome Interactions
3.4.2 HCV-Driven Epigenetic Changes
3.4.3 Epigenetic Biomarkers
3.4.4 Epigenetic Therapeutic Targets
3.5 Host–Microbiome–Epigenetic Interactions in Hepatitis
3.5.1 Gut–Liver Axis and Hepatitis
3.5.2 Microbiome-Driven Epigenetic Regulation
3.5.3 Dysbiosis, Inflammation, and Epigenetic Changes
3.5.4 Microbiota–MiRNA Crosstalk
3.5.5 Therapeutic Implications
3.6 Clinical Applications: Biomarkers and Therapeutic Targets
3.6.1 Epigenetic Biomarkers for Diagnosis and Prognosis
3.6.2 Clinical Translation of Epigenetic Therapies
3.6.3 Challenges and Future Directions
3.7 Conclusion
References
4. Immune Pathogenesis of Hepatitis Disease
Rahul Khanna, Navpreet Kaur and Keshani Bhushan
4.1 Introduction
4.2 Mechanisms of Immune System Evasion
4.2.1 Evasion Strategies by Viruses
4.2.2 Latency
4.2.3 Epitope Mutation and Modulation of Apoptosis
4.2.4 Viral Tropism and Disruption of Antigen Presentation
4.2.5 NK Cell Evasion and Antibody and Complement System Evasion
4.2.6 Host Metabolic Manipulation
4.3 Immune Evasion Strategies of Various Hepatitis Viruses
4.3.1 Hepatitis A Virus (HAV)
4.3.2 Hepatitis B Virus (HBV)
4.3.3 Hepatitis C Virus (HCV)
4.3.4 Hepatitis D Virus (HDV)
4.3.5 Hepatitis E Virus (HEV)
4.4 Innate and Adaptive Immune Response
4.5 Pathogen Recognition Receptors (PRRs) and Viral Sensing
4.5.1 Toll-Like Receptors (TLRs)
4.5.2 RIG-I-Like Receptors (RLRs)
4.5.3 NOD-Like Receptors (NLRs)
4.5.4 Type I and III Interferons
4.5.5 Pro-Inflammatory Cytokines
4.5.6 Chemokines
4.5.7 Key Innate Immune Cell Types
4.5.8 Adaptive Immune Response to Hepatitis Viruses
4.5.8.1 CD4+ T Helper Cells
4.5.8.2 CD8+ Cytotoxic T Lymphocytes (CTLs)
4.5.8.3 B Cells and Antibody Responses
4.6 Immune Regulation and Injury in the Liver
4.6.1 Immune Activation and Regulation in the Liver
4.6.2 Mechanisms of Immune-Mediated Liver Injury
4.6.3 Cytoprotective Mechanisms
4.6.4 Hepatic Immune Tolerance
4.6.5 Cellular Basis of Tolerance
4.6.6 Relevance to Physiology and Pathology
4.7 Immunotherapeutics and Vaccine Perspectives
4.7.1 Current Immunotherapeutic Approaches
4.7.2 Therapeutic Vaccines for Chronic Hepatitis
4.7.3 Adjuvants, Antigen Delivery, and Overcoming Immune Tolerance in Therapeutic Hepatitis Vaccines
4.8 Preventive Vaccines and Global Impact
4.8.1 Hepatitis A Vaccine
4.8.2 Hepatitis B Vaccine
4.8.3 Hepatitis E Vaccine
4.9 Conclusion
References
5. Advances in Computational Chemistry for Hepatitis Drug Detection
Anamika Singh, Smriti Dewangan, K.P. Yadav and Gulab Chand Sahu
5.1 Introduction
5.2 Global Burden of Hepatitis B and C
5.2.1 Obstacles in the Development of Antiviral Therapeutics
5.2.2 Historical and Contemporary Role of Computational Chemistry in Drug Discovery
5.3 Molecular Targets in Hepatitis Viruses
5.3.1 Structural–Functional Insights into Viral Replication Machinery
5.3.2 Host–Pathogen Interactome and Molecular Pathogenesis
5.3.3 Identification and Validation of Druggable Targets in HBV and HCV
5.4 Computational Chemistry Methodologies in Hepatitis
5.4.1 Molecular Docking Techniques for Hepatitis Targets
5.4.2 Molecular Dynamics (MD) Simulations in Viral Protein‑Ligand Complexes
5.4.3 Quantum Mechanics Approaches for Mechanistic Insights
5.4.4 Structure–Activity and QSAR Modeling
5.5 Integration of Artificial Intelligence and Machine Learning
5.5.1 Predictive Modeling of Antiviral Activity Using Machine Learning Techniques
5.5.2 Deep Learning for Novel Molecular Design
5.5.3 AI-Driven Virtual Screening and Lead Optimization
5.6 Case Studies in Hepatitis Drug Discovery
5.6.1 Rational Design of NS3/4A Protease Inhibitors
5.6.2 Nucleotide and Non-Nucleotide Polymerases Inhibitors
5.6.3 HBV Capsid Assembly Modulator
5.7 Computational Tools and Databases
5.7.1 Structural Databases for Hepatitis Drug Targets
5.7.2 Ligand Libraries and ADMET Screening for Hepatitis Therapeutics
5.7.3 Modeling and Dynamics Simulation Tools in Hepatitis Drug Discovery
5.8 Challenges and Limitations
5.8.1 Predictive Accuracy and Reproducibility In Silico
5.8.2 Resistance Mutations and Viral Evolution
5.8.3 Bridging the Gap between In Silico and In Vitro
5.9 Future Perspectives
5.10 Conclusion
References
6. Computational Chemistry Approaches on Hepatitis Drug Discovery
Charmy Twala
6.1 Introduction
6.2 Hepatitis Drug Discovery Landscape
6.2.1 Molecular Targets for HBV
6.2.2 Drug Discovery Process for HCV
6.2.3 FDA-Approved Therapies
6.2.4 Challenges in Hepatitis Drug Discovery
6.2.5 The Role of Computational Chemistry
6.3 Computational Chemistry in Antiviral Discovery
6.3.1 Target Identification
6.3.2 Structure Retrieval and Modeling
6.3.3 Virtual Screening
6.3.4 Molecular Docking
6.3.5 Molecular Dynamics Simulations
6.3.6 Density Functional Theory and Time-Dependent DFT
6.3.7 Quantitative Structure-Activity Relationship (QSAR)
6.3.8 De Novo Drug Design
6.3.9 Artificial Intelligence (AI) and Machine Learning Integration
6.4 Applications in Hepatitis Drug Design
6.5 Key Studies and Findings in Hepatitis Drug Discovery
6.5.1 Computational Chemistry Approaches in Hepatitis Drug Development
6.5.2 Critical Analysis and Impact
6.6 Discussion
6.6.1 Strengths of Computational Methodologies
6.6.2 Limitations and Challenges
6.6.3 Critical Analysis
6.7 Future Direction in Hepatitis Drug Discovery
6.7.1 Deep Learning and AI-Driven Drug Discovery
6.7.2 Cloud-Based Simulations and Global Collaboration
6.7.3 Personalized Antiviral Therapies
6.7.4 Rapid-Response Drug Development Pipelines
6.7.5 Interdisciplinary Collaboration
6.7.6 Critical Analysis and Future Outlook
6.8 Conclusions
References
7. Genome Analysis of Hepatitis Viral Disease
Shradha Kaushik
7.1 Introduction
7.2 Genomic Approaches to Hepatitis Viruses
7.2.1 Polymerase Chain Reaction (PCR) and Sanger Sequencing
7.2.2 Next‑Generation Sequencing (NGS)
7.2.3 Single‑Genome Sequencing (SGS)
7.2.4 Genome-to-Genome Analyses
7.2.5 Bioinformatics and Knowledge Management
7.3 Hepatitis Genome Analysis
7.3.1 Hepatitis B Virus (HBV)
7.3.2 Hepatitis C Virus (HCV)
7.3.3 Hepatitis A Virus (HAV)
7.3.4 Hepatitis E Virus (HEV)
7.4 Hepatitis Delta Virus (HDV) Genome Analysis
7.5 Integration of Host and Viral Genomics
7.6 Advances in Sequencing Technologies for Hepatitis Viruses
7.6.1 Illumina and Nanopore Sequencing
7.6.2 Single‑Genome and Deep Sequencing
7.6.3 Bioinformatics Pipelines for Viral Genome Analysis
7.6.4 Future Trends: Multi‑Omics Integration
7.7 Clinical Implications of Viral Genome Analysis
7.7.1 Prognosis and Treatment Outcomes
7.7.2 Personalized Medicine in Hepatitis
7.7.3 Challenges and Future Directions
7.8 Conclusion
Bibliography
8. Quantitative Structure–Activity Relationship Studies on Hepatitis Disease
Mansi
8.1 Introduction
8.2 Public Databases and Bioinformatics Tools for HBV
8.2.1 NIHR HIC HBV Research Database
8.2.2 HBVdb (Hepatitis B Virus Database)
8.2.3 HepSEQ (Hepatitis Sequence Database)
8.2.4 Geno2pheno (HBV) Tool
8.3 Public Databases and Bioinformatics Tools for HCV
8.3.1 Virus Pathogen and Analysis Resource and Database
8.3.2 The Los Alamos National Laboratory’s HCV Sequence Database
8.3.3 The European Hepatitis C Virus Database
8.3.4 ViralZone
8.3.5 Role of QSAR in Studying Viral Hepatitis HBV and HCV Infections
8.4 Conclusion
References
9. System-Based Therapeutic Strategies for Hepatitis: A Network Pharmacology Approach
Sanjana Gaikwad
9.1 Introduction
9.2 Systems-Level Pathophysiology of Hepatitis
9.3 Multi-Omics Integration and Network Analysis Approaches for Hepatitis
9.4 Therapeutic Target Identification
9.5 Polypharmacology and Natural Compounds
9.6 Computational Tools and Methods
9.7 Case Studies
9.8 Conclusion and Future Prospects
References
10. Quantum Chemical Calculations of Derived Compounds as Potential Inhibitors against Hepatitis Virus
Lovleen Kaur and Subrat Kumar Pattanayak
10.1 Introduction
10.2 Literature Review and Rationale for Selection
10.3 Computational Details
10.3.1 Toxicity Prediction and Docking
10.3.2 Frontier Molecular Orbital Calculations
10.3.3 Electrostatic Potential Mapping
10.4 Results and Discussion
10.4.1 Toxicity Prediction and Docking
10.4.2 FMO Analysis
10.4.3 Electrostatic Potential Mapping
10.4.4 Integrated Computational Analysis: Correlating Docking, Electronic Properties, and Molecular Recognition
10.5 Conclusions and Future Directions
References
6. Computational Chemistry Approaches on Hepatitis Drug Discovery
Charmy Twala
6.1 Introduction
6.2 Hepatitis Drug Discovery Landscape
6.2.1 Molecular Targets for HBV
6.2.2 Drug Discovery Process for HCV
6.2.3 FDA-Approved Therapies
6.2.4 Challenges in Hepatitis Drug Discovery
6.2.5 The Role of Computational Chemistry
6.3 Computational Chemistry in Antiviral Discovery
6.3.1 Target Identification
6.3.2 Structure Retrieval and Modeling
6.3.3 Virtual Screening
6.3.4 Molecular Docking
6.3.5 Molecular Dynamics Simulations
6.3.6 Density Functional Theory and Time-Dependent DFT
6.3.7 Quantitative Structure-Activity Relationship (QSAR)
6.3.8 De Novo Drug Design
6.3.9 Artificial Intelligence (AI) and Machine Learning Integration
6.4 Applications in Hepatitis Drug Design
6.5 Key Studies and Findings in Hepatitis Drug Discovery
6.5.1 Computational Chemistry Approaches in Hepatitis Drug Development
6.5.2 Critical Analysis and Impact
6.6 Discussion
6.6.1 Strengths of Computational Methodologies
6.6.2 Limitations and Challenges
6.6.3 Critical Analysis
6.7 Future Direction in Hepatitis Drug Discovery
6.7.1 Deep Learning and AI-Driven Drug Discovery
6.7.2 Cloud-Based Simulations and Global Collaboration
6.7.3 Personalized Antiviral Therapies
6.7.4 Rapid-Response Drug Development Pipelines
6.7.5 Interdisciplinary Collaboration
6.7.6 Critical Analysis and Future Outlook
6.8 Conclusions
References
7. Genome Analysis of Hepatitis Viral Disease
Shradha Kaushik
7.1 Introduction
7.2 Genomic Approaches to Hepatitis Viruses
7.2.1 Polymerase Chain Reaction (PCR) and Sanger Sequencing
7.2.2 Next‑Generation Sequencing (NGS)
7.2.3 Single‑Genome Sequencing (SGS)
7.2.4 Genome-to-Genome Analyses
7.2.5 Bioinformatics and Knowledge Management
7.3 Hepatitis Genome Analysis
7.3.1 Hepatitis B Virus (HBV)
7.3.2 Hepatitis C Virus (HCV)
7.3.3 Hepatitis A Virus (HAV)
7.3.4 Hepatitis E Virus (HEV)
7.4 Hepatitis Delta Virus (HDV) Genome Analysis
7.5 Integration of Host and Viral Genomics
7.6 Advances in Sequencing Technologies for Hepatitis Viruses
7.6.1 Illumina and Nanopore Sequencing
7.6.2 Single‑Genome and Deep Sequencing
7.6.3 Bioinformatics Pipelines for Viral Genome Analysis
7.6.4 Future Trends: Multi‑Omics Integration
7.7 Clinical Implications of Viral Genome Analysis
7.7.1 Prognosis and Treatment Outcomes
7.7.2 Personalized Medicine in Hepatitis
7.7.3 Challenges and Future Directions
7.8 Conclusion
Bibliography
8. Quantitative Structure–Activity Relationship Studies on Hepatitis Disease
Mansi
8.1 Introduction
8.2 Public Databases and Bioinformatics Tools for HBV
8.2.1 NIHR HIC HBV Research Database
8.2.2 HBVdb (Hepatitis B Virus Database)
8.2.3 HepSEQ (Hepatitis Sequence Database)
8.2.4 Geno2pheno (HBV) Tool
8.3 Public Databases and Bioinformatics Tools for HCV
8.3.1 Virus Pathogen and Analysis Resource and Database
8.3.2 The Los Alamos National Laboratory’s HCV Sequence Database
8.3.3 The European Hepatitis C Virus Database
8.3.4 ViralZone
8.3.5 Role of QSAR in Studying Viral Hepatitis HBV and HCV Infections
8.4 Conclusion
References
9. System-Based Therapeutic Strategies for Hepatitis: A Network Pharmacology Approach
Sanjana Gaikwad
9.1 Introduction
9.2 Systems-Level Pathophysiology of Hepatitis
9.3 Multi-Omics Integration and Network Analysis Approaches for Hepatitis
9.4 Therapeutic Target Identification
9.5 Polypharmacology and Natural Compounds
9.6 Computational Tools and Methods
9.7 Case Studies
9.8 Conclusion and Future Prospects
References
10. Quantum Chemical Calculations of Derived Compounds as Potential Inhibitors against Hepatitis Virus
Lovleen Kaur and Subrat Kumar Pattanayak
10.1 Introduction
10.2 Literature Review and Rationale for Selection
10.3 Computational Details
10.3.1 Toxicity Prediction and Docking
10.3.2 Frontier Molecular Orbital Calculations
10.3.3 Electrostatic Potential Mapping
10.4 Results and Discussion
10.4.1 Toxicity Prediction and Docking
10.4.2 FMO Analysis
10.4.3 Electrostatic Potential Mapping
10.4.4 Integrated Computational Analysis: Correlating Docking, Electronic Properties, and Molecular Recognition
10.5 Conclusions and Future Directions
References
11. Prevention and Global Vaccination Status and Emerging Therapy in Hepatitis Disease
Charu Tomar and Pratichi Singh
11.1 Introduction
11.2 Hepatitis Viruses: Types and Transmission
11.3 Prevention Strategies in Hepatitis
11.3.1 General Preventive Measures
11.3.2 Vaccination as Prevention
11.4 New Therapies in Hepatitis Disease
11.5 Conclusion and Challenges in Hepatitis Control
References
12. Decoding Hepatitis Therapeutics: A Network-Based System Biology and Polypharmacology Approach
Parameswar Sahu, Manas Ranjan Dikhit, Pragya Tiwari and Rosaleen Sahoo
12.1 Introduction
12.2 Limitations of Current Mono-Target Therapies
12.3 Need for Multi-Target Strategies in Hepatitis Treatment
12.4 Pathophysiology and Molecular Basis of Hepatitis
12.5 Major Molecular Pathways Involved in Hepatic Inflammation and Fibrosis
12.6 Crosstalk between Immune Response, Oxidative Stress, and Apoptosis
12.7 Rationale for Targeting Multiple Pathways
12.8 Definition and Principles of Polypharmacology
12.8.1 Systems Biology: Integrating Omics Data and Network Biology
12.8.2 Synergy between Polypharmacology and Systems Biology
12.8.3 Tools and Technologies Used (e.g., Network Pharmacology, Data Integration Platforms)
12.9 Systems-Level Targets in Hepatitis
12.9.1 Identification of Host and Viral Targets via Genomics, Transcriptomics, and Proteomics
12.9.2 Network Analysis to Identify Key Regulators (Hub Genes, Bottlenecks)
12.9.3 Pathway Enrichment Analysis (e.g., TLR, NF-κB, JAK/STAT, MAPK Pathways)
12.10 Strategies for Multi-Target Drug Discovery
12.10.1 Network Pharmacology-Based Screening
12.10.2 Ligand-Based and Structure-Based Drug Design for Multi-Target Binding
12.10.3 In Silico Modeling of Target-Drug Interactions (Docking, MD Simulations)
12.10.4 Drug Repurposing Using Polypharmacology Principles
12.11 Natural Products and Multi-Target Potential
12.12 Future Perspectives and Conclusion
Bibliography
13. Leveraging AI and Big Data for Early Detection and Personalized Treatment of Hepatitis
Abhishek Kumar Sahu, Rosaleen Sahoo, Parameswar Sahu, Sundeep Singh Saluja and Siddharth Srivastava
13.1 Introduction
13.2 Deep Learning Framework for Advanced Hepatitis Analysis
13.2.1 Convolutional Neural Networks in Medical Imaging
13.2.2 Recurrent Neural Networks for Temporal Analysis
13.2.3 Transformer Architectures and Natural Language Processing
13.2.4 Genomic-Based Precision Treatment
13.2.5 Real-Time Surveillance Systems
13.2.6 AI-Accelerated Compound Identification
13.2.7 Resistance Pattern Prediction
13.3 Limitations
13.3.1 Data Quality and Standardization
13.3.2 Algorithmic Bias and Generalizability
13.3.3 Regulatory Considerations
13.3.4 AI in Hepatitis
13.3.5 Automated Image Analysis
13.3.6 NLP for Clinical Text and Real-World Data
13.3.7 Clinical Decision Support Systems [CDSS]
13.3.8 Robotics, Surgical AI, and Remote Monitoring
13.4 Conclusion
References
14. Network Pharmacology and Structure-Based Drug Designing for Hepatic Disorder
Pragnya Paramita Mahapatra, Biswajit Mishra, Maheswata Moharana and Satya Narayan Sahu
14.1 Introduction
14.2 Data Mining Process
14.3 Network Architecture and Evaluation
14.4 Results Validation
14.4.1 Methods of Network Pharmacology Research
14.4.2 Methodology
14.4.3 Integrating the Molecular Disease Network with the Pharmacological Network of the Potential Drugs
14.4.4 Network Pharmacology’s Therapeutic Implications
14.5 Conclusion
References
15. Experimental Models for Drug Repurposing in Viral Hepatitis: Applications of In Vitro and In Vivo Methodologies
Amit Talukdar and Arpita Devi
15.1 Introduction
15.1.1 Current Diagnosis for Viral Hepatitis and Its Treatments
15.1.2 Limitations of Current Treatments and Rationale for Drug Repurposing
15.2 Strategies for Drug Repurposing: On-Target, Off-Target and Combination-Target Strategies
15.3 In Vitro Models for Testing Repurposed Drugs against Viral Hepatitis
15.3.1 Two-Dimensional (2D) Cell Culture Systems
15.3.2 Hepatoma-Derived Cell Lines
15.3.3 HepaRG Cell Line
15.3.4 NTCP-Overexpressing Hepatoma Cell Lines
15.4 Three-Dimensional (3D) Cell Culture Systems
15.4.1 Hepatic Spheroids
15.4.2 Stem-Cell Derived Hepatic Organoids
15.5 In Vivo Models for Testing Repurposed Drugs against Viral Hepatitis
15.5.1 Chimpanzees
15.5.2 Macaques
15.5.3 Tamarins
15.5.4 Tupaias and Rodents
15.5.5 Woodchucks (Groundhogs)
15.5.6 Mongolian Gerbils (Desert Rats)
15.5.7 Mice
15.5.8 Pigs and Rabbits
15.5.9 Chickens
15.5.10 Other Small Animals
15.6 Regulatory and Ethical Considerations for Repurposed Drugs
15.7 Conclusion and Future Perspectives
Bibliography
16. The Immunogenetic Landscape of Viral Hepatitis: Determinants of Persistence and Pathogenesis
Amrita Chakrabarti and Jawahar Kopparam
16.1 Introduction
16.2 Host–Pathogen Interactions in Viral Hepatitis
16.3 Hepatitis A Virus (HAV)
16.3.1 Epidemiology of Hepatitis A Virus
16.3.2 Genetic Landscape of Hepatitis A Virus
16.3.3 Innate Immune Response
16.3.4 Adaptive Immune Response
16.4 Hepatitis B Virus (HBV)
16.4.1 Epidemiology of Hepatitis B Virus
16.4.2 Genetic Landscape of Hepatitis B Virus
16.4.3 Innate Immune Response to HBV
16.4.4 Adaptive Immune Response to HBV
16.5 Hepatitis C Virus (HCV)
16.5.1 Epidemiology of Hepatitis C Virus
16.5.2 Genetic Landscape of Hepatitis C Virus
16.5.3 Innate Immune Response of HCV
16.5.4 Adaptive Immune Response of HCV
16.6 Hepatitis D: The Satellite Virus of HBV
16.6.1 Epidemiology of Hepatitis D Virus
16.6.2 HDV Acquisition and Associated Disease Outcomes
16.6.3 Genetic Landscape of Hepatitis D Virus
16.6.4 Innate Immune Response of HDV
16.6.5 Adaptive Immune Response of HDV
16.7 Hepatitis E
16.7.1 Epidemiology of Hepatitis E Virus
16.7.2 Genetic Landscape of Hepatitis E Virus
16.7.3 Innate Immune Response of HEV
16.7.4 Adaptive Immune Response of HEV
16.8 HCC Development
16.8.1 Immune Mechanisms Fueling HBV-Related HCC
16.8.2 Immune Mechanisms Fueling HCV-Related HCC
16.9 Current Therapies and Limitations
16.10 Conclusions and Future Perspectives
References
17. Future Perspectives in Hepatitis Disease
Yamini Thakur and Om Prakash Gaure
17.1 Introduction
17.2 The Unresolved Challenges of Chronic Hepatitis
17.3 Traditional and Emerging Therapeutic Gaps
17.4 Vision for a Transformative Future
17.5 Advances and Emerging Trends in Hepatitis Disease
17.5.1 Gene- and RNA-Editing Technologies
17.5.1.1 mRNA Therapeutic Platforms
17.5.2 Epigenetic Modulation
17.5.3 Vaccines and Immunotherapeutics in the Next Generation
17.5.4 AI, Multi-Omics, and Precision Medicine
17.5.5 Microbiome and the Gut–Liver Axis
17.5.6 Advanced Delivery: Nanocarriers and Nanotheranostics
17.5.7 Global Health Equity and Access
17.5.8 Ethical, Safety, and Regulatory Frontiers
17.5.9 Integration of Natural Compounds with Advanced Technologies
17.6 Conclusion
References
Index
Back to Top
1. Hepatitis: A Comprehensive Overview of Types, Causes, and Treatment Strategies
Avijit Biswal and Maheswata Moharana
1.1 Introduction
1.2 Types of Hepatitis
1.2.1 Viral Hepatitis (Types, Causes, Diagnosis)
1.2.2 Non-Viral Hepatitis (Types, Cause, Diagnosis)
1.2.3 Treatment Strategies of Viral and Non-Viral Hepatitis and Challenges
1.3 Conclusions and Future Perspective
References
2. Molecular Biology of Liver Diseases: Hepatitis B, Hepatitis C, and Hepatitis E Viruses
Swetanshu, Harshita Rana and Pratichi Singh
2.1 Introduction
2.1.1 Virology and Genetic Organization
2.2 Mechanisms of Viral Entry and Intracellular Replication
2.2.1 HBV Entry and Replication
2.2.2 HCV Replication and Entry
2.2.3 HEV Entry and Replication
2.3 Virus–Host Interactions and Immune Evasion
2.3.1 HBV-Host Interactions
2.3.2 HCV–Host Interactions
2.3.3 HEV–Host Interactions
2.4 Host Immune and Molecular Responses
2.4.1 Innate Immune Responses
2.4.2 Adaptive Immune Responses
2.5 Molecular Stress Responses and Pathology
2.6 Fibrosis and Hepatocellular Carcinoma
2.6.1 HBV and Fibrosis/HCC
2.6.2 HCV and Fibrosis/HCC
2.6.3 HEV and Liver Diseases
2.7 Therapeutic Implications
2.7.1 HBV Therapies
2.7.2 HCV Therapies
2.7.3 HEV Therapies
2.8 Conclusion
References
3. Epigenetics and Genetic Factors in Hepatitis Disease
Anu Bansal
3.1 Introduction
3.1.1 Global Health Impact
3.1.2 Beyond Viral Etiology: Role of Host Factors
3.2 Host Genetic Predisposition in Hepatitis
3.2.1 HLA and Immune Response Genes
3.2.2 Cytokine Gene Polymorphisms
3.2.3 Toll-Like Receptors (TLRs)
3.2.4 PNPLA3 and Other Metabolic Genes
3.3 Epigenetic Mechanisms in Hepatitis Pathogenesis
3.3.1 DNA Methylation
3.3.2 Histone Modifications
3.3.3 Non-Coding RNAs
3.4 Epigenetic Modifications in Chronic Hepatitis B and C Infection
3.4.1 HBV Epigenome Interactions
3.4.2 HCV-Driven Epigenetic Changes
3.4.3 Epigenetic Biomarkers
3.4.4 Epigenetic Therapeutic Targets
3.5 Host–Microbiome–Epigenetic Interactions in Hepatitis
3.5.1 Gut–Liver Axis and Hepatitis
3.5.2 Microbiome-Driven Epigenetic Regulation
3.5.3 Dysbiosis, Inflammation, and Epigenetic Changes
3.5.4 Microbiota–MiRNA Crosstalk
3.5.5 Therapeutic Implications
3.6 Clinical Applications: Biomarkers and Therapeutic Targets
3.6.1 Epigenetic Biomarkers for Diagnosis and Prognosis
3.6.2 Clinical Translation of Epigenetic Therapies
3.6.3 Challenges and Future Directions
3.7 Conclusion
References
4. Immune Pathogenesis of Hepatitis Disease
Rahul Khanna, Navpreet Kaur and Keshani Bhushan
4.1 Introduction
4.2 Mechanisms of Immune System Evasion
4.2.1 Evasion Strategies by Viruses
4.2.2 Latency
4.2.3 Epitope Mutation and Modulation of Apoptosis
4.2.4 Viral Tropism and Disruption of Antigen Presentation
4.2.5 NK Cell Evasion and Antibody and Complement System Evasion
4.2.6 Host Metabolic Manipulation
4.3 Immune Evasion Strategies of Various Hepatitis Viruses
4.3.1 Hepatitis A Virus (HAV)
4.3.2 Hepatitis B Virus (HBV)
4.3.3 Hepatitis C Virus (HCV)
4.3.4 Hepatitis D Virus (HDV)
4.3.5 Hepatitis E Virus (HEV)
4.4 Innate and Adaptive Immune Response
4.5 Pathogen Recognition Receptors (PRRs) and Viral Sensing
4.5.1 Toll-Like Receptors (TLRs)
4.5.2 RIG-I-Like Receptors (RLRs)
4.5.3 NOD-Like Receptors (NLRs)
4.5.4 Type I and III Interferons
4.5.5 Pro-Inflammatory Cytokines
4.5.6 Chemokines
4.5.7 Key Innate Immune Cell Types
4.5.8 Adaptive Immune Response to Hepatitis Viruses
4.5.8.1 CD4+ T Helper Cells
4.5.8.2 CD8+ Cytotoxic T Lymphocytes (CTLs)
4.5.8.3 B Cells and Antibody Responses
4.6 Immune Regulation and Injury in the Liver
4.6.1 Immune Activation and Regulation in the Liver
4.6.2 Mechanisms of Immune-Mediated Liver Injury
4.6.3 Cytoprotective Mechanisms
4.6.4 Hepatic Immune Tolerance
4.6.5 Cellular Basis of Tolerance
4.6.6 Relevance to Physiology and Pathology
4.7 Immunotherapeutics and Vaccine Perspectives
4.7.1 Current Immunotherapeutic Approaches
4.7.2 Therapeutic Vaccines for Chronic Hepatitis
4.7.3 Adjuvants, Antigen Delivery, and Overcoming Immune Tolerance in Therapeutic Hepatitis Vaccines
4.8 Preventive Vaccines and Global Impact
4.8.1 Hepatitis A Vaccine
4.8.2 Hepatitis B Vaccine
4.8.3 Hepatitis E Vaccine
4.9 Conclusion
References
5. Advances in Computational Chemistry for Hepatitis Drug Detection
Anamika Singh, Smriti Dewangan, K.P. Yadav and Gulab Chand Sahu
5.1 Introduction
5.2 Global Burden of Hepatitis B and C
5.2.1 Obstacles in the Development of Antiviral Therapeutics
5.2.2 Historical and Contemporary Role of Computational Chemistry in Drug Discovery
5.3 Molecular Targets in Hepatitis Viruses
5.3.1 Structural–Functional Insights into Viral Replication Machinery
5.3.2 Host–Pathogen Interactome and Molecular Pathogenesis
5.3.3 Identification and Validation of Druggable Targets in HBV and HCV
5.4 Computational Chemistry Methodologies in Hepatitis
5.4.1 Molecular Docking Techniques for Hepatitis Targets
5.4.2 Molecular Dynamics (MD) Simulations in Viral Protein‑Ligand Complexes
5.4.3 Quantum Mechanics Approaches for Mechanistic Insights
5.4.4 Structure–Activity and QSAR Modeling
5.5 Integration of Artificial Intelligence and Machine Learning
5.5.1 Predictive Modeling of Antiviral Activity Using Machine Learning Techniques
5.5.2 Deep Learning for Novel Molecular Design
5.5.3 AI-Driven Virtual Screening and Lead Optimization
5.6 Case Studies in Hepatitis Drug Discovery
5.6.1 Rational Design of NS3/4A Protease Inhibitors
5.6.2 Nucleotide and Non-Nucleotide Polymerases Inhibitors
5.6.3 HBV Capsid Assembly Modulator
5.7 Computational Tools and Databases
5.7.1 Structural Databases for Hepatitis Drug Targets
5.7.2 Ligand Libraries and ADMET Screening for Hepatitis Therapeutics
5.7.3 Modeling and Dynamics Simulation Tools in Hepatitis Drug Discovery
5.8 Challenges and Limitations
5.8.1 Predictive Accuracy and Reproducibility In Silico
5.8.2 Resistance Mutations and Viral Evolution
5.8.3 Bridging the Gap between In Silico and In Vitro
5.9 Future Perspectives
5.10 Conclusion
References
6. Computational Chemistry Approaches on Hepatitis Drug Discovery
Charmy Twala
6.1 Introduction
6.2 Hepatitis Drug Discovery Landscape
6.2.1 Molecular Targets for HBV
6.2.2 Drug Discovery Process for HCV
6.2.3 FDA-Approved Therapies
6.2.4 Challenges in Hepatitis Drug Discovery
6.2.5 The Role of Computational Chemistry
6.3 Computational Chemistry in Antiviral Discovery
6.3.1 Target Identification
6.3.2 Structure Retrieval and Modeling
6.3.3 Virtual Screening
6.3.4 Molecular Docking
6.3.5 Molecular Dynamics Simulations
6.3.6 Density Functional Theory and Time-Dependent DFT
6.3.7 Quantitative Structure-Activity Relationship (QSAR)
6.3.8 De Novo Drug Design
6.3.9 Artificial Intelligence (AI) and Machine Learning Integration
6.4 Applications in Hepatitis Drug Design
6.5 Key Studies and Findings in Hepatitis Drug Discovery
6.5.1 Computational Chemistry Approaches in Hepatitis Drug Development
6.5.2 Critical Analysis and Impact
6.6 Discussion
6.6.1 Strengths of Computational Methodologies
6.6.2 Limitations and Challenges
6.6.3 Critical Analysis
6.7 Future Direction in Hepatitis Drug Discovery
6.7.1 Deep Learning and AI-Driven Drug Discovery
6.7.2 Cloud-Based Simulations and Global Collaboration
6.7.3 Personalized Antiviral Therapies
6.7.4 Rapid-Response Drug Development Pipelines
6.7.5 Interdisciplinary Collaboration
6.7.6 Critical Analysis and Future Outlook
6.8 Conclusions
References
7. Genome Analysis of Hepatitis Viral Disease
Shradha Kaushik
7.1 Introduction
7.2 Genomic Approaches to Hepatitis Viruses
7.2.1 Polymerase Chain Reaction (PCR) and Sanger Sequencing
7.2.2 Next‑Generation Sequencing (NGS)
7.2.3 Single‑Genome Sequencing (SGS)
7.2.4 Genome-to-Genome Analyses
7.2.5 Bioinformatics and Knowledge Management
7.3 Hepatitis Genome Analysis
7.3.1 Hepatitis B Virus (HBV)
7.3.2 Hepatitis C Virus (HCV)
7.3.3 Hepatitis A Virus (HAV)
7.3.4 Hepatitis E Virus (HEV)
7.4 Hepatitis Delta Virus (HDV) Genome Analysis
7.5 Integration of Host and Viral Genomics
7.6 Advances in Sequencing Technologies for Hepatitis Viruses
7.6.1 Illumina and Nanopore Sequencing
7.6.2 Single‑Genome and Deep Sequencing
7.6.3 Bioinformatics Pipelines for Viral Genome Analysis
7.6.4 Future Trends: Multi‑Omics Integration
7.7 Clinical Implications of Viral Genome Analysis
7.7.1 Prognosis and Treatment Outcomes
7.7.2 Personalized Medicine in Hepatitis
7.7.3 Challenges and Future Directions
7.8 Conclusion
Bibliography
8. Quantitative Structure–Activity Relationship Studies on Hepatitis Disease
Mansi
8.1 Introduction
8.2 Public Databases and Bioinformatics Tools for HBV
8.2.1 NIHR HIC HBV Research Database
8.2.2 HBVdb (Hepatitis B Virus Database)
8.2.3 HepSEQ (Hepatitis Sequence Database)
8.2.4 Geno2pheno (HBV) Tool
8.3 Public Databases and Bioinformatics Tools for HCV
8.3.1 Virus Pathogen and Analysis Resource and Database
8.3.2 The Los Alamos National Laboratory’s HCV Sequence Database
8.3.3 The European Hepatitis C Virus Database
8.3.4 ViralZone
8.3.5 Role of QSAR in Studying Viral Hepatitis HBV and HCV Infections
8.4 Conclusion
References
9. System-Based Therapeutic Strategies for Hepatitis: A Network Pharmacology Approach
Sanjana Gaikwad
9.1 Introduction
9.2 Systems-Level Pathophysiology of Hepatitis
9.3 Multi-Omics Integration and Network Analysis Approaches for Hepatitis
9.4 Therapeutic Target Identification
9.5 Polypharmacology and Natural Compounds
9.6 Computational Tools and Methods
9.7 Case Studies
9.8 Conclusion and Future Prospects
References
10. Quantum Chemical Calculations of Derived Compounds as Potential Inhibitors against Hepatitis Virus
Lovleen Kaur and Subrat Kumar Pattanayak
10.1 Introduction
10.2 Literature Review and Rationale for Selection
10.3 Computational Details
10.3.1 Toxicity Prediction and Docking
10.3.2 Frontier Molecular Orbital Calculations
10.3.3 Electrostatic Potential Mapping
10.4 Results and Discussion
10.4.1 Toxicity Prediction and Docking
10.4.2 FMO Analysis
10.4.3 Electrostatic Potential Mapping
10.4.4 Integrated Computational Analysis: Correlating Docking, Electronic Properties, and Molecular Recognition
10.5 Conclusions and Future Directions
References
6. Computational Chemistry Approaches on Hepatitis Drug Discovery
Charmy Twala
6.1 Introduction
6.2 Hepatitis Drug Discovery Landscape
6.2.1 Molecular Targets for HBV
6.2.2 Drug Discovery Process for HCV
6.2.3 FDA-Approved Therapies
6.2.4 Challenges in Hepatitis Drug Discovery
6.2.5 The Role of Computational Chemistry
6.3 Computational Chemistry in Antiviral Discovery
6.3.1 Target Identification
6.3.2 Structure Retrieval and Modeling
6.3.3 Virtual Screening
6.3.4 Molecular Docking
6.3.5 Molecular Dynamics Simulations
6.3.6 Density Functional Theory and Time-Dependent DFT
6.3.7 Quantitative Structure-Activity Relationship (QSAR)
6.3.8 De Novo Drug Design
6.3.9 Artificial Intelligence (AI) and Machine Learning Integration
6.4 Applications in Hepatitis Drug Design
6.5 Key Studies and Findings in Hepatitis Drug Discovery
6.5.1 Computational Chemistry Approaches in Hepatitis Drug Development
6.5.2 Critical Analysis and Impact
6.6 Discussion
6.6.1 Strengths of Computational Methodologies
6.6.2 Limitations and Challenges
6.6.3 Critical Analysis
6.7 Future Direction in Hepatitis Drug Discovery
6.7.1 Deep Learning and AI-Driven Drug Discovery
6.7.2 Cloud-Based Simulations and Global Collaboration
6.7.3 Personalized Antiviral Therapies
6.7.4 Rapid-Response Drug Development Pipelines
6.7.5 Interdisciplinary Collaboration
6.7.6 Critical Analysis and Future Outlook
6.8 Conclusions
References
7. Genome Analysis of Hepatitis Viral Disease
Shradha Kaushik
7.1 Introduction
7.2 Genomic Approaches to Hepatitis Viruses
7.2.1 Polymerase Chain Reaction (PCR) and Sanger Sequencing
7.2.2 Next‑Generation Sequencing (NGS)
7.2.3 Single‑Genome Sequencing (SGS)
7.2.4 Genome-to-Genome Analyses
7.2.5 Bioinformatics and Knowledge Management
7.3 Hepatitis Genome Analysis
7.3.1 Hepatitis B Virus (HBV)
7.3.2 Hepatitis C Virus (HCV)
7.3.3 Hepatitis A Virus (HAV)
7.3.4 Hepatitis E Virus (HEV)
7.4 Hepatitis Delta Virus (HDV) Genome Analysis
7.5 Integration of Host and Viral Genomics
7.6 Advances in Sequencing Technologies for Hepatitis Viruses
7.6.1 Illumina and Nanopore Sequencing
7.6.2 Single‑Genome and Deep Sequencing
7.6.3 Bioinformatics Pipelines for Viral Genome Analysis
7.6.4 Future Trends: Multi‑Omics Integration
7.7 Clinical Implications of Viral Genome Analysis
7.7.1 Prognosis and Treatment Outcomes
7.7.2 Personalized Medicine in Hepatitis
7.7.3 Challenges and Future Directions
7.8 Conclusion
Bibliography
8. Quantitative Structure–Activity Relationship Studies on Hepatitis Disease
Mansi
8.1 Introduction
8.2 Public Databases and Bioinformatics Tools for HBV
8.2.1 NIHR HIC HBV Research Database
8.2.2 HBVdb (Hepatitis B Virus Database)
8.2.3 HepSEQ (Hepatitis Sequence Database)
8.2.4 Geno2pheno (HBV) Tool
8.3 Public Databases and Bioinformatics Tools for HCV
8.3.1 Virus Pathogen and Analysis Resource and Database
8.3.2 The Los Alamos National Laboratory’s HCV Sequence Database
8.3.3 The European Hepatitis C Virus Database
8.3.4 ViralZone
8.3.5 Role of QSAR in Studying Viral Hepatitis HBV and HCV Infections
8.4 Conclusion
References
9. System-Based Therapeutic Strategies for Hepatitis: A Network Pharmacology Approach
Sanjana Gaikwad
9.1 Introduction
9.2 Systems-Level Pathophysiology of Hepatitis
9.3 Multi-Omics Integration and Network Analysis Approaches for Hepatitis
9.4 Therapeutic Target Identification
9.5 Polypharmacology and Natural Compounds
9.6 Computational Tools and Methods
9.7 Case Studies
9.8 Conclusion and Future Prospects
References
10. Quantum Chemical Calculations of Derived Compounds as Potential Inhibitors against Hepatitis Virus
Lovleen Kaur and Subrat Kumar Pattanayak
10.1 Introduction
10.2 Literature Review and Rationale for Selection
10.3 Computational Details
10.3.1 Toxicity Prediction and Docking
10.3.2 Frontier Molecular Orbital Calculations
10.3.3 Electrostatic Potential Mapping
10.4 Results and Discussion
10.4.1 Toxicity Prediction and Docking
10.4.2 FMO Analysis
10.4.3 Electrostatic Potential Mapping
10.4.4 Integrated Computational Analysis: Correlating Docking, Electronic Properties, and Molecular Recognition
10.5 Conclusions and Future Directions
References
11. Prevention and Global Vaccination Status and Emerging Therapy in Hepatitis Disease
Charu Tomar and Pratichi Singh
11.1 Introduction
11.2 Hepatitis Viruses: Types and Transmission
11.3 Prevention Strategies in Hepatitis
11.3.1 General Preventive Measures
11.3.2 Vaccination as Prevention
11.4 New Therapies in Hepatitis Disease
11.5 Conclusion and Challenges in Hepatitis Control
References
12. Decoding Hepatitis Therapeutics: A Network-Based System Biology and Polypharmacology Approach
Parameswar Sahu, Manas Ranjan Dikhit, Pragya Tiwari and Rosaleen Sahoo
12.1 Introduction
12.2 Limitations of Current Mono-Target Therapies
12.3 Need for Multi-Target Strategies in Hepatitis Treatment
12.4 Pathophysiology and Molecular Basis of Hepatitis
12.5 Major Molecular Pathways Involved in Hepatic Inflammation and Fibrosis
12.6 Crosstalk between Immune Response, Oxidative Stress, and Apoptosis
12.7 Rationale for Targeting Multiple Pathways
12.8 Definition and Principles of Polypharmacology
12.8.1 Systems Biology: Integrating Omics Data and Network Biology
12.8.2 Synergy between Polypharmacology and Systems Biology
12.8.3 Tools and Technologies Used (e.g., Network Pharmacology, Data Integration Platforms)
12.9 Systems-Level Targets in Hepatitis
12.9.1 Identification of Host and Viral Targets via Genomics, Transcriptomics, and Proteomics
12.9.2 Network Analysis to Identify Key Regulators (Hub Genes, Bottlenecks)
12.9.3 Pathway Enrichment Analysis (e.g., TLR, NF-κB, JAK/STAT, MAPK Pathways)
12.10 Strategies for Multi-Target Drug Discovery
12.10.1 Network Pharmacology-Based Screening
12.10.2 Ligand-Based and Structure-Based Drug Design for Multi-Target Binding
12.10.3 In Silico Modeling of Target-Drug Interactions (Docking, MD Simulations)
12.10.4 Drug Repurposing Using Polypharmacology Principles
12.11 Natural Products and Multi-Target Potential
12.12 Future Perspectives and Conclusion
Bibliography
13. Leveraging AI and Big Data for Early Detection and Personalized Treatment of Hepatitis
Abhishek Kumar Sahu, Rosaleen Sahoo, Parameswar Sahu, Sundeep Singh Saluja and Siddharth Srivastava
13.1 Introduction
13.2 Deep Learning Framework for Advanced Hepatitis Analysis
13.2.1 Convolutional Neural Networks in Medical Imaging
13.2.2 Recurrent Neural Networks for Temporal Analysis
13.2.3 Transformer Architectures and Natural Language Processing
13.2.4 Genomic-Based Precision Treatment
13.2.5 Real-Time Surveillance Systems
13.2.6 AI-Accelerated Compound Identification
13.2.7 Resistance Pattern Prediction
13.3 Limitations
13.3.1 Data Quality and Standardization
13.3.2 Algorithmic Bias and Generalizability
13.3.3 Regulatory Considerations
13.3.4 AI in Hepatitis
13.3.5 Automated Image Analysis
13.3.6 NLP for Clinical Text and Real-World Data
13.3.7 Clinical Decision Support Systems [CDSS]
13.3.8 Robotics, Surgical AI, and Remote Monitoring
13.4 Conclusion
References
14. Network Pharmacology and Structure-Based Drug Designing for Hepatic Disorder
Pragnya Paramita Mahapatra, Biswajit Mishra, Maheswata Moharana and Satya Narayan Sahu
14.1 Introduction
14.2 Data Mining Process
14.3 Network Architecture and Evaluation
14.4 Results Validation
14.4.1 Methods of Network Pharmacology Research
14.4.2 Methodology
14.4.3 Integrating the Molecular Disease Network with the Pharmacological Network of the Potential Drugs
14.4.4 Network Pharmacology’s Therapeutic Implications
14.5 Conclusion
References
15. Experimental Models for Drug Repurposing in Viral Hepatitis: Applications of In Vitro and In Vivo Methodologies
Amit Talukdar and Arpita Devi
15.1 Introduction
15.1.1 Current Diagnosis for Viral Hepatitis and Its Treatments
15.1.2 Limitations of Current Treatments and Rationale for Drug Repurposing
15.2 Strategies for Drug Repurposing: On-Target, Off-Target and Combination-Target Strategies
15.3 In Vitro Models for Testing Repurposed Drugs against Viral Hepatitis
15.3.1 Two-Dimensional (2D) Cell Culture Systems
15.3.2 Hepatoma-Derived Cell Lines
15.3.3 HepaRG Cell Line
15.3.4 NTCP-Overexpressing Hepatoma Cell Lines
15.4 Three-Dimensional (3D) Cell Culture Systems
15.4.1 Hepatic Spheroids
15.4.2 Stem-Cell Derived Hepatic Organoids
15.5 In Vivo Models for Testing Repurposed Drugs against Viral Hepatitis
15.5.1 Chimpanzees
15.5.2 Macaques
15.5.3 Tamarins
15.5.4 Tupaias and Rodents
15.5.5 Woodchucks (Groundhogs)
15.5.6 Mongolian Gerbils (Desert Rats)
15.5.7 Mice
15.5.8 Pigs and Rabbits
15.5.9 Chickens
15.5.10 Other Small Animals
15.6 Regulatory and Ethical Considerations for Repurposed Drugs
15.7 Conclusion and Future Perspectives
Bibliography
16. The Immunogenetic Landscape of Viral Hepatitis: Determinants of Persistence and Pathogenesis
Amrita Chakrabarti and Jawahar Kopparam
16.1 Introduction
16.2 Host–Pathogen Interactions in Viral Hepatitis
16.3 Hepatitis A Virus (HAV)
16.3.1 Epidemiology of Hepatitis A Virus
16.3.2 Genetic Landscape of Hepatitis A Virus
16.3.3 Innate Immune Response
16.3.4 Adaptive Immune Response
16.4 Hepatitis B Virus (HBV)
16.4.1 Epidemiology of Hepatitis B Virus
16.4.2 Genetic Landscape of Hepatitis B Virus
16.4.3 Innate Immune Response to HBV
16.4.4 Adaptive Immune Response to HBV
16.5 Hepatitis C Virus (HCV)
16.5.1 Epidemiology of Hepatitis C Virus
16.5.2 Genetic Landscape of Hepatitis C Virus
16.5.3 Innate Immune Response of HCV
16.5.4 Adaptive Immune Response of HCV
16.6 Hepatitis D: The Satellite Virus of HBV
16.6.1 Epidemiology of Hepatitis D Virus
16.6.2 HDV Acquisition and Associated Disease Outcomes
16.6.3 Genetic Landscape of Hepatitis D Virus
16.6.4 Innate Immune Response of HDV
16.6.5 Adaptive Immune Response of HDV
16.7 Hepatitis E
16.7.1 Epidemiology of Hepatitis E Virus
16.7.2 Genetic Landscape of Hepatitis E Virus
16.7.3 Innate Immune Response of HEV
16.7.4 Adaptive Immune Response of HEV
16.8 HCC Development
16.8.1 Immune Mechanisms Fueling HBV-Related HCC
16.8.2 Immune Mechanisms Fueling HCV-Related HCC
16.9 Current Therapies and Limitations
16.10 Conclusions and Future Perspectives
References
17. Future Perspectives in Hepatitis Disease
Yamini Thakur and Om Prakash Gaure
17.1 Introduction
17.2 The Unresolved Challenges of Chronic Hepatitis
17.3 Traditional and Emerging Therapeutic Gaps
17.4 Vision for a Transformative Future
17.5 Advances and Emerging Trends in Hepatitis Disease
17.5.1 Gene- and RNA-Editing Technologies
17.5.1.1 mRNA Therapeutic Platforms
17.5.2 Epigenetic Modulation
17.5.3 Vaccines and Immunotherapeutics in the Next Generation
17.5.4 AI, Multi-Omics, and Precision Medicine
17.5.5 Microbiome and the Gut–Liver Axis
17.5.6 Advanced Delivery: Nanocarriers and Nanotheranostics
17.5.7 Global Health Equity and Access
17.5.8 Ethical, Safety, and Regulatory Frontiers
17.5.9 Integration of Natural Compounds with Advanced Technologies
17.6 Conclusion
References
Index
Back to Top