구조 및 면역정보학적 접근을 통한 구제역 바이러스 (FMDV) 치료법 및 소 내재면역 반응 연구 = Structural and Immunoinformatic Insights into FMDV Therapeutics and Bovine Innate Immune Response

다국어 초록 (Multilingual Abstract)

Foot-and-Mouth Disease Virus (FMDV) is a highly contagious pathogen causing devastating economic losses worldwide in the livestock industry, affecting cloven-hoofed animals such as cattle, sheep, goats, and pigs. The virus’s widespread transmission, high mutation rates, multiple serotypes, and complex host-pathogen interactions present significant challenges for effective control. This thesis begins by reviewing (Chapter 1) the epidemiology, molecular biology, and pathogenesis of FMDV, including the structural and genomic organization of the virus, mechanistic roles of its structural and non-structural proteins in modulating host innate immune responses, and current diagnostics and control strategies. The limitations of existing vaccines and antiviral therapies are discussed, highlighting the urgent need for innovative, serotype-specific, and mechanism-informed therapeutic approaches.
The central objective of this research is to develop integrated structural bioinformatics and immunoinformatic strategies to target FMDV, especially focusing on the critical role of the 3C protease (3Cpro) in viral replication and pathogenesis in serotype O, alongside investigating host innate immune factors such as the bovine MDA5 receptor. The research objectives are: (i) to identify potential natural inhibitors of 3Cpro using structure-based virtual screening and molecular dynamics simulations; (ii) to decipher the structural dynamics induced by active site mutations within 3Cpro and their effects on enzyme activity; (iii) to design a multi-epitope vaccine candidate leveraging immunoinformatics tailored to bovine immune responses; and (iv) to evaluate the functional impact of missense variants in bovine MDA5 on antiviral signaling through computational approaches.
Chapter 2 of the thesis used a large dataset of 69,040 natural compounds from the InterBioScreen and emplyoed structure-based virtual screening method by targeting 3C protease collection. Out of these, five compounds—STOCK1N-62634, STOCK1N-96109, STOCK1N-94672, STOCK1N-89819, and STOCK1N-80570—were found to have strong binding affinities to the target 3C protease, with docking scores of −9.576, −8.1, −7.744, −7.647, and −7.778 kcal/mol, respectively. These promising hits were further evaluated for their drug-likeness based on physicochemical properties, and their electronic features were analyzed using density functional theory (DFT). The dynamic stability and binding behavior of these complexes were then extensively characterized through extensive 300-nanosecond molecular dynamics (MD) simulations. The assessment included analyses such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), hydrogen bonding patterns, principal component analysis (PCA), and the mapping of the free energy landscape (FEL). Furthermore, the binding free energies, calculated by the MM-PBSA method, indicated that all five compounds, most notably STOCK1N-62634, STOCK1N-96109, and STOCK1N-94672, demonstrated potent inhibitory interactions with the 3C protease. These findings provide promising antiviral candidates for further experimental investigation and potential therapeutic development.
Chapter 3 investigates the consequences of active site mutations (notably C142L and C142S) on the structural integrity and dynamic behavior of 3Cpro using all-atom MD simulations. The replication cycle of FMDV and related picornaviruses relies heavily on the 3Cpro, a viral enzyme responsible for cleaving a large polyprotein precursor at precise sites to produce functional viral proteins. Owing to its essential contribution to viral maturation and pathogenesis, 3Cpro has emerged as a prominent target for antiviral drug development targeting FMDV. Within 3Cpro, the β-ribbon region (amino acids 138–150), which houses the catalytically important Cys142 (C142) residue, is notably conserved among viral strains and plays a substantial role in substrate recognition and enzymatic specificity. Prior experimental studies have revealed that mutations at C142 (e.g., C142S and C142L) influence the function of the protease, yet a comprehensive understanding of how these active-site modifications alter the enzyme’s intrinsic dynamics and structural transitions has remained elusive. Such knowledge is crucial for the rational design of effective and selective 3Cpro inhibitors. To bridge this gap, we performed extensive MD simulations, including multiple replicates for both the wild-type (WT) and mutant (C142S and C142L) 3Cpro proteins. The simulation results revealed that the C142S mutant, in particular, induces prominent structural rearrangements in the protease compared to the WT and the C142L variant. Analyzing the essential dynamics demonstrated that the mutational effects extend well beyond the active site, leading to substantial differences in global protein motions relative to the wild-type enzyme. Furthermore, cross-correlation analysis highlighted a consistent pattern of anti-correlated motions between specific regions of the WT and C142L mutant, suggesting preserved long-range communication networks within these variants. Complementary residue interaction network analysis, focusing on betweenness centrality, identified common residue nodes involved in intra-molecular signaling across all three forms, underscoring invariant pathways for allosteric communication. The most striking finding was that the C142S mutation is likely to alter the conformation and flexibility of the β-ribbon, causing this region to occlude the catalytic pocket—a motion predicted to reduce enzymatic activity through impaired substrate access. Similarly, the C142L substitution, while less dramatic, still modulates β-ribbon architecture and could influence substrate engagement during catalysis, in concordance with previous biochemical observations. Overall, this chapter provides new insights into the conformational and dynamic behaviors of FMDV 3Cpro and its clinically relevant mutants, highlighting the structural plasticity of the β-ribbon and its impact on protease function. These results pave the way for structure-aided inhibitor design, offering a mechanistic foundation for developing targeted antiviral therapies against foot-and-mouth disease.
Chapter 4 integrates structural and immunoinformatic methodologies to rationally design a multi-epitope vaccine (MEBV) against FMDV. FMDV poses a significant challenge for vaccine development due to its high genetic variability and multiple circulating serotypes. Traditional inactivated vaccines require constant updating and may lack broad protective efficacy. To address these limitations, this chapter presents the computational design and evaluation of a multi-epitope-based vaccine (MEBV) specifically tailored for FMDV, with emphasis on bovine leukocyte antigen (BoLA) allele compatibility for optimal immune response in cattle. Using advanced immunoinformatic tools, non-toxic, antigenic, and non-allergenic epitopes were identified and assembled with immunostimulatory adjuvants including β-defensin 3 and PADRE sequences, interconnected by suitable linkers to enhance vaccine stability and immunogenicity. Molecular docking and molecular dynamics simulations confirmed the MEBV’s stable and strong binding interactions with key immune receptors TLR3 and TLR7, essential for initiating innate immunity. Immune simulation further predicted robust activation of B-cell and T-cell responses, along with increased cytokine and macrophage levels, maintaining elevated expression of IFN-γ and IL-2 over time. Codon optimization for Escherichia coli K12 expression was performed to facilitate experimental production, accompanied by in silico cloning to demonstrate practical scalability. Overall, this computationally designed MEBV exhibits promising immunogenic properties and broad coverage against diverse FMDV strains, positioning it as a viable candidate for further experimental validation and development. Epitope prediction prioritized antigenic, non-allergenic sequences targeting cattle-specific BoLA alleles. The vaccine construct, enhanced with β-defensin 3 adjuvant and immune-stimulatory linkers, exhibits predicted structural stability and strong binding affinity to toll-like receptors (TLR3 and TLR7), validated by docking and molecular dynamics. Immune simulations indicate robust humoral and cellular responses, suggesting the candidate’s potential efficacy pending confirmation via experimental validation and scale-up production protocols. This chapter underscores the potential of epitope-based vaccine strategies to advance FMD control by overcoming the shortcomings of traditional vaccines and offering cost-effective, targeted solutions for disease management in livestock.
Chapter 5 explores the bovine melanoma differentiation-associated protein 5 (MDA5) receptor’s innate immune role in detecting viral dsRNA and triggering antiviral pathways. The bovine IFIH1 gene, which encodes MDA5, is a major part of antiviral innate immunity in cattle and mediates recognition of long, double-stranded viral RNA, particularly against picornaviruses like FMDV. To elucidate the functional significance of naturally occurring IFIH1 variants, we performed a comprehensive survey of SNPs in the core MDA5 and identified 106 missense variants through database mining and in silico prediction tools. Eighteen of those variants were consistently classified as deleterious, with G490D, I507V, I717M, and L729H mapping to highly conserved, functionally essential residues. MD simulations of wild-type and mutant dsRNA-bound MDA5 variants, particularly I717M and G490D, induced increased backbone fluctuations and reduced structural adaptability based on essential dynamics analysis. Moreover, the domain-based RMSF profiling highlighted enhanced local flexibility in key helicase and C-terminal regions, correlating with weakening of dsRNA contacts in MDA5 variants. Although the dsRNA itself remained stably accommodated in its binding pocket, the mutant proteins consistently showed compromised domain closure and altered residue interactions that would facilitate RNA sensing oligomeric filament formation. These results reveal the molecular basis by which deleterious IFIH1 nsSNPs disrupt innate immune signaling in cattle and emphasize their potential role in disease resistance and livestock health. Furthermore, this study aids rational genetic selection and provides a framework for further structure-based interventions to maximize antiviral immunity in agriculture and livestock industries.
Together, this thesis presents an integrated, multi-disciplinary framework combining structural biology, computational chemistry, immunoinformatics, and molecular genetics to combat FMDV more effectively through precision livestock therapeutics. From identifying natural antiviral compounds and elucidating mutation-induced structural dynamics of viral targets to innovating multi-epitope vaccine designs and decoding host immune receptor variant functionality, this work bridges fundamental research with translational potential. The novel findings advocate for holistic approaches that consider viral mutation landscapes, host immune variability, and advanced computational methodologies to innovate sustainable and effective control measures against FMDV, ultimately safeguarding livestock health, productivity, and global economic stability.

목차 (Table of Contents)

• Chapter 1 General Introduction 1
• 1.1. Foot-and- Mouth Disease Overview 2
• 1.2. History, Global trends and Serotypes' distribution 3
• 1.3. Transmission of FMDV 5
• 1.4. Life cycle and Pathogenesis 7
• 1.5. Host-Pathogen Interaction and Innate Immune responses 11
• 1.6. Structure and Genomic organization of FMDV 16
• 1.7. FMDV Proteins Regulate Host Innate Immunity 17
• 1.7.1. Structural Proteins and Their Impact on Host Innate Immune Regulation 18
• 1.7.1.1. FMDV VP1-Mediated Suppression of Innate Immunity 18
• 1.7.1.2. FMDV VP3-Mediated Suppression of Innate Immunity 20
• 1.7.1.3. FMDV VP4-Mediated Suppression of Innate Immunity 21
• 1.7.2. Non-Structural Proteins and Their Impact on Host Innate Immune Regulation 21
• 1.7.2.1. FMDV Lpro-Mediated Suppression of Innate Immunity 22
• 1.7.2.2. FMDV 3Cpro-Mediated Suppression of Innate Immunity 24
• 1.7.2.3. Advances in FMDV 2B Suppressing Innate Immunity 25
• 1.7.2.4. Advances in FMDV 3A Suppressing Innate Immunity 26
• 1.7.2.5. Role of Other FMDV Proteins in the Regulation of Host Innate Immunity 27
• 1.8. Diagnosis of FMDV 28
• 1.9. Implementation of FMD control 30
• 1.10. FMD Vaccines 30
• 1.10.1.1. Inactivated (killed) vaccines 31
• 1.10.1.2. Live attenuated vaccines 31
• 1.10.1.3. Subunit vaccines 32
• 1.10.1.4. Vectored vaccines 32
• 1.10.1.5. DNA vaccines 33
• 1.10.1.6. Virus-like particle (VLP) vaccines 33
• 1.10.2. Advancement in Antivirals targeting FMDV 34
• 1.10.2.1. Small molecule inhibitors 34
• 1.10.2.2. Biologics 37
• 1.10.2.3. Natural products 38
• 1.10.2.4. RNA-based strategies 39
• 1.10.3. Challenges in developing antivirals against FMDV 40
• 1.11. Objective of this Research Work 41
• 1.12. Theory and Methodology 42
• 1.12.1. Structure Prediction 42
• 1.12.2. Molecular Modeling in Drug Design 42
• 1.12.3. Molecular Docking concept and workflow 43
• 1.12.4. Force field-based working 44
• 1.12.4.1. Empirical scoring 44
• 1.12.4.2. Machine Learning augmented scoring 46
• 1.12.5. Force fields 46
• 1.12.6. The Periodic Boundary Conditions 49
• 1.12.7. The Solvation of modelled system 51
• 1.12.8. The truncation of Potentials 51
• 1.12.8.1. The non-bonded interactions 51
• 1.12.8.2. The Long-Range Forces 51
• 1.12.9. Energy Minimization 53
• 1.12.9.1. The Steepest descent algorithm 54
• 1.12.9.2. The Conjugate gradient algorithm 55
• 1.12.10. The Molecular Dynamic Simulations 56
• 1.12.10.1. The Newtonian Motion 56
• 1.12.10.2. The Finite difference method 57
• 1.12.10.2.1. Verlet algorithm 57
• 1.12.10.2.2. The Leap-frog algorithm 58
• 1.12.10.3. The Time steps 58
• 1.12.10.4. The MD simulations at various conditions 59
• 1.12.11. The general MD protocol 60
• 1.12.12. The MD trajectory analyzes 60
• 1.12.12.1. Basic analyzes 60
• 1.12.12.2. Principal Component Analysis (PCA) 61
• 1.12.12.3. Root mean square inner product 62
• 1.12.12.4. Free energy landscape analysis 63
• 1.12.12.5. Secondary structure analysis 63
• 1.12.12.6. Mode vector analysis 64
• 1.12.12.7. The binding energy analysis 64
• 1.13. References 66
• Chapter 2 Structure-based virtual screening and molecular dynamics studies to explore potential natural inhibitors against 3C protease of foot-and-mouth disease virus 99
• 2.1. Introduction 100
• 2.2. Theory and Methods 102
• 2.2.1. Preparation of target protein 102
• 2.2.2. Selection of natural compounds 103
• 2.2.3. Structure-based virtual screening 103
• 2.2.4. Density functional theory calculation 104
• 2.2.5. Molecular dynamics simulation 104
• 2.2.6. Binding free energy calculationI 105
• 2.3. Results 106
• 2.3.1. Identification of potent inhibitors through SBVS 106
• 2.3.2. Assessment of drug-likeness through physiochemical properties 108
• 2.3.3. Quantum mechanics 110
• 2.3.4. Molecular dynamics simulation analysis 112
• 2.3.5. Principal component analysis-based free energy landscape 114
• 2.3.6. Binding free energy analysis 116
• 2.4. Discussion 119
• 2.5. Conclusion 123
• 2.6. Supplementary 124
• 2.7. References 126
• Chapter 3 Elucidating the structural dynamics induced by active site mutations in 3C protease of foot-and-mouth disease virus 133
• 3.1. Introduction 134
• 3.2. Materials and Methods 135
• 3.2.1. Structural preparation of WT and mutants of 3Cpro 135
• 3.2.2. Molecular dynamics simulation 137
• 3.2.3. Principal Component Analysis (PCA) 137
• 3.2.4. Residue Interaction Networks (RIN) 138
• 3.3. Results and Discussions 138
• 3.3.1. Structural dynamics and stability of WT and mutants of 3Cpro 139
• 3.3.2. Residual flexibility and change in secondary structure analysis 142
• 3.3.3. EEssential dynamics of WT and mutants of 3Cpro 144
• 3.3.4. Cross-correlation analysis 148
• 3.3.5. Between centrality analysis 149
• 3.4. Conclusion 152
• 3.5. Supplementary 154
• 3.6. References 157
• Chapter 4 An integrated Structural and Immunoinformatic Approach to Design a Multi-epitope Based Vaccine against the Foot-and-Mouth Disease Virus 164
• 4.1. Introduction 165
• 4.2. Methods 166
• 4.2.1. Foot-and-mouth disease virus retrieval 166
• 4.2.2. B-cell prediction 167
• 4.2.3. MHC-I specific CTL epitope prediction 167
• 4.2.4. MHC-II specific HTL epitope prediction 168
• 4.2.5. Epitope toxicity prediction 168
• 4.2.6. Construction and physiochemical characterization of the mutli-epitope-based vaccine 169
• 4.2.7. Molecular Docking 170
• 4.2.8. Molecular dynamics simulations 170
• 4.2.9. Codon optimization and in silico cloning 171
• 4.2.10. Immune response simulations 171
• 4.3. Results 171
• 4.3.1. Retrieval and evaluation of structural proteins 171
• 4.3.2. Prediction of B-cell epitopes 172
• 4.3.3. Prediction of cytotoxic and helper T-lymphocyte epitopes 172
• 4.3.4. Desiging the final multi-epitope-based vaccine subunit 173
• 4.3.5. Binding interactions of the multi-epitope-based vaccine with TLRs 175
• 4.3.6. Structural stability assessment during MD simulations 176
• 4.3.7. Binding free energy and interaction energies between the multi-epitope-based vaccine with TLRs 178
• 4.3.8. Immune simulation 180
• 4.3.9. In silico cloning 181
• 4.4. Discussion 182
• 4.5. Conclusion 185
• 4.6. Supplementary 186
• 4.7. References 197
• Chapter 5 Computational insights into the functional impact of missense variants on Bovine MDA5 receptor: A study on dsRNA Recognition and Response 207
• 5.1. Introduction 208
• 5.2. Materials and Methods 211
• 5.2.1. Collection of datasets 211
• 5.2.2. Identification of deleterious nsSNPs 211
• 5.2.3. Prediction of destabilizing nsSNPs 212
• 5.2.4. Conservatioin profile of MDA5 212
• 5.2.5. Structural preparation of dsRNA-bound MDA5 wild-type (WT) and selected variant complexes 213
• 5.2.6. MD simulation 213
• 5.3. Results 214
• 5.3.1. Identified Deleterious and Destabilized nsSNPs in MDA5 214
• 5.3.2. Residual Conservation profile of MDA5 215
• 5.3.3. Structural impact assessed via MD simulation 215
• 5.3.4. Essential Dynamics analysis of MDA5 218
• 5.3.5. Free energy landscape (FEL) analysis of MDA5 variants 220
• 5.3.6. Residual fluctuations induced by MDA5 variants 223
• 5.3.7. Interaction of dsRNA with MDA5 variants 224
• 5.4. Discussion 226
• 5.5. Conclusion 229
• 5.6. Supplementary 230
• 5.7. References 237
• Appendix 249
• 초록 251
• Acknowledgment 256