Genotype-Resolved NS5 Stability Predicts Japanese Encephalitis Virus Fitness

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This study evaluated how sequence differences among JEV genotypes G1–G5 shape NS5 stability and, in turn, replication potential. A unified in silico workflow combined physicochemical profiling, residue-level substitution mapping, and atomistic molecular dynamics to compare structural stability and conformational behavior across genotypes, with a focus on substitutions predicted to modulate enzymatic performance. Analyses revealed that G5 NS5 maintains a balanced electrostatic environment and persistent hydrogen-bonding networks, yielding greater structural stability than other genotypes. In contrast, G4 NS5 presented a charge imbalance and reduced stability. Simulations consistently supported the robustness of G5 dynamics, with specific substitutions—including Y65, M59, E182, and T191—contributing to improved packing, favourable local interactions, and putative gains in catalytic efficiency. These molecular attributes align with heightened replication capacity and provide a mechanistic rationale for the recent prominence of G5 strains relative to G1–G4. Comprising together, our results demonstrate that genotype-linked substitutions in NS5 directly influence protein stability, replication efficiency, and adaptive potential. Translationally, prioritizing G5-informed NS5 features may guide the design of small-molecule inhibitors and vaccine antigens with broader protective value. More broadly, the presented computational pipeline enables rapid, genotype-aware assessment of protein stability and function in emerging viral lineages, supporting genomic surveillance, risk stratification, and the rational development of broad-spectrum antivirals. Non-structural protein-5(NS5) Japanese Encephalitis (JE) Structure modeling MD Simulation Residue-level substitution Figures Figure 1 Figure 2 Introduction Japanese encephalitis (JE) is a zoonotic disease that causes encephalitis in individuals across Asia, Australia, and the Western Pacific. Transmission is most common in agricultural settings such as farms and rice fields, though it can occasionally occur in urban areas. Although many infections go unnoticed, those that do cause illness often come with noticeable symptoms, with severe complications, including high fever, headache, confusion, coma, tremors, and altered mental states caused by brain inflammation [ 1 ]. JE leads to an estimated 68,000 symptomatic cases annually, with approximately 17,000 fatalities. The infection also affects the central nervous system (CNS), leading to seizures and death in severe cases. Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus related to dengue, Zika, Yellow Fever, and West Nile viruses. The first recognized JE case was reported in Japan in 1871, and outbreaks remain a persistent global public-health concern [ 2 ]. JEV is transmitted primarily by Culex tritaeniorhynchus mosquitoes; waterbirds (especially Ardeidae) act as reservoir hosts, pigs serve as amplifying hosts, and humans are dead-end hosts with no human-to-human transmission [ 3 ]. The ~ 11-kb, single-stranded positive-sense RNA genome encodes a single polyprotein that is cleaved into structural (C, prM, E) and non-structural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, NS5) proteins. As a positive-sense RNA virus, JEV delivers an infectious genome that functions directly as mRNA, enabling immediate translation of viral proteins and rapid initiation of replication and virion assembly [ 4 ]. Among these proteins, NS5 is pivotal for replication and uniquely combines an N-terminal methyltransferase (MTase) with a C-terminal RNA-dependent RNA polymerase (RdRp). Together, these domains drive RNA synthesis and 5′ capping and are especially critical for efficient replication in the central nervous system [ 5 ]. The RdRp is organized into finger, palm, and thumb subdomains that coordinate RNA binding, catalysis, and processivity [ 6 ]. Beyond its enzymatic roles, NS5 interfaces with host pathways: it binds the mitochondrial trifunctional protein (MTP), disrupting long-chain fatty-acid metabolism and potentially provoking pro-inflammatory cytokine release that can worsen disease and facilitate viral spread [ 7 ]. NS5 also antagonizes type I interferon signaling by blocking activation of key transcription factors, including IRF3 and NF-κB, thereby blunting the host antiviral response [ 8 ]. Structural studies have mapped inhibitor-binding pockets on NS5, providing a strong foundation for structure-based antiviral discovery [ 9 ]. Genetically, JEV is divided into five genotypes—G1 through G5—each distinguished by unique evolutionary backgrounds, geographical ranges, and host-vector associations, as determined through genome analysis [ 10 , 11 ]. Since the 1990s, G1 has emerged as the dominant genotype across much of Asia, whereas G3 was historically more widespread. G2 and G5 represent older genotypes with more limited geographic presence [ 12 , 13 , 14 ]. Despite JEV being a single serotype, shifts in genotype dominance have been observed over time, and in some regions, genotype distribution remains poorly documented [ 5 ]. Phylogenetic analysis suggests that the genotypes evolved in the following order: G5, G3, G2, G1, and finally G4. Genotype 4 (G4) is considered the most recent lineage, having emerged approximately 122 years ago (with a 95% highest posterior density [HPD] interval of 57–233 years). The G4 lineage also exhibits a high mutation rate, with a mean substitution rate of 1.145 × 10⁻³ (95% HPD: 9.55 × 10⁻⁴ to 1.35 × 10⁻³), placing it among the rapidly evolving viruses [ 16 ]. This study investigates how genotype-specific amino acid substitutions alter the structure and stability of the NS5 protein across Japanese encephalitis virus (JEV) genotypes G1–G5, and addresses a simple yet unresolved question: Does NS5 stability contribute to explaining why some strains sustain higher viral loads—and thus greater fitness—than others? Although NS5 is central to replication, its stability–fitness contribution remains poorly quantified and the key residues governing genotype-dependent stability are unknown. To close this gap, we introduce a streamlined, genotype-aware computational workflow that rapidly profiles NS5 stability and conformational shifts from curated sequence accessions. By pinpointing residue changes that tune stability, our analysis links molecular architecture to replication efficiency, transmissibility, and potential disease severity. While optimized for JEV, the approach generalizes to other flaviviruses, offering a practical path to identify stability-driven vulnerabilities and to inform targeted antivirals and vaccine designs aimed at curbing pathogenicity and reducing JEV-associated morbidity and mortality. Materials and Methods 2.1 Data Retrieval and NS5 protein sequence alignment A comprehensive database search was conducted to screen the most recent JEV genotypes, reflecting current epidemiological trends, and analyze the structural stability and conformational changes of NS5 proteins across the screened JEV genomes. The accession numbers are listed in Table .1 , which were considered from human cerebrospinal fluid samples, the primary site of viral replication [ 17 ]. The NS5 protein regions were retrieved and extracted from the GenBank Database ( https://www.ncbi.nlm.nih.gov/ ), followed by sequence alignment performed using Clustal Omega ( https://www.ebi.ac.uk/jdispatcher/msa/clustalo ) to examine key conserved and variable regions. Table 1 Accession numbers of JEV genomic sequences used in this study GenBank Accession Organism Genotypes (G) Year Tissue Strain Country QKI86564.1 Homo sapiens 1 2018 Cerebrospinal fluid NX1889 China AAF73859.1 Homo sapiens 2 1995 Cerebrospinal fluid FU Australia AFP33182.1 Homo sapiens 3 2010 Cerebrospinal fluid IND-WB-JE2 India UYD39327.1 Homo sapiens 4 2021 Cerebrospinal fluid JEV/Human/NT_Tiwi Australia WXB51294.1 Homo sapiens 5 2015 Cerebrospinal fluid NCCP 43279 South Korea 2.2 NS5 Protein Sequence Examination: Primary Structure Insights The retrieved NS5 protein sequences of each of the five genotypes—G1, G2, G3, G4, and G5 of similar length (905 amino acids)—were analyzed to deduce the primary sequence information using ExPASy-ProtParam ( https://web.expasy.org/protparam/ ), which computes various physical and chemical parameters for a user-entered protein sequence. The computed parameters include molecular weight, amino acid composition, atomic composition, and grand average of hydropathicity (GRAVY). ProtParam provided crucial insights into various aspects of the primary structure of the NS5 proteins from G1 to G5, which are essential for elucidating their basic structure. 2.3 Structure Modeling of NS5 Protein Across the Genotypes Structure modeling of NS5 across genotypes 1 to 5 was conducted using MODELLER [ 18 ]. Template selection was performed through BLASTp searches against the PDB database by utilizing the respective sequences, which identified a suitable template, NS5 from a related flavivirus (PDB ID: 4k6m). The selected template was employed for NS5 modeling across multiple genotypes. Models exhibiting the most favourable DOPE scores, as computed by MODELLER, were prioritized for downstream analyses. Structural integrity was then verified via Ramachandran plot assessment using PROCHECK ( https://saves.mbi.ucla.edu/ ). 2.4 Molecular Dynamics (MD) Simulation Molecular dynamics simulations were executed utilizing the GROMACS 2024.4 platform [ 19 ] with the CHARMM36[ 20 ] force field to evaluate the structural stability, flexibility, and compactness of the NS5 proteins across the five JEV genotypes [ 21 , 22 ]. The system was prepared using the Ewald Particle Mesh method to calculate electrostatic forces over a distance [ 23 ]and placed into a solvation box hydrated using the TIP3P model, followed by the addition of Na + and Cl − ions to neutralize the system [ 24 ]. Steric conflicts were minimized with 50,000 steps of steepest descent (SD) energy minimization. The LINCS algorithm [ 25 ] was utilized to constrain all hydrogen bonds, ensuring system stability. The system was then equilibrated using the NVT ensemble with a timestep of 2 fs at 310 K for 100 ps, followed by pressure equilibration under the NPT ensemble for 1 ns at 310 K and 1 atmosphere using the Parrinello-Rahman pressure coupling method [ 26 ]. Temperature coupling was maintained using the velocity-rescaling method (Bussi, Donadio, and Parrinello, n.d..). The simulation was executed for 100 ns (100,000 ps) during the production phase. Key structural parameters, including Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF), were calculated using GROMACS to assess conformational stability and residue fluctuation among the NS5 proteins. Additionally, hydrogen bond analysis was performed to evaluate interactions contributing to the protein’s structural integrity Results 3.1 Sequence determination of the NS5 protein among the genotypes The sequence determination of the NS5 protein among JEV genotypes reveals variations in molecular weight, charge distribution, and hydropathicity, which influence structural stability and function ( Table 2 ) . Molecular weight affects protein inertia and movement dynamics, with G3 having the highest molecular weight (103,353.93 Da) and G5 the lowest (103,191.70 Da). Electrostatic interactions, crucial for protein folding and stability, are influenced by the distribution of charged amino acids. The total number of negatively charged residues (Asp and Glu) varies among genotypes, with G3, G4, and G5 containing 119, G1 having 116, and G2 with 118. Similarly, positively charged residues (Arg and Lys) are highest in G4 (132), while G1 has 129, and G2, G3, and G5 each contain 130. Hydropathicity, measured by the Grand Average of Hydropathicity (GRAVY) score, indicates the protein’s overall hydrophobic or hydrophilic nature. The GRAVY values for G1, G2, G3, G4, and G5 are − 0.514, -0.527, -0.533, -0.543, and − 0.528, respectively, confirming that all NS5 proteins are hydrophilic, which influences their engagement with cellular machinery and associated processes. Table 2 Physicochemical properties of the NS5 protein across JEV genotypes 1 to 5 JEV genotypes Parameters G1 G2 G3 G4 G5 Molecular weight (Da) 103200.88 103275.84 103353.93 103330.84 103191.70 Total no. of negatively charged residues (Asp + Glu) 116 118 119 119 119 Total number of positively charged residues (Arg + Lys) 129 130 130 132 130 Total number of atoms 14424 14431 14434 14435 14392 Grand average of hydropathicity -0.514 -0.527 -0.533 -0.543 -0.528 3.2 Key Residue Differences in the RdRp and MTase Domains Across JEV Genotypes In the RdRp domain, genotype 5 (G5) carries a distinctive set of substitutions that plausibly reshape local packing, electrostatics, and catalytic behavior. At positions 17, 65, and 182, G5 encodes T17, Y65, and E182, whereas other genotypes more typically harbor A17, H65, and R182 (S1). The bulkier, aromatic Tyr65 (vs His65) can perturb nearby hydrophobic packing and thus modulate polymerase stability, while the charge reversal at 182 (Glu replacing Arg) risks disrupting salt bridges and hydrogen-bond networks that help maintain structural integrity. These shifts occur near functionally sensitive regions and may influence enzyme performance. Consistent with this, G5 presents A51/V52, whereas other genotypes show S/A or conserved A/V; the hydrophobic Val52 in G5 could alter contacts with the RNA backbone, with potential consequences for RNA binding and catalytic efficiency. Additional substitutions at positions 265–267 in G5 (A/V/G) differ from S/T/D in other genotypes (S2). Because these residues likely sit close to the active site, such changes could tune substrate interactions or local flexibility. At position 316, G5 carries Gln in place of histidine or leucine found in other genotypes; the loss of His—often a proton donor/acceptor—suggests a shifted catalytic microenvironment. G5 also retains Val at position 344 where others show Ile or Thr; the smaller Val side chain can ease steric crowding and stabilize adjacent loops. A similar pattern appears at position 118: G5 (along with G3 and G1) has Ile, whereas G4 and G2 carry Val; the larger Ile can promote tighter hydrophobic packing and improved local stability. Notably, analogous genotype-specific divergence extends into the methyltransferase (MTase) domain, indicating that these structural and functional adjustments are not confined to a single NS5 subdomain. At position 191( S3 ), G5 features threonine instead of valine, introducing a hydroxyl group that may create polar interactions or hydrogen bonds, alter local stability and possibly affect substrate binding. Genotype 5 (G5) also exhibits a methionine substitution at position 59, replacing the leucine found in other genotypes. Due to methionine’s sulfur-containing side chain, this change may impact regional flexibility or alter local hydrophobic interactions. G5 keeps lysine at position 9, while G4 has arginine. The shorter side chain of lysine may slightly affect binding kinetics with the methyl donor S-adenosylmethionine (SAM), although both residues are positively charged. At position 149, there is even another significant difference: G5 encodes aspartic acid rather than glutamic acid, which is what other genotypes encode. The protein's interaction with the RNA cap structure may be influenced by aspartic acid's shorter side chain. G5 substitutes valine for leucine at position 213, which is a conservative move between two hydrophobic residues but could somewhat alter the geometry of the cap-binding pocket. When combined, these G5-specific amino acid alterations point to complex impacts on enzyme performance, protein stability, and structural flexibility. Such alterations may reflect evolutionary adaptations aimed at improving replication efficiency or evading host immune responses. 3.3 Molecular Dynamics of NS5 Protein Reveal Enhanced Structural Stability in JEV Genotype 5 Molecular dynamics techniques elucidate the complexities of the structural dynamics of the NS5 protein across five JEV genotypes in a solvent environment. RMSD, RMSF, and hydrogen bond analyses reveal critical differences in conformational stability. RMSD analysis indicates that Genotype 4 ( Fig. 1 d ) exhibits the highest deviations over time, particularly after 10 ns, suggesting increased flexibility and potential structural instability. In contrast, G1 ( Fig. 1 a ) shows deviations after 80 ns in the C-terminal region, while G2 ( Fig. 1 b ) also fluctuates from its native form. Meanwhile, G3 and G5 maintain relatively stable RMSD values ( Fig. 1 c & 2 d ) , indicating greater structural integrity and a more preserved conformation. RMSF analysis further supports these findings by highlighting residue-level flexibility. G4 displays higher fluctuations, particularly in the RdRp domain, Mtase, and N-terminal regions, which could affect its functional stability. Meanwhile, G2 exhibits moderate fluctuations, whereas G3 and G5 show the lowest fluctuations, suggesting a more compact and stable structure ( Fig. 2 a ) . The increased flexibility observed in G4 may contribute to its overall instability, potentially affecting its function within the viral replication process. Assessing hydrogen bonds provides deeper insight into NS5 stability, since more consistent bonds usually reflect stronger structural resilience. Genotype 4 likely forms fewer stable hydrogen bonds, contributing to increased fluctuations and structural deviations, as reflected in its higher RMSD and RMSF values. In contrast, Genotypes 2 and 3 maintain a stronger hydrogen bonding network, stabilizing their structures and reducing fluctuations. This supports the observation that Genotypes 5 and 3 are the most stable, followed by Genotypes 2 and 1, while Genotype 4 is the least stable ( Fig. 2 b ). These structural variations may influence viral replication and interactions with host factors, highlighting the need for further computational and experimental studies. Additionally, the results of the radius of gyration ( Fig. 2 c ) highlighted that Genotype 1 (red) maintains the most compact structure with Rg values of 3.15–3.4 nm for the majority of the simulation, showing exceptional structural stability until a late-simulation expansion around 80,000 ps. Genotype 3 (green) exhibits the highest structural flexibility with Rg fluctuations between 3.1–3.6 nm and dramatic expansion spikes around 40,000 ps and 95,000 ps, indicating increased conformational sampling compared to other variants. Genotypes 2, 4, and 5 display intermediate stability profiles with overlapping Rg ranges, suggesting similar structural compactness and moderate conformational dynamics throughout the 100ns simulation Discussion NS5 is the largest and most conserved non-structural protein encoded by JEV, serving as a cornerstone of the viral replication process. Structurally, it comprises two key domains: the N-terminal methyltransferase (MTase), which facilitates 5’-RNA capping, and the C-terminal RNA-dependent RNA polymerase (RdRp), responsible for synthesizing the viral RNA. Both domains are vital for ensuring effective genome replication. Due to its critical functions and high conservation across flaviviruses, NS5 has been widely recognized as a prime target for antiviral drug development [ 27 ]. Our genotype-specific structural analysis of NS5 across JEV genotypes 1 through 5 uncovered notable differences in characteristics such as molecular weight (MW), compactness, and charge distribution. The molecular weight of NS5 varied from 103,191.70 Da in G5 to 103,353.93 Da in G3—a difference of 162.23 Da. These variations are primarily driven by genotype-specific amino acid substitutions or deletions, underscoring evolutionary pressures at play. Interestingly, there is no clear linear trend in MW changes across genotypes. However, G1 and G5—both genotypes with rising prevalence—tend to encode smaller NS5 proteins compared to G3, G2, and G4. This reduction in mass may contribute to increased structural compactness and enhanced in vivo stability, as compact and well-balanced charge distributions are thought to improve protein resilience [ 28 ]. Moreover, a lighter protein structure could reduce the cellular energy demands of replication, potentially boosting viral replication efficiency [ 29 , 30 , 31 ]. G5 is markedly more compact even though its GRAVY score is less negative (− 0.528, i.e., slightly more hydrophilic on average). This indicates that compactness here is governed less by bulk hydropathy and more by electrostatics: G5’s nearly balanced charge—about 130 positively charged versus 119 negatively charged residues (net + 11)—supports tighter packing through salt bridges and screened repulsions. This agrees with prior work showing that well-distributed electrostatic interactions are central to protein stability [ 32 ]. By contrast, G4 carries a stronger net negative charge that weakens intramolecular attractions, increasing backbone and loop mobility and thereby reducing overall stability—a pattern reported for other structurally dynamic viral proteins [ 33 ]. At the residue level, G5 harbors distinctive substitutions in the RdRp domain: Tyr65 and Glu182 supplant the more commonly conserved His65 and Arg182. These replacements alter side-chain size and charge (steric and electrostatic effects), plausibly shifting local packing, salt-bridge patterns, and active-site microenvironments in ways consistent with prior NS5 analyses across flaviviruses [ 34 ]. Additional changes, such as Ala51 and Val52, may further optimize polymerase–RNA complementarity, improving template engagement and catalytic throughput. In the MTase domain, unique substitutions Thr191 and Met59 introduce opportunities for new hydrogen bonds and strengthened hydrophobic contacts, echoing mechanisms previously linked to enhanced methyltransferase performance [ 35 ]. Molecular-dynamics results reinforce this picture: G5 exhibits lower RMSD (global structural drift) and lower RMSF (per-residue flexibility), indicating higher structural integrity with minimal domain-scale motion. Such reinforced hydrogen-bond networks and reduced fluctuations have been associated with improved replication fidelity [ 36 ]. Functionally, a more stable NS5 lets G5 expend fewer cellular and viral resources on folding and quality control, allocating more toward genome replication—consistent with higher observed viral loads. Conversely, G4’s flexibility may help it sample conformations advantageous for immune evasion, but the same plasticity appears to compromise replication efficiency, reflecting an evolutionary trade-off [ 37 ]. Taken together, the NS5 mutational patterns in G1 and G5 likely confer concrete evolutionary benefits: (i) more efficient enzymatic activity via fine-tuned residue interactions, (ii) greater structural resilience under physiological conditions, and (iii) improved replication fidelity owing to reduced structural fluctuations—all consistent with earlier mechanistic insights for RNA-virus polymerases and capping enzymes [ 38 ]. These traits likely underlie the prevalence and periodic re-emergence of these genotypes, particularly under vaccine-imposed selective pressure. Use of inactivated G3 vaccines may have inadvertently favored genotypes with distinct antigenic and structural profiles—most notably G1 and G5—as hypothesized in vaccine-driven viral evolution studies [ 39 ]. This interpretation is reinforced by convergent signals across our analyses, including radius of gyration (Rg), distinct structural behaviors, and stability patterns observed among all five genotypes. Overall, the data show that protein mass alone does not confer functional advantage; rather, evolutionary shifts in residue composition and charge distribution can recalibrate electrostatics and packing, thereby altering enzyme behavior and replication dynamics. These findings motivate targeted investigations into how such molecular features shape host–virus interactions and immune responses, to inform genotype-aware intervention strategies. In this study, we assessed NS5 stability using complementary readouts—physicochemical profiling, multi-scale RMSD/RMSF metrics, hydrogen-bond network analysis, and Rg measurements from molecular dynamics trajectories. It is essential to highlight that our findings are solely based on computer-aided technology; the genotype-specific substitutions we identified yield clear, testable hypotheses and provide actionable starting points for rational vaccine and antiviral design. Conclusion This study establishes a genotype-aware, in-silico framework that ties specific NS5 substitutions to measurable shifts in conformational and thermodynamic stability—and, by extension, to replication efficiency, pathogenic potential, and viral fitness. Residues Y65, M59, E182, and T191 emerge as stability-shaping levers that explain genotype-level differences and nominate high-value sites for therapeutic intervention. By jointly mapping conserved, function-critical motifs with mutation hotspots, we define actionable targets for broad-spectrum antivirals and epitope-focused vaccines. While the results are computational, they yield clear, testable hypotheses and a prioritized roadmap for wet-lab validation. The workflow generalizes to other flaviviruses and, integrated with genomic surveillance, can accelerate variant triage, sharpen outbreak forecasting, and guide targeted interventions in high-risk settings. Declarations Competing Interest The authors have declared no competing interests. Author Contribution K.P.S conceptualized and designed the study, contributing to the manuscript review and editing. H.T conducted the research, performed data analysis, interpreted the results, and prepared the initial draft of the manuscript. V.R and J.H contributed to the manuscript review and editing, with J.H also providing technical input. N.K assisted with data analysis. A.P and P.P.S were involved in the manuscript review and editing. All authors read and approved the final manuscript. Acknowledgments This work was supported by the National Disease Modelling Consortium, Indian Institute of Technology Bombay [grant number 47013250001]. The authors also wish to acknowledge the Spatial Epidemiological Laboratory and the Director of ICAR-NIVEDI for furnishing the requisite facilities to conduct this work. Additionally, the authors would like to recognize that the research was supported by the Indian Council of Agricultural Research, under the Department of Agricultural Research and Education, Government of India. Data Availability Data is provided within the manuscript or supplementary information files References Muniaraj M, Rajamannar V (2019) Impact of SA 14-14-2 vaccination on the occurrence of Japanese encephalitis in India. Hum Vaccin Immunother. ;15(4):834-840Japanese encephalitis. World Health Organization. December 2015. Archived from the original on 13 July 2017. https://doi.org/10.1080/21645515.2018.1564435 Quan TM, Thao TTN, Duy NM (2020) Estimates of the global burden of Japanese encephalitis and the impact of vaccination from 2000–2015 eLife. 9:e51027. https://doi.org/10.7554/eLife.51027 . Tran Minh Nhat and Hannah Clapham Ladreyt H, Chevalier V, Durand B (2022) Modelling Japanese encephalitis virus transmission dynamics and human exposure in a Cambodian rural multi-host system. PLoS Negl Trop Dis 16(7):e0010572. https://doi.org/10.1371/journal.pntd.0010572 Louten J (2016) Virus Replication. Essent Hum Virol. :49–70 Solomon T, Ni H, Beasley DW, Ekkelenkamp M, Cardosa MJ, Barrett AD (2003) Origin and evolution of Japanese encephalitis virus in southeast Asia. J Virol 77(5):3091–3098. https://doi.org/10.1128/jvi.77.5.3091-3098.2003 Yadav P, Chakraborty P, Jha NK, Dewanjee S, Jha AK, Panda SP, Mishra PC, Dey A, Jha SK (2022) Molecular mechanism and role of Japanese encephalitis virus infection in central nervous system-mediated diseases. Viruses 14(12):2686. https://doi.org/10.3390/v14122686 Kao YT, Chang BL, Liang JJ, Tsai HJ, Lee YL, Lin RJ, Lin YL (2015) Japanese encephalitis virus nonstructural protein NS5 interacts with mitochondrial trifunctional protein and impairs fatty acid β-oxidation. PLoS Pathog 11(3):e1004750. https://doi.org/10.1371/journal.ppat.1004750 Ye J, Chen Z, Li Y, Zhao Z, He W, Zohaib A et al (2017) Japanese Encephalitis Virus NS5 Inhibits Type I Interferon (IFN) Production by Blocking the Nuclear Translocation of IFN Regulatory Factor 3 and NF-κb. J Virol 91(8):e00039–e00017. https://doi.org/10.1128/jvi.00039-17 Zhu Y, He Z, Qi Z (2023) Virus-host Interactions in Early Japanese Encephalitis Virus Infection. Virus Res 331:199120. https://doi.org/10.1016/j.virusres.2023.199120 Mohammed MA, Galbraith SE, Radford AD, Dove W, Takasaki T, Kurane I, Solomon T (July 2011) Molecular phylogenetic and evolutionary analyses of Muar strain of Japanese encephalitis virus reveal it is the missing fifth genotype. Infect Genet Evol 11(5):855–862. Bibcode:2011InfGE https://doi.org/10.1016/j.meegid.2011.01.020 Pan XL, Liu H, Wang HY, Fu SH, Liu HZ, Zhang HL, Li MH, Gao XY, Wang JL, Sun XH et al (2011) Emergence of genotype I of Japanese encephalitis virus as the dominant genotype in Asia. J Virol 85:9847–9853. https://doi.org/10.1128/jvi.00825-11 Hanna JN, Ritchie SA, Phillips DA, Shield J, Bailey MC, Mackenzie JS, Poidinger M, McCall BJ, Mills PJ (1996) An outbreak of Japanese encephalitis in the Torres Strait, Australia, 1995. Med J Aust 165:256–260. https://doi.org/10.5694/j.1326-5377.1996.tb124960.x Williams DT, Wang L-F, Daniels PW, Mackenzie JS (2000) Molecular characterization of the first Australian isolate of Japanese encephalitis virus, the FU strain. J Gen Virol 81:2471–2480. https://doi.org/10.1099/0022-1317-81-10-2471 Chen W-R, Tesh RB, Rico-Hesse R (1990) Genetic Variation of Japanese Encephalitis Virus in Nature. J Gen Virol 71:2915–2922. https://doi.org/10.1099/0022-1317-71-12-2915 Spickler AR (2023) Japanese Encephalitis. Retrieved from http://www.cfsph.iastate.edu/DiseaseInfo/factsheets.php Xu G, Gao T, Wang Z, Zhang J, Cui B, Shen X, Zhou A, Zhang Y, Zhao J, Liu H, Liang G Re-Emerged Genotype IV of Japanese Encephalitis Virus Is the Youngest Virus in Evolution. Viruses 2023 Feb 24,15(3):626. https://doi.org/10.3390/v15030626 Kumar S, Verma A, Yadav P, Dubey SK, Azhar EI, Maitra SS, Dwivedi VD Molecular pathogenesis of Japanese encephalitis and possible therapeutic strategies. Arch Virol 2022 Sep, 167(9):1739–1762. https://doi.org/10.1007/s00705-022-05481-z Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815. https://doi.org/10.1006/jmbi.1993.1626 Bekker H, Berendsen HJC, Dijkstra EJ, Achterop S, van Drunen R, van der Spoel D, Sijbers A, Keegstra H et al Gromacs: A parallel computer for molecular dynamics simulations, pp. 252–256 in Physics computing 92. Huang J, MacKerell AD Jr. CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data. J Comput Chem 2013 Sep 30,34(25):2135–2145. https://doi.org/10.1002/jcc.23354 Berendsen HJC, Van Der Spoel D, Van Drunen R (1995) GROMACS: A Message-Passing Parallel Molecular Dynamics Implementation. 91:43–56. https://doi.org/10.1016/0010-4655(95)00042-E Hess B, Kutzner C, Van Der Spoel D (2008) and Erik Lindahl. Article GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. https://doi.org/10.1021/ct700301q Darden T et al (1993) Particle Mesh Ewald: An Nlog (N) Method for Ewald Sums in Large Systems Particle Mesh Ewald : An N -Log (N) Method for Ewald Sums in Large Systems. 10089. http://dx.doi.org/10.1063/1.464397 Harrach MF, Drossel B, Harrach MF, Drossel B (2014) Structure and Dynamics of TIP3P, TIP4P, and TIP5P Water near Smooth and Atomistic Walls of Different Hydroaffinity Structure and Dynamics of TIP3P, TIP4P, and TIP5P Water near Smooth and Atomistic Walls of Different Hydroaffinity. 174501. https://doi.org/10.1063/1.4872239 Hess B, Bekker H, Herman JC, Berendsen, Johannes GEM, Fraaije (1997) LINCS: A Linear Constraint Solver for Molecular Simulations. J Comput Chem 18(12):1463–1472. https://doi.org/10.1002/(SICI)1096-987X (199709)18:12%3C1463::AID-JCC4%3E3.0.CO;2-H Parrinello M (2012) and A Rahman. Polymorphic Transitions in Single Crystals: A New Molecular Dynamics Method Polymorphic Transitions in Single Crystals : A New Molecular Dynamics Method. 7182(1981) https://doi.org/10.1063/1.328693 Klema VJ, Padmanabhan R, Choi KH Flaviviral Replication Complex: Coordination between RNA Synthesis and 5'-RNA Capping. Viruses 2015 Aug 13,7(8):4640–4656. https://doi.org/10.3390/v7082837 SARS CoV2 RdRp mutations affect the mutation rate of the SARS-CoV-2 genome, Eskier D, Karakülah G, Suner A, Oktay Y (2020) RdRp mutations are associated with SARS-CoV-2 genome evolution. PeerJ. ;8:e9587 Xu Y, Wang H, Nussinov R, Ma B (2013) Protein charge and mass contribute to the spatio-temporal dynamics of protein-protein interactions in a minimal proteome. Proteomics 13(8):1339–1351. https://doi.org/10.1002/pmic.201100540 Schweizer L, Mueller L (2014) Protein conformational dynamics and signaling in evolution and pathophysiology. In Biased Signaling in Physiology, Pharmacology and Therapeutics (pp. 209–249). Academic Press https://doi.org/10.1016/B978-0-12-411460-9.00007-0 Yin X, Popa H, Stapon A, Bouda E, Garcia-Diaz M (2023) Fidelity of Ribonucleotide Incorporation by the SARS-CoV-2 Replication Complex. J Mol Biol 435(5):167973. https://doi.org/10.1016/j.jmb.2023.167973 Zong K, Wei C, Li W, Wang C, Ruan J, Liu X, Zhang S, Yan H, Cao R, Li X Identification of novel inhibitors of dengue viral NS5 RNA-dependent RNA polymerase through molecular docking, biological activity evaluation and molecular dynamics simulations. J Enzyme Inhib Med Chem 2025 Dec, 40(1):2463006. https://doi.org/10.1080/14756366.2025.2463006 Jiří Šponer G, Bussi M, Krepl P, Banáš S, Bottaro RA, Cunha (2018) Alejandro Gil-Ley, Giovanni Pinamonti, Simón Poblete, Petr Jurečka, Nils G. Walter, and Michal Otyepka Chemical Reviews (8), 4177 – 433. https://doi.org/10.1021/acs.chemrev.7b00427 Pascua BPG, Casiguran SL, Villagracia ARC et al (2025) Molecular docking and dynamics of potential inhibitors of NS5 protein methyltransferase domain of dengue virus serotype 3 derived from marine sponges. Discov Chem 2:29. https://doi.org/10.1007/s44371-025-00107-0 Klema VJ, Ye M, Hindupur A, Teramoto T, Gottipati K, Padmanabhan R, Choi KH Dengue Virus Nonstructural Protein 5 (NS5) Assembles into a Dimer with a Unique Methyltransferase and Polymerase Interface. PLoS Pathog 2016 Feb 19,12(2):e1005451. https://doi.org/10.1371/journal.ppat.1005451 Tiwari RK, Pandey V, Srivastava H, Srivastava AK, Pandey V Docking and MM study of non-structural protein (NS5) of Japanese Encephalitis Virus (JEV) with some derivatives of adenosyl. Front Chem 2023 Nov 27,111258764. https://doi.org/10.3389/fchem.2023.1258764 Deb A, Nagpal S, Yadav RK, Thakur H, Nair D, Krishnan V, Vrati S (2024) Japanese encephalitis virus NS5 protein interacts with nucleolin to enhance the virus replication. J Virol 98(8):e0085824. https://doi.org/10.1128/jvi.00858-24 Raboni S, Spyrakis F, Campanini B, Amadasi A, Bettati S, Peracchi A, Mozzarelli A, Contestabile R (2010) 7.10-pyridoxal 5’-phosphate-dependent enzymes: catalysis, conformation, and genomics. Compr Nat Prod II 7:273–350 Yakovenko ML, Cherkasova EA, Rezapkin GV, Ivanova OE, Ivanov AP, Eremeeva TP, Baykova OY, Chumakov KM, Agol VI (2006) Antigenic evolution of vaccine-derived polioviruses: changes in individual epitopes and relative stability of the overall immunological properties. J Virol 80(6):2641–2653. https://doi.org/10.1128/jvi.80.6.2641-2653.2006 Additional Declarations No competing interests reported. Supplementary Files SupplementaryDetails10102025.docx Cite Share Download PDF Status: Published Journal Publication published 23 Feb, 2026 Read the published version in Virus Genes → Version 1 posted Editorial decision: Revision requested 04 Dec, 2025 Reviews received at journal 03 Dec, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers invited by journal 12 Nov, 2025 Editor assigned by journal 11 Oct, 2025 Submission checks completed at journal 11 Oct, 2025 First submitted to journal 10 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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1","display":"","copyAsset":false,"role":"figure","size":140903,"visible":true,"origin":"","legend":"\u003cp\u003eRMSD Backbone of different genotypes (a-Genotype 1, b-Genotype 2, c-Genotype 3, d-Genotype 4, e-Genotype (G5)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7823758/v1/52039b68407c8e82ef802aab.png"},{"id":96634527,"identity":"75a9adb5-8dd2-449f-b13c-0e645f859e3e","added_by":"auto","created_at":"2025-11-24 13:23:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":253731,"visible":true,"origin":"","legend":"\u003cp\u003ea) RMSF analysis for 5 different JEV genotypes, b) All-atom number of hydrogen bond analysis for 5 different JEV genotypes, c) Radius of Gyration for different genotypes\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7823758/v1/149075dfbaf4e776fa5585e4.png"},{"id":103765846,"identity":"171230d6-3f37-49c5-b9b4-924664da343e","added_by":"auto","created_at":"2026-03-02 16:10:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1161162,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7823758/v1/394688ed-879a-4eb6-bb3d-031894bc7bc5.pdf"},{"id":96634565,"identity":"d1764c60-8212-4abc-9721-001c26fec029","added_by":"auto","created_at":"2025-11-24 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Transmission is most common in agricultural settings such as farms and rice fields, though it can occasionally occur in urban areas. Although many infections go unnoticed, those that do cause illness often come with noticeable symptoms, with severe complications, including high fever, headache, confusion, coma, tremors, and altered mental states caused by brain inflammation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. JE leads to an estimated 68,000 symptomatic cases annually, with approximately 17,000 fatalities. The infection also affects the central nervous system (CNS), leading to seizures and death in severe cases.\u003c/p\u003e\u003cp\u003eJapanese encephalitis virus (JEV) is a mosquito-borne flavivirus related to dengue, Zika, Yellow Fever, and West Nile viruses. The first recognized JE case was reported in Japan in 1871, and outbreaks remain a persistent global public-health concern [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. JEV is transmitted primarily by \u003cem\u003eCulex tritaeniorhynchus\u003c/em\u003e mosquitoes; waterbirds (especially Ardeidae) act as reservoir hosts, pigs serve as amplifying hosts, and humans are dead-end hosts with no human-to-human transmission [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The ~\u0026thinsp;11-kb, single-stranded positive-sense RNA genome encodes a single polyprotein that is cleaved into structural (C, prM, E) and non-structural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, NS5) proteins. As a positive-sense RNA virus, JEV delivers an infectious genome that functions directly as mRNA, enabling immediate translation of viral proteins and rapid initiation of replication and virion assembly [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAmong these proteins, NS5 is pivotal for replication and uniquely combines an N-terminal methyltransferase (MTase) with a C-terminal RNA-dependent RNA polymerase (RdRp). Together, these domains drive RNA synthesis and 5\u0026prime; capping and are especially critical for efficient replication in the central nervous system [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The RdRp is organized into finger, palm, and thumb subdomains that coordinate RNA binding, catalysis, and processivity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Beyond its enzymatic roles, NS5 interfaces with host pathways: it binds the mitochondrial trifunctional protein (MTP), disrupting long-chain fatty-acid metabolism and potentially provoking pro-inflammatory cytokine release that can worsen disease and facilitate viral spread [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. NS5 also antagonizes type I interferon signaling by blocking activation of key transcription factors, including IRF3 and NF-κB, thereby blunting the host antiviral response [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Structural studies have mapped inhibitor-binding pockets on NS5, providing a strong foundation for structure-based antiviral discovery [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGenetically, JEV is divided into five genotypes\u0026mdash;G1 through G5\u0026mdash;each distinguished by unique evolutionary backgrounds, geographical ranges, and host-vector associations, as determined through genome analysis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Since the 1990s, G1 has emerged as the dominant genotype across much of Asia, whereas G3 was historically more widespread. G2 and G5 represent older genotypes with more limited geographic presence [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Despite JEV being a single serotype, shifts in genotype dominance have been observed over time, and in some regions, genotype distribution remains poorly documented [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Phylogenetic analysis suggests that the genotypes evolved in the following order: G5, G3, G2, G1, and finally G4. Genotype 4 (G4) is considered the most recent lineage, having emerged approximately 122 years ago (with a 95% highest posterior density [HPD] interval of 57\u0026ndash;233 years). The G4 lineage also exhibits a high mutation rate, with a mean substitution rate of 1.145 \u0026times; 10⁻\u0026sup3; (95% HPD: 9.55 \u0026times; 10⁻⁴ to 1.35 \u0026times; 10⁻\u0026sup3;), placing it among the rapidly evolving viruses [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study investigates how genotype-specific amino acid substitutions alter the structure and stability of the NS5 protein across Japanese encephalitis virus (JEV) genotypes G1\u0026ndash;G5, and addresses a simple yet unresolved question: Does NS5 stability contribute to explaining why some strains sustain higher viral loads\u0026mdash;and thus greater fitness\u0026mdash;than others? Although NS5 is central to replication, its stability\u0026ndash;fitness contribution remains poorly quantified and the key residues governing genotype-dependent stability are unknown. To close this gap, we introduce a streamlined, genotype-aware computational workflow that rapidly profiles NS5 stability and conformational shifts from curated sequence accessions. By pinpointing residue changes that tune stability, our analysis links molecular architecture to replication efficiency, transmissibility, and potential disease severity. While optimized for JEV, the approach generalizes to other flaviviruses, offering a practical path to identify stability-driven vulnerabilities and to inform targeted antivirals and vaccine designs aimed at curbing pathogenicity and reducing JEV-associated morbidity and mortality.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data Retrieval and NS5 protein sequence alignment\u003c/h2\u003e\u003cp\u003eA comprehensive database search was conducted to screen the most recent JEV genotypes, reflecting current epidemiological trends, and analyze the structural stability and conformational changes of NS5 proteins across the screened JEV genomes. The accession numbers are listed in \u003cb\u003eTable .1\u003c/b\u003e, which were considered from human cerebrospinal fluid samples, the primary site of viral replication [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The NS5 protein regions were retrieved and extracted from the GenBank Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), followed by sequence alignment performed using Clustal Omega (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/jdispatcher/msa/clustalo\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/jdispatcher/msa/clustalo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to examine key conserved and variable regions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAccession numbers of JEV genomic sequences used in this study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenBank Accession\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganism\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenotypes (G)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTissue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStrain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQKI86564.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCerebrospinal fluid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNX1889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAAF73859.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCerebrospinal fluid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAFP33182.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCerebrospinal fluid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIND-WB-JE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIndia\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUYD39327.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCerebrospinal fluid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eJEV/Human/NT_Tiwi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWXB51294.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCerebrospinal fluid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNCCP 43279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSouth Korea\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 NS5 Protein Sequence Examination: Primary Structure Insights\u003c/h2\u003e\u003cp\u003eThe retrieved NS5 protein sequences of each of the five genotypes\u0026mdash;G1, G2, G3, G4, and G5 of similar length (905 amino acids)\u0026mdash;were analyzed to deduce the primary sequence information using ExPASy-ProtParam (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.expasy.org/protparam/\u003c/span\u003e\u003cspan address=\"https://web.expasy.org/protparam/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which computes various physical and chemical parameters for a user-entered protein sequence. The computed parameters include molecular weight, amino acid composition, atomic composition, and grand average of hydropathicity (GRAVY). ProtParam provided crucial insights into various aspects of the primary structure of the NS5 proteins from G1 to G5, which are essential for elucidating their basic structure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Structure Modeling of NS5 Protein Across the Genotypes\u003c/h2\u003e\u003cp\u003eStructure modeling of NS5 across genotypes 1 to 5 was conducted using MODELLER [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Template selection was performed through BLASTp searches against the PDB database by utilizing the respective sequences, which identified a suitable template, NS5 from a related flavivirus (PDB ID: 4k6m). The selected template was employed for NS5 modeling across multiple genotypes. Models exhibiting the most favourable DOPE scores, as computed by MODELLER, were prioritized for downstream analyses. Structural integrity was then verified via Ramachandran plot assessment using PROCHECK (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://saves.mbi.ucla.edu/\u003c/span\u003e\u003cspan address=\"https://saves.mbi.ucla.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Molecular Dynamics (MD) Simulation\u003c/h2\u003e\u003cp\u003eMolecular dynamics simulations were executed utilizing the GROMACS 2024.4 platform [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] with the CHARMM36[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] force field to evaluate the structural stability, flexibility, and compactness of the NS5 proteins across the five JEV genotypes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The system was prepared using the Ewald Particle Mesh method to calculate electrostatic forces over a distance [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]and placed into a solvation box hydrated using the TIP3P model, followed by the addition of Na\u0026thinsp;+\u0026thinsp;and Cl\u0026thinsp;\u0026minus;\u0026thinsp;ions to neutralize the system [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Steric conflicts were minimized with 50,000 steps of steepest descent (SD) energy minimization. The LINCS algorithm [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] was utilized to constrain all hydrogen bonds, ensuring system stability. The system was then equilibrated using the NVT ensemble with a timestep of 2 fs at 310 K for 100 ps, followed by pressure equilibration under the NPT ensemble for 1 ns at 310 K and 1 atmosphere using the Parrinello-Rahman pressure coupling method [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Temperature coupling was maintained using the velocity-rescaling method (Bussi, Donadio, and Parrinello, n.d..). The simulation was executed for 100 ns (100,000 ps) during the production phase. Key structural parameters, including Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF), were calculated using GROMACS to assess conformational stability and residue fluctuation among the NS5 proteins. Additionally, hydrogen bond analysis was performed to evaluate interactions contributing to the protein\u0026rsquo;s structural integrity\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Sequence determination of the NS5 protein among the genotypes\u003c/h2\u003e\u003cp\u003eThe sequence determination of the NS5 protein among JEV genotypes reveals variations in molecular weight, charge distribution, and hydropathicity, which influence structural stability and function \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Molecular weight affects protein inertia and movement dynamics, with G3 having the highest molecular weight (103,353.93 Da) and G5 the lowest (103,191.70 Da). Electrostatic interactions, crucial for protein folding and stability, are influenced by the distribution of charged amino acids. The total number of negatively charged residues (Asp and Glu) varies among genotypes, with G3, G4, and G5 containing 119, G1 having 116, and G2 with 118. Similarly, positively charged residues (Arg and Lys) are highest in G4 (132), while G1 has 129, and G2, G3, and G5 each contain 130. Hydropathicity, measured by the Grand Average of Hydropathicity (GRAVY) score, indicates the protein\u0026rsquo;s overall hydrophobic or hydrophilic nature. The GRAVY values for G1, G2, G3, G4, and G5 are \u0026minus;\u0026thinsp;0.514, -0.527, -0.533, -0.543, and \u0026minus;\u0026thinsp;0.528, respectively, confirming that all NS5 proteins are hydrophilic, which influences their engagement with cellular machinery and associated processes.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical properties of the NS5 protein across JEV genotypes 1 to 5\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eJEV genotypes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eG1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eG2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eG3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eG4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eG5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolecular weight (Da)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e103200.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e103275.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e103353.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e103330.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e103191.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal no. of negatively charged residues (Asp\u0026thinsp;+\u0026thinsp;Glu)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal number of positively charged residues (Arg\u0026thinsp;+\u0026thinsp;Lys)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal number of atoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14424\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14435\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14392\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGrand average of hydropathicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.514\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.528\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Key Residue Differences in the RdRp and MTase Domains Across JEV Genotypes\u003c/h2\u003e\u003cp\u003eIn the RdRp domain, genotype 5 (G5) carries a distinctive set of substitutions that plausibly reshape local packing, electrostatics, and catalytic behavior. At positions 17, 65, and 182, G5 encodes T17, Y65, and E182, whereas other genotypes more typically harbor A17, H65, and R182 (S1). The bulkier, aromatic Tyr65 (vs His65) can perturb nearby hydrophobic packing and thus modulate polymerase stability, while the charge reversal at 182 (Glu replacing Arg) risks disrupting salt bridges and hydrogen-bond networks that help maintain structural integrity. These shifts occur near functionally sensitive regions and may influence enzyme performance. Consistent with this, G5 presents A51/V52, whereas other genotypes show S/A or conserved A/V; the hydrophobic Val52 in G5 could alter contacts with the RNA backbone, with potential consequences for RNA binding and catalytic efficiency.\u003c/p\u003e\u003cp\u003eAdditional substitutions at positions 265\u0026ndash;267 in G5 (A/V/G) differ from S/T/D in other genotypes (S2). Because these residues likely sit close to the active site, such changes could tune substrate interactions or local flexibility. At position 316, G5 carries Gln in place of histidine or leucine found in other genotypes; the loss of His\u0026mdash;often a proton donor/acceptor\u0026mdash;suggests a shifted catalytic microenvironment. G5 also retains Val at position 344 where others show Ile or Thr; the smaller Val side chain can ease steric crowding and stabilize adjacent loops. A similar pattern appears at position 118: G5 (along with G3 and G1) has Ile, whereas G4 and G2 carry Val; the larger Ile can promote tighter hydrophobic packing and improved local stability. Notably, analogous genotype-specific divergence extends into the methyltransferase (MTase) domain, indicating that these structural and functional adjustments are not confined to a single NS5 subdomain.\u003c/p\u003e\u003cp\u003eAt position 191(\u003cb\u003eS3\u003c/b\u003e), G5 features threonine instead of valine, introducing a hydroxyl group that may create polar interactions or hydrogen bonds, alter local stability and possibly affect substrate binding. Genotype 5 (G5) also exhibits a methionine substitution at position 59, replacing the leucine found in other genotypes. Due to methionine\u0026rsquo;s sulfur-containing side chain, this change may impact regional flexibility or alter local hydrophobic interactions. G5 keeps lysine at position 9, while G4 has arginine. The shorter side chain of lysine may slightly affect binding kinetics with the methyl donor S-adenosylmethionine (SAM), although both residues are positively charged. At position 149, there is even another significant difference: G5 encodes aspartic acid rather than glutamic acid, which is what other genotypes encode. The protein's interaction with the RNA cap structure may be influenced by aspartic acid's shorter side chain. G5 substitutes valine for leucine at position 213, which is a conservative move between two hydrophobic residues but could somewhat alter the geometry of the cap-binding pocket. When combined, these G5-specific amino acid alterations point to complex impacts on enzyme performance, protein stability, and structural flexibility. Such alterations may reflect evolutionary adaptations aimed at improving replication efficiency or evading host immune responses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Molecular Dynamics of NS5 Protein Reveal Enhanced Structural Stability in JEV Genotype 5\u003c/h2\u003e\u003cp\u003eMolecular dynamics techniques elucidate the complexities of the structural dynamics of the NS5 protein across five JEV genotypes in a solvent environment. RMSD, RMSF, and hydrogen bond analyses reveal critical differences in conformational stability. RMSD analysis indicates that Genotype 4 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ed\u003cb\u003e)\u003c/b\u003e exhibits the highest deviations over time, particularly after 10 ns, suggesting increased flexibility and potential structural instability. In contrast, G1\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e shows deviations after 80 ns in the C-terminal region, while G2\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e also fluctuates from its native form. Meanwhile, G3 and G5 maintain relatively stable RMSD values \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ec \u0026amp; \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ed\u003cb\u003e)\u003c/b\u003e, indicating greater structural integrity and a more preserved conformation. RMSF analysis further supports these findings by highlighting residue-level flexibility. G4 displays higher fluctuations, particularly in the RdRp domain, Mtase, and N-terminal regions, which could affect its functional stability. Meanwhile, G2 exhibits moderate fluctuations, whereas G3 and G5 show the lowest fluctuations, suggesting a more compact and stable structure \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. The increased flexibility observed in G4 may contribute to its overall instability, potentially affecting its function within the viral replication process. Assessing hydrogen bonds provides deeper insight into NS5 stability, since more consistent bonds usually reflect stronger structural resilience. Genotype 4 likely forms fewer stable hydrogen bonds, contributing to increased fluctuations and structural deviations, as reflected in its higher RMSD and RMSF values. In contrast, Genotypes 2 and 3 maintain a stronger hydrogen bonding network, stabilizing their structures and reducing fluctuations. This supports the observation that Genotypes 5 and 3 are the most stable, followed by Genotypes 2 and 1, while Genotype 4 is the least stable \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eb\u003cb\u003e).\u003c/b\u003e These structural variations may influence viral replication and interactions with host factors, highlighting the need for further computational and experimental studies. Additionally, the results of the radius of gyration\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ec\u003cb\u003e)\u003c/b\u003e highlighted that Genotype 1 (red) maintains the most compact structure with Rg values of 3.15\u0026ndash;3.4 nm for the majority of the simulation, showing exceptional structural stability until a late-simulation expansion around 80,000 ps. Genotype 3 (green) exhibits the highest structural flexibility with Rg fluctuations between 3.1\u0026ndash;3.6 nm and dramatic expansion spikes around 40,000 ps and 95,000 ps, indicating increased conformational sampling compared to other variants. Genotypes 2, 4, and 5 display intermediate stability profiles with overlapping Rg ranges, suggesting similar structural compactness and moderate conformational dynamics throughout the 100ns simulation\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eNS5 is the largest and most conserved non-structural protein encoded by JEV, serving as a cornerstone of the viral replication process. Structurally, it comprises two key domains: the N-terminal methyltransferase (MTase), which facilitates 5\u0026rsquo;-RNA capping, and the C-terminal RNA-dependent RNA polymerase (RdRp), responsible for synthesizing the viral RNA. Both domains are vital for ensuring effective genome replication. Due to its critical functions and high conservation across flaviviruses, NS5 has been widely recognized as a prime target for antiviral drug development [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Our genotype-specific structural analysis of NS5 across JEV genotypes 1 through 5 uncovered notable differences in characteristics such as molecular weight (MW), compactness, and charge distribution. The molecular weight of NS5 varied from 103,191.70 Da in G5 to 103,353.93 Da in G3\u0026mdash;a difference of 162.23 Da. These variations are primarily driven by genotype-specific amino acid substitutions or deletions, underscoring evolutionary pressures at play. Interestingly, there is no clear linear trend in MW changes across genotypes. However, G1 and G5\u0026mdash;both genotypes with rising prevalence\u0026mdash;tend to encode smaller NS5 proteins compared to G3, G2, and G4. This reduction in mass may contribute to increased structural compactness and enhanced in vivo stability, as compact and well-balanced charge distributions are thought to improve protein resilience [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Moreover, a lighter protein structure could reduce the cellular energy demands of replication, potentially boosting viral replication efficiency [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eG5 is markedly more compact even though its GRAVY score is less negative (\u0026minus;\u0026thinsp;0.528, i.e., slightly more hydrophilic on average). This indicates that compactness here is governed less by bulk hydropathy and more by electrostatics: G5\u0026rsquo;s nearly balanced charge\u0026mdash;about 130 positively charged versus 119 negatively charged residues (net\u0026thinsp;+\u0026thinsp;11)\u0026mdash;supports tighter packing through salt bridges and screened repulsions. This agrees with prior work showing that well-distributed electrostatic interactions are central to protein stability [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. By contrast, G4 carries a stronger net negative charge that weakens intramolecular attractions, increasing backbone and loop mobility and thereby reducing overall stability\u0026mdash;a pattern reported for other structurally dynamic viral proteins [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. At the residue level, G5 harbors distinctive substitutions in the RdRp domain: Tyr65 and Glu182 supplant the more commonly conserved His65 and Arg182. These replacements alter side-chain size and charge (steric and electrostatic effects), plausibly shifting local packing, salt-bridge patterns, and active-site microenvironments in ways consistent with prior NS5 analyses across flaviviruses [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Additional changes, such as Ala51 and Val52, may further optimize polymerase\u0026ndash;RNA complementarity, improving template engagement and catalytic throughput. In the MTase domain, unique substitutions Thr191 and Met59 introduce opportunities for new hydrogen bonds and strengthened hydrophobic contacts, echoing mechanisms previously linked to enhanced methyltransferase performance [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Molecular-dynamics results reinforce this picture: G5 exhibits lower RMSD (global structural drift) and lower RMSF (per-residue flexibility), indicating higher structural integrity with minimal domain-scale motion. Such reinforced hydrogen-bond networks and reduced fluctuations have been associated with improved replication fidelity [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Functionally, a more stable NS5 lets G5 expend fewer cellular and viral resources on folding and quality control, allocating more toward genome replication\u0026mdash;consistent with higher observed viral loads. Conversely, G4\u0026rsquo;s flexibility may help it sample conformations advantageous for immune evasion, but the same plasticity appears to compromise replication efficiency, reflecting an evolutionary trade-off [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Taken together, the NS5 mutational patterns in G1 and G5 likely confer concrete evolutionary benefits: (i) more efficient enzymatic activity via fine-tuned residue interactions, (ii) greater structural resilience under physiological conditions, and (iii) improved replication fidelity owing to reduced structural fluctuations\u0026mdash;all consistent with earlier mechanistic insights for RNA-virus polymerases and capping enzymes [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese traits likely underlie the prevalence and periodic re-emergence of these genotypes, particularly under vaccine-imposed selective pressure. Use of inactivated G3 vaccines may have inadvertently favored genotypes with distinct antigenic and structural profiles\u0026mdash;most notably G1 and G5\u0026mdash;as hypothesized in vaccine-driven viral evolution studies [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This interpretation is reinforced by convergent signals across our analyses, including radius of gyration (Rg), distinct structural behaviors, and stability patterns observed among all five genotypes. Overall, the data show that protein mass alone does not confer functional advantage; rather, evolutionary shifts in residue composition and charge distribution can recalibrate electrostatics and packing, thereby altering enzyme behavior and replication dynamics. These findings motivate targeted investigations into how such molecular features shape host\u0026ndash;virus interactions and immune responses, to inform genotype-aware intervention strategies. In this study, we assessed NS5 stability using complementary readouts\u0026mdash;physicochemical profiling, multi-scale RMSD/RMSF metrics, hydrogen-bond network analysis, and Rg measurements from molecular dynamics trajectories. It is essential to highlight that our findings are solely based on computer-aided technology; the genotype-specific substitutions we identified yield clear, testable hypotheses and provide actionable starting points for rational vaccine and antiviral design.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study establishes a genotype-aware, in-silico framework that ties specific NS5 substitutions to measurable shifts in conformational and thermodynamic stability\u0026mdash;and, by extension, to replication efficiency, pathogenic potential, and viral fitness. Residues Y65, M59, E182, and T191 emerge as stability-shaping levers that explain genotype-level differences and nominate high-value sites for therapeutic intervention. By jointly mapping conserved, function-critical motifs with mutation hotspots, we define actionable targets for broad-spectrum antivirals and epitope-focused vaccines. While the results are computational, they yield clear, testable hypotheses and a prioritized roadmap for wet-lab validation. The workflow generalizes to other flaviviruses and, integrated with genomic surveillance, can accelerate variant triage, sharpen outbreak forecasting, and guide targeted interventions in high-risk settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting Interest\u003c/h2\u003e\u003cp\u003eThe authors have declared no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK.P.S conceptualized and designed the study, contributing to the manuscript review and editing. H.T conducted the research, performed data analysis, interpreted the results, and prepared the initial draft of the manuscript. V.R and J.H contributed to the manuscript review and editing, with J.H also providing technical input. N.K assisted with data analysis. A.P and P.P.S were involved in the manuscript review and editing. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Disease Modelling Consortium, Indian Institute of Technology Bombay [grant number 47013250001]. The authors also wish to acknowledge the Spatial Epidemiological Laboratory and the Director of ICAR-NIVEDI for furnishing the requisite facilities to conduct this work. Additionally, the authors would like to recognize that the research was supported by the Indian Council of Agricultural Research, under the Department of Agricultural Research and Education, Government of India.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMuniaraj M, Rajamannar V (2019) Impact of SA 14-14-2 vaccination on the occurrence of Japanese encephalitis in India. Hum Vaccin Immunother. ;15(4):834-840Japanese encephalitis. World Health Organization. December 2015. Archived from the original on 13 July 2017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/21645515.2018.1564435\u003c/span\u003e\u003cspan address=\"10.1080/21645515.2018.1564435\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuan TM, Thao TTN, Duy NM (2020) Estimates of the global burden of Japanese encephalitis and the impact of vaccination from 2000\u0026ndash;2015 eLife. 9:e51027. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7554/eLife.51027\u003c/span\u003e\u003cspan address=\"10.7554/eLife.51027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Tran Minh Nhat and Hannah Clapham\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLadreyt H, Chevalier V, Durand B (2022) Modelling Japanese encephalitis virus transmission dynamics and human exposure in a Cambodian rural multi-host system. PLoS Negl Trop Dis 16(7):e0010572. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pntd.0010572\u003c/span\u003e\u003cspan address=\"10.1371/journal.pntd.0010572\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLouten J (2016) Virus Replication. Essent Hum Virol. :49\u0026ndash;70\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSolomon T, Ni H, Beasley DW, Ekkelenkamp M, Cardosa MJ, Barrett AD (2003) Origin and evolution of Japanese encephalitis virus in southeast Asia. J Virol 77(5):3091\u0026ndash;3098. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/jvi.77.5.3091-3098.2003\u003c/span\u003e\u003cspan address=\"10.1128/jvi.77.5.3091-3098.2003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYadav P, Chakraborty P, Jha NK, Dewanjee S, Jha AK, Panda SP, Mishra PC, Dey A, Jha SK (2022) Molecular mechanism and role of Japanese encephalitis virus infection in central nervous system-mediated diseases. Viruses 14(12):2686. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/v14122686\u003c/span\u003e\u003cspan address=\"10.3390/v14122686\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKao YT, Chang BL, Liang JJ, Tsai HJ, Lee YL, Lin RJ, Lin YL (2015) Japanese encephalitis virus nonstructural protein NS5 interacts with mitochondrial trifunctional protein and impairs fatty acid β-oxidation. PLoS Pathog 11(3):e1004750. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.ppat.1004750\u003c/span\u003e\u003cspan address=\"10.1371/journal.ppat.1004750\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYe J, Chen Z, Li Y, Zhao Z, He W, Zohaib A et al (2017) Japanese Encephalitis Virus NS5 Inhibits Type I Interferon (IFN) Production by Blocking the Nuclear Translocation of IFN Regulatory Factor 3 and NF-κb. J Virol 91(8):e00039\u0026ndash;e00017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/jvi.00039-17\u003c/span\u003e\u003cspan address=\"10.1128/jvi.00039-17\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu Y, He Z, Qi Z (2023) Virus-host Interactions in Early Japanese Encephalitis Virus Infection. Virus Res 331:199120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.virusres.2023.199120\u003c/span\u003e\u003cspan address=\"10.1016/j.virusres.2023.199120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohammed MA, Galbraith SE, Radford AD, Dove W, Takasaki T, Kurane I, Solomon T (July 2011) Molecular phylogenetic and evolutionary analyses of Muar strain of Japanese encephalitis virus reveal it is the missing fifth genotype. Infect Genet Evol 11(5):855\u0026ndash;862. Bibcode:2011InfGE\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.meegid.2011.01.020\u003c/span\u003e\u003cspan address=\"10.1016/j.meegid.2011.01.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePan XL, Liu H, Wang HY, Fu SH, Liu HZ, Zhang HL, Li MH, Gao XY, Wang JL, Sun XH et al (2011) Emergence of genotype I of Japanese encephalitis virus as the dominant genotype in Asia. J Virol 85:9847\u0026ndash;9853. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/jvi.00825-11\u003c/span\u003e\u003cspan address=\"10.1128/jvi.00825-11\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHanna JN, Ritchie SA, Phillips DA, Shield J, Bailey MC, Mackenzie JS, Poidinger M, McCall BJ, Mills PJ (1996) An outbreak of Japanese encephalitis in the Torres Strait, Australia, 1995. Med J Aust 165:256\u0026ndash;260. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5694/j.1326-5377.1996.tb124960.x\u003c/span\u003e\u003cspan address=\"10.5694/j.1326-5377.1996.tb124960.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilliams DT, Wang L-F, Daniels PW, Mackenzie JS (2000) Molecular characterization of the first Australian isolate of Japanese encephalitis virus, the FU strain. J Gen Virol 81:2471\u0026ndash;2480. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1099/0022-1317-81-10-2471\u003c/span\u003e\u003cspan address=\"10.1099/0022-1317-81-10-2471\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen W-R, Tesh RB, Rico-Hesse R (1990) Genetic Variation of Japanese Encephalitis Virus in Nature. J Gen Virol 71:2915\u0026ndash;2922. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1099/0022-1317-71-12-2915\u003c/span\u003e\u003cspan address=\"10.1099/0022-1317-71-12-2915\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSpickler AR (2023) Japanese Encephalitis. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cfsph.iastate.edu/DiseaseInfo/factsheets.php\u003c/span\u003e\u003cspan address=\"http://www.cfsph.iastate.edu/DiseaseInfo/factsheets.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu G, Gao T, Wang Z, Zhang J, Cui B, Shen X, Zhou A, Zhang Y, Zhao J, Liu H, Liang G Re-Emerged Genotype IV of Japanese Encephalitis Virus Is the Youngest Virus in Evolution. Viruses 2023 Feb 24,15(3):626. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/v15030626\u003c/span\u003e\u003cspan address=\"10.3390/v15030626\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumar S, Verma A, Yadav P, Dubey SK, Azhar EI, Maitra SS, Dwivedi VD Molecular pathogenesis of Japanese encephalitis and possible therapeutic strategies. Arch Virol 2022 Sep, 167(9):1739\u0026ndash;1762. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00705-022-05481-z\u003c/span\u003e\u003cspan address=\"10.1007/s00705-022-05481-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779\u0026ndash;815. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1006/jmbi.1993.1626\u003c/span\u003e\u003cspan address=\"10.1006/jmbi.1993.1626\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBekker H, Berendsen HJC, Dijkstra EJ, Achterop S, van Drunen R, van der Spoel D, Sijbers A, Keegstra H et al Gromacs: A parallel computer for molecular dynamics simulations, pp. 252\u0026ndash;256 in \u003cem\u003ePhysics computing 92.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang J, MacKerell AD Jr. CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data. J Comput Chem 2013 Sep 30,34(25):2135\u0026ndash;2145. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jcc.23354\u003c/span\u003e\u003cspan address=\"10.1002/jcc.23354\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerendsen HJC, Van Der Spoel D, Van Drunen R (1995) GROMACS: A Message-Passing Parallel Molecular Dynamics Implementation. 91:43\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0010-4655(95)00042-E\u003c/span\u003e\u003cspan address=\"10.1016/0010-4655(95)00042-E\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHess B, Kutzner C, Van Der Spoel D (2008) and Erik Lindahl. Article GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/ct700301q\u003c/span\u003e\u003cspan address=\"10.1021/ct700301q\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarden T et al (1993) Particle Mesh Ewald: An Nlog (N) Method for Ewald Sums in Large Systems Particle Mesh Ewald : An N -Log (N) Method for Ewald Sums in Large Systems. 10089. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1063/1.464397\u003c/span\u003e\u003cspan address=\"10.1063/1.464397\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarrach MF, Drossel B, Harrach MF, Drossel B (2014) Structure and Dynamics of TIP3P, TIP4P, and TIP5P Water near Smooth and Atomistic Walls of Different Hydroaffinity Structure and Dynamics of TIP3P, TIP4P, and TIP5P Water near Smooth and Atomistic Walls of Different Hydroaffinity. 174501. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1063/1.4872239\u003c/span\u003e\u003cspan address=\"10.1063/1.4872239\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHess B, Bekker H, Herman JC, Berendsen, Johannes GEM, Fraaije (1997) LINCS: A Linear Constraint Solver for Molecular Simulations. J Comput Chem 18(12):1463\u0026ndash;1472. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/(SICI)1096-987X\u003c/span\u003e\u003cspan address=\"10.1002/(SICI)1096-987X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e(199709)18:12%3C1463::AID-JCC4%3E3.0.CO;2-H\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParrinello M (2012) and A Rahman. Polymorphic Transitions in Single Crystals: A New Molecular Dynamics Method Polymorphic Transitions in Single Crystals : A New Molecular Dynamics Method. 7182(1981) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1063/1.328693\u003c/span\u003e\u003cspan address=\"10.1063/1.328693\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlema VJ, Padmanabhan R, Choi KH Flaviviral Replication Complex: Coordination between RNA Synthesis and 5'-RNA Capping. Viruses 2015 Aug 13,7(8):4640\u0026ndash;4656. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/v7082837\u003c/span\u003e\u003cspan address=\"10.3390/v7082837\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSARS CoV2 RdRp mutations affect the mutation rate of the SARS-CoV-2 genome, Eskier D, Karak\u0026uuml;lah G, Suner A, Oktay Y (2020) RdRp mutations are associated with SARS-CoV-2 genome evolution. PeerJ. ;8:e9587\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu Y, Wang H, Nussinov R, Ma B (2013) Protein charge and mass contribute to the spatio-temporal dynamics of protein-protein interactions in a minimal proteome. Proteomics 13(8):1339\u0026ndash;1351. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/pmic.201100540\u003c/span\u003e\u003cspan address=\"10.1002/pmic.201100540\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchweizer L, Mueller L (2014) Protein conformational dynamics and signaling in evolution and pathophysiology. In Biased Signaling in Physiology, Pharmacology and Therapeutics (pp. 209\u0026ndash;249). Academic Press \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/B978-0-12-411460-9.00007-0\u003c/span\u003e\u003cspan address=\"10.1016/B978-0-12-411460-9.00007-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYin X, Popa H, Stapon A, Bouda E, Garcia-Diaz M (2023) Fidelity of Ribonucleotide Incorporation by the SARS-CoV-2 Replication Complex. J Mol Biol 435(5):167973. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jmb.2023.167973\u003c/span\u003e\u003cspan address=\"10.1016/j.jmb.2023.167973\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZong K, Wei C, Li W, Wang C, Ruan J, Liu X, Zhang S, Yan H, Cao R, Li X Identification of novel inhibitors of dengue viral NS5 RNA-dependent RNA polymerase through molecular docking, biological activity evaluation and molecular dynamics simulations. J Enzyme Inhib Med Chem 2025 Dec, 40(1):2463006. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/14756366.2025.2463006\u003c/span\u003e\u003cspan address=\"10.1080/14756366.2025.2463006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJiř\u0026iacute; Šponer G, Bussi M, Krepl P, Ban\u0026aacute;š S, Bottaro RA, Cunha (2018) Alejandro Gil-Ley, Giovanni Pinamonti, Sim\u0026oacute;n Poblete, Petr Jurečka, Nils G. Walter, and Michal Otyepka \u003cem\u003eChemical Reviews\u003c/em\u003e (8), 4177\u0026thinsp;\u0026ndash;\u0026thinsp;433. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.chemrev.7b00427\u003c/span\u003e\u003cspan address=\"10.1021/acs.chemrev.7b00427\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePascua BPG, Casiguran SL, Villagracia ARC et al (2025) Molecular docking and dynamics of potential inhibitors of NS5 protein methyltransferase domain of dengue virus serotype 3 derived from marine sponges. Discov Chem 2:29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s44371-025-00107-0\u003c/span\u003e\u003cspan address=\"10.1007/s44371-025-00107-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlema VJ, Ye M, Hindupur A, Teramoto T, Gottipati K, Padmanabhan R, Choi KH Dengue Virus Nonstructural Protein 5 (NS5) Assembles into a Dimer with a Unique Methyltransferase and Polymerase Interface. PLoS Pathog 2016 Feb 19,12(2):e1005451. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.ppat.1005451\u003c/span\u003e\u003cspan address=\"10.1371/journal.ppat.1005451\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTiwari RK, Pandey V, Srivastava H, Srivastava AK, Pandey V Docking and MM study of non-structural protein (NS5) of Japanese Encephalitis Virus (JEV) with some derivatives of adenosyl. Front Chem 2023 Nov 27,111258764. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fchem.2023.1258764\u003c/span\u003e\u003cspan address=\"10.3389/fchem.2023.1258764\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeb A, Nagpal S, Yadav RK, Thakur H, Nair D, Krishnan V, Vrati S (2024) Japanese encephalitis virus NS5 protein interacts with nucleolin to enhance the virus replication. J Virol 98(8):e0085824. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/jvi.00858-24\u003c/span\u003e\u003cspan address=\"10.1128/jvi.00858-24\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRaboni S, Spyrakis F, Campanini B, Amadasi A, Bettati S, Peracchi A, Mozzarelli A, Contestabile R (2010) 7.10-pyridoxal 5\u0026rsquo;-phosphate-dependent enzymes: catalysis, conformation, and genomics. Compr Nat Prod II 7:273\u0026ndash;350\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYakovenko ML, Cherkasova EA, Rezapkin GV, Ivanova OE, Ivanov AP, Eremeeva TP, Baykova OY, Chumakov KM, Agol VI (2006) Antigenic evolution of vaccine-derived polioviruses: changes in individual epitopes and relative stability of the overall immunological properties. J Virol 80(6):2641\u0026ndash;2653. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/jvi.80.6.2641-2653.2006\u003c/span\u003e\u003cspan address=\"10.1128/jvi.80.6.2641-2653.2006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"virus-genes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"viru","sideBox":"Learn more about [Virus Genes](http://link.springer.com/journal/11262)","snPcode":"11262","submissionUrl":"https://submission.nature.com/new-submission/11262/3","title":"Virus Genes","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Non-structural protein-5(NS5), Japanese Encephalitis (JE), Structure modeling, MD Simulation, Residue-level substitution","lastPublishedDoi":"10.21203/rs.3.rs-7823758/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7823758/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eJapanese encephalitis virus (JEV) remains a major health threat across Asia, yet the contribution of genotype-specific variation in the multifunctional NS5 protein to viral fitness is not fully resolved. This study evaluated how sequence differences among JEV genotypes G1\u0026ndash;G5 shape NS5 stability and, in turn, replication potential. A unified in silico workflow combined physicochemical profiling, residue-level substitution mapping, and atomistic molecular dynamics to compare structural stability and conformational behavior across genotypes, with a focus on substitutions predicted to modulate enzymatic performance. Analyses revealed that G5 NS5 maintains a balanced electrostatic environment and persistent hydrogen-bonding networks, yielding greater structural stability than other genotypes. In contrast, G4 NS5 presented a charge imbalance and reduced stability. Simulations consistently supported the robustness of G5 dynamics, with specific substitutions\u0026mdash;including Y65, M59, E182, and T191\u0026mdash;contributing to improved packing, favourable local interactions, and putative gains in catalytic efficiency. These molecular attributes align with heightened replication capacity and provide a mechanistic rationale for the recent prominence of G5 strains relative to G1\u0026ndash;G4. Comprising together, our results demonstrate that genotype-linked substitutions in NS5 directly influence protein stability, replication efficiency, and adaptive potential. Translationally, prioritizing G5-informed NS5 features may guide the design of small-molecule inhibitors and vaccine antigens with broader protective value. More broadly, the presented computational pipeline enables rapid, genotype-aware assessment of protein stability and function in emerging viral lineages, supporting genomic surveillance, risk stratification, and the rational development of broad-spectrum antivirals.\u003c/p\u003e","manuscriptTitle":"Genotype-Resolved NS5 Stability Predicts Japanese Encephalitis Virus Fitness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-24 13:23:05","doi":"10.21203/rs.3.rs-7823758/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-04T14:13:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-03T18:37:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38774059483713953083158338900127632410","date":"2025-11-13T21:01:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-12T17:07:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-11T08:37:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-11T08:35:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Virus Genes","date":"2025-10-10T07:17:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"virus-genes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"viru","sideBox":"Learn more about [Virus Genes](http://link.springer.com/journal/11262)","snPcode":"11262","submissionUrl":"https://submission.nature.com/new-submission/11262/3","title":"Virus Genes","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0d7d3eb1-0a2d-4cb2-9887-a90a04624e0d","owner":[],"postedDate":"November 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:07:45+00:00","versionOfRecord":{"articleIdentity":"rs-7823758","link":"https://doi.org/10.1007/s11262-026-02213-2","journal":{"identity":"virus-genes","isVorOnly":false,"title":"Virus Genes"},"publishedOn":"2026-02-23 15:59:23","publishedOnDateReadable":"February 23rd, 2026"},"versionCreatedAt":"2025-11-24 13:23:05","video":"","vorDoi":"10.1007/s11262-026-02213-2","vorDoiUrl":"https://doi.org/10.1007/s11262-026-02213-2","workflowStages":[]},"version":"v1","identity":"rs-7823758","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7823758","identity":"rs-7823758","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}