Syed Luqman Ali

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M.tb), remains a major global health burden, with host immune responses critically influencing disease progression and treatment outcomes. In this study, we performed an integrative multi-cohort analysis combining transcriptomics, SNP-based structural evaluation, and molecular docking to identify key immune regulators and potential therapeutic targets. Transcriptomic datasets from macrophage and patient-derived samples were analyzed to identify differentially expressed genes, followed by functional enrichment and network-based analyses to identify key immune regulators. Non-synonymous SNPs (nsSNPs) were evaluated using multiple predictive tools (SIFT, PolyPhen-2, CADD, REVEL, MetaLR, Mutation Assessor), while structural impacts were assessed using DUET and Project HOPE. A total of 162 DEGs were identified, significantly enriched in immune-related pathways including cytokine signaling, receptor activity, and host defense responses. Five hub genes SELL, CD19, CD27, PRF1, and KLRK1 were prioritized, with SELL and PRF1 demonstrating the highest regulatory importance. Structural and functional analyses identified six deleterious nsSNPs in SELL (G169E, W309R, W247R) and PRF1 (V419G, V482G, P459S), all predicted to destabilize protein structure and impair immune function. Molecular docking and MM/GBSA analyses revealed favorable and energetically stable interactions between selected immunomodulatory compounds and both wild-type and mutant protein structures. Key ligand-residue interactions supported the potential of these compounds to modulate SELL- and PRF1-associated immune pathways. Notably, mutant variants showed enhanced ligand binding, with BIMOSIAMOSE displaying the highest affinity in SELL W309R (- 6.92 kcal/mol) and PRF1 mutants (- 5.35 kcal/mol), suggesting mutation-induced alterations in binding pocket conformation. Unlike previous single-cohort or single-method studies in tuberculosis, this work employs a multi-cohort, systems-level integrative framework to identify robust host immune signatures. By combining transcriptomic meta-analysis across diverse infection models with protein-protein interaction network prioritization, regulatory network inference, genetic variant impact assessment, and structure-based computational validation, we identified conserved immune-associated genes, particularly SELL and PRF1, as central regulatory nodes in tuberculosis pathogenesis. The integration of structural modeling, molecular docking, and molecular dynamics simulations further strengthens the mechanistic plausibility of these candidates. This multi-layered strategy provides a comprehensive framework for prioritizing biologically consistent biomarkers and therapeutic targets in tuberculosis, offering a systems-level perspective beyond traditional single-omics approaches.

Ross River virus (RRV), a mosquito‐borne alphavirus of the Togaviridae family, is the causative agent of Ross River fever a debilitating infectious disease characterized by fever, rash, and persistent polyarthritis. The virus remains endemic across Australia and the Pacific regions, with sporadic outbreaks reported in new geographic areas due to climate change and increased mosquito activity. Despite its growing public health impact, no licensed vaccine or antiviral therapy currently exists, underscoring the urgent need for an effective preventive strategy. In this study, an immunoinformatics‐based approach was employed to design a novel multi‐epitope vaccine (MEV) against RRV, where conserved and antigenic cytotoxic T‐lymphocyte (CTL), helper T‐lymphocyte (HTL), and B‐cell epitopes were predicted from structural proteins (capsid and envelope glycoproteins E1 and E2) as well as selected non‐structural protein regions, followed by their rational assembly into a vaccine construct using appropriate linkers and an immune‐stimulatory adjuvant. Conserved and antigenic cytotoxic T‐lymphocyte (CTL), helper T‐lymphocyte (HTL), and B‐cell epitopes were predicted from structural and non‐structural proteins and linked with appropriate linkers, while β‐defensin was incorporated as an adjuvant to enhance immunogenicity. The vaccine construct underwent modeling, refinement, and structural validation using PSIPRED, AlphaFold, and GalaxyRefine. Molecular docking analyses with immune receptors (TLR8 and HLA) and molecular dynamics (MD) simulations evaluated receptor binding affinity and structural stability. The C‐ImmSim server was used to simulate immune responses, and codon optimization ensured suitability for Escherichia coli expression. The designed MEV exhibited strong antigenicity (0.79), stability, and solubility, with a molecular weight of ~30 kDa and theoretical pI of 9.98. Structural validation revealed over 95% of residues in favored Ramachandran regions, and docking analysis showed predicted interaction with TLR8 (− 1712.2 kJ/mol). MD simulations confirmed stable complex formation, while immune simulations predicted robust and long‐lasting humoral and cellular immune responses with elevated IgG, IFN‐γ, and memory B/T‐cell populations. The designed MEV demonstrates promising antigenic, structural, and immunological properties, making it a potential vaccine candidate for further in vitro and in vivo evaluation against Ross River virus infection.

Background: Dengue virus (DENV), comprising four antigenically distinct serotypes (DENV1–4), continues to pose a major global health burden. The lack of a universally protective vaccine capable of inducing balanced immunity against all serotypes remains a critical challenge, largely due to antigenic diversity and the risk of antibody-dependent enhancement (ADE). Conserved capsid proteins represent promising targets for epitope-based vaccine development because of their structural stability and immunogenic potential. Methods: An integrated reverse vaccinology and immunoinformatics strategy was employed to design a conserved capsid-based multi-epitope vaccine (MEV-DV) targeting DENV1–4. B-cell, cytotoxic T-lymphocyte (CTL), and helper T-lymphocyte (HTL) epitopes were screened for antigenicity, non-allergenicity, non-toxicity, and sequence conservancy. Selected epitopes were assembled using appropriate linkers with β-defensin as an adjuvant and a PADRE sequence. The construct was evaluated for physicochemical properties, 3D structure modeling and validation, solubility, disulfide engineering, molecular docking with TLR4 and TLR8, molecular dynamics simulation, and immune simulation. Experimental validation was performed in albino mice using an alum-adjuvanted formulation, and humoral responses were assessed by hemagglutination inhibition (HI) assay. Results: The finalized MEV-DV construct exhibited high antigenicity (0.8559), favorable physicochemical properties, and structural stability, with 97.6% of residues located in favored Ramachandran regions. Docking studies demonstrated strong binding affinity with TLR4 and TLR8, and molecular dynamics simulations confirmed stable receptor–vaccine interactions over 50 ns. Immune simulations predicted robust humoral and cellular immune responses with sustained memory formation. In vivo immunization induced detectable antibodies by day 7, with peak HI titers at day 21. Antibody levels were statistically comparable to those elicited by a commercial inactivated dengue vaccine ( p > 0.05), and no adverse effects were observed. Conclusion: This study demonstrates that a conserved capsid-based multi-epitope vaccine designed through reverse vaccinology and immunoinformatics is structurally stable, immunogenic, and safe in a murine model. The combined computational and experimental findings support the potential of MEV-DV as a promising broadly protective dengue vaccine candidate and warrant further evaluation through neutralization assays and viral challenge studies.

In the intricate world of aquatic ecosystems, infectious pancreatic necrosis virus (IPNV) and viral hemorrhagic septicemia virus (VHSV) emerge as formidable threats to marine life, posing diverse diseases that reverberate through shared host species (Salmon, trout fishes). The coexistence of these viruses amplifies health risks, compelling the pursuit of inventive intervention strategies. Recognizing the urgency, a current and optimistic initiative strives to craft a revolutionary combined vaccine, offering protection against both IPNV and VHSV. This innovative endeavor, driven by an immunoinformatics approach, identifies immune-dominant epitopes from CadB and LamB proteins, ensuring the final vaccine’s immunogenicity, non-allergenicity, and enhanced solubility. Molecular dynamics simulations validate its binding stability and structural integrity. In a pivotal move, codon optimization using Escherichia coli K12 as a model result in an ideal guanine-cytosine content and a higher Codon Adaptation Index value, seamlessly integrating into the cloning vector pET2+ (a). In essence, our outcomes underscore the potential of this proposed peptide vaccine to elicit a robust immune response against both IHNV and VHSV, marking a breakthrough in the holistic management of infectious diseases in aquatic environments.

Pancreatic cancer is one of the most lethal malignancies worldwide, characterized by late diagnosis, aggressive progression, and poor survival. Dysregulation of regulated cell death (RCD) pathways, including apoptosis, ferroptosis, necroptosis, and mitochondrial dysfunction, contributes to tumor survival, therapy resistance, and immune evasion. Understanding the molecular mechanisms underlying these processes is critical for identifying prognostic biomarkers and therapeutic targets. Publicly available pancreatic cancer gene expression datasets (GSE227567 and GSE275246) were analyzed to identify differentially expressed RCD and mitochondrial genes. FRGs, APGs, NRGs, and MGs were intersected with the DEGs, followed by functional enrichment, protein-protein interaction (PPI) network construction, and hub gene prioritization. Co-expression, immune infiltration, and pathway activity analyses were performed across pathological stages and pan-cancer datasets. Missense SNPs in top hub genes ATF4 and PMAIP1 were evaluated for structural and energetic impact using HOPE and DynaMut. Analysis identified 448 FRGs, 73 APGs, 32 NRGs, and 930 MGs in GSE227567, and 123 APGs, 0 FRGs, 36 NRGs, and 577 MGs in GSE275246. Cross-dataset overlap was highest for APGs (116 genes), while other RCD and mitochondrial genes were largely dataset-specific. Filtering and PPI network analysis prioritized nine hub genes (ATF4, PMAIP1, BCL2L1, ATF3, TRADD, SRC, SFN, KCNMA1, GUK1). Functional enrichment highlighted mitochondrial metabolism, oxidative phosphorylation, and apoptosis pathways, with integration into PI3K-AKT, MAPK, p53, and VEGF signaling. Immune infiltration analysis revealed myeloid-enriched tumor microenvironments in mutant contexts. Pan-cancer and stage-wise expression profiling indicated that ATF4 and PMAIP1 exhibit consistent stage-dependent modulation. Survival analysis showed that high PMAIP1 expression correlates with poor prognosis (HR = 1.26, p = 0.00185), while ATF4 shows a protective trend (HR = 0.84, p = 0.0145). SNP analysis revealed six missense variants in each gene, with ATF4 variants predominantly destabilizing and affecting the bZIP domain, whereas PMAIP1 variants were mostly surface-exposed and modulatory. Our integrative analysis identifies ATF4 and PMAIP1 as key RCD- and mitochondrial-associated genes in pancreatic cancer, with functional SNPs that influence prognosis and may serve as therapeutic targets. These findings provide insights into mitochondrial-driven apoptosis, tumor progression, and potential avenues for precision medicine interventions.

Background: Latent tuberculosis infection (LTBI) is the principal reservoir for active tuberculosis, with >85% of cases attributable to reactivation. Bacillus Calmette-Guérin fails to block this transition, leaving a critical gap in prevention. Methods: An immunoinformatics/reverse-vaccinology pipeline was applied to seven dormancy-related antigens retrieved from Mycobrowser. T-cell epitopes were predicted with NetMHCI/IIpan-4.1 and B-cell epitopes with ABCpred; antigenicity, allergenicity, and toxicity were evaluated with VaxiJen, AllerTOP, and ToxinPred. Secondary/tertiary structures were modeled with PSIPRED and AlphaFold-3; docking to Toll-like receptors (TLR) 2/4 and 100 ns molecular dynamics simulations assessed complex stability. Immune responses were simulated with C-ImmSim, and the mRNA sequence was human-codon-optimized using ExpOptimizer. Results: The resulting construct, RP14914P, encodes 14 cytotoxic T lymphocyte, 9 helper T lymphocyte, and 14 B-cell epitopes within an 866-aa, 90.4 kDa polypeptide. Antigenicity score = 0.7797, immunogenicity score = 8.58629. and no toxicity or allergenicity was predicted. Physicochemical analysis: instability index = 28.65, and solubility = 0.513. Estimated population coverage is 82.35% and 99.67% for Human Leukocyte Antigen (HLA)-I and HLA-II globally. Docking energies: −1477.8 kcal/mol (TLR2) and −1480.1 kcal/mol (TLR4). Molecular dynamics trajectories confirm stable binding. Immune simulation predicts potent activation of Natural Killer cells, macrophages, and dendritic cells, Th1 polarization, high interferon-γ/interleukin-2 secretion, and durable memory. Conclusions: In silico analyses predict that RP14914P exhibits favorable immunogenicity, safety, and broad population coverage, suggesting its potential as a promising mRNA vaccine candidate to prevent LTBI reactivation. However, these computational predictions require thorough experimental validation to confirm the vaccine’s immunogenicity and protective efficacy.

Lung squamous cell carcinoma (LUSC) remains one of the most aggressive subtypes of non-small cell lung cancer (NSCLC), characterized by high mortality, therapeutic resistance, and molecular heterogeneity. Emerging evidence highlights the importance of regulated cell death (RCD) pathways including apoptosis, necroptosis, ferroptosis, and pyroptosis in determining tumor fate, immune evasion, and treatment response. However, the transcriptional regulators and genetic variants governing these cell death mechanisms in LUSC remain largely undefined. An integrative transcriptomic analysis of five GEO datasets (GSE146868, GSE204753, GSE268049, GSE236654, and GSE250509) was conducted to identify differentially expressed genes associated with apoptosis, necroptosis, ferroptosis, and pyroptosis, using curated gene sets from FerrDb v2.0, KEGG, Reactome, and GeneCards. Functional enrichment via GO and KEGG revealed strong activation of inflammatory, TNF, and necroptosis pathways. Protein–protein interaction networks (STRING) and hub analysis (Cytoscape–CytoHubba) identified core DE-RCDGs, while upstream transcriptional regulators were predicted with iRegulon and validated through UALCAN expression, hallmark enrichment, and survival datasets (TCGA, HPA). Finally, high-impact non-synonymous SNPs (nsSNPs) in key TFs were prioritized through a multi-layer bioinformatics pipeline (SIFT, PolyPhen 2, CADD, REVEL, MetaLR, Mutation Assessor) and structurally modeled to assess their functional impact. Network-based and regulatory enrichment analyses identified PPARG, STAT3, HIF1A, SMAD1, and ZBTB16 as central transcriptional regulators bridging apoptosis and necroptosis signaling in LUSC. Hallmark pathway enrichment highlighted their involvement in hypoxia response, TNF/NF-κB signaling, and metabolic reprogramming, underscoring their multi-faceted regulatory impact. Expression validation using TCGA/UALCAN confirmed significant upregulation of all five TFs in tumor tissues, with STAT3 and HIF1A exhibiting the most prominent oncogenic expression patterns. Survival analysis indicated that elevated STAT3 and HIF1A expression correlated with poorer overall survival, though independent validation via the HPA database revealed no significant survival separation, suggesting a context-dependent prognostic role. Variant analysis further revealed high-impact deleterious nsSNPs in both STAT3 (C712R; rs193922722 and Q633L; rs2144684101) and HIF1A (C255G; rs1242097924 and D55G; rs2044414353), each predicted to disrupt protein structural stability, metal-binding geometry, and interaction interfaces. Structural modeling confirmed conformational destabilization and altered residue orientation, consistent with potential impairment in transcriptional regulation and signaling fidelity. Current multi-omics analysis delineates STAT3 and HIF1A as central regulators coordinating apoptotic and necroptotic cross talk in LUSC. Deleterious nsSNPs within these TFs highlight structural vulnerabilities potentially driving tumor progression and therapeutic resistance, offering promising targets for precision-based intervention. Graphical Abstract

Dengue Virus Serotype 4 (DENV4) continues to contribute substantially to global dengue morbidity, yet current tetravalent vaccines provide inconsistent protection and may pose risks of antibody‐dependent enhancement (ADE). This study aimed to design and evaluate a serotype‐specific multi‐epitope vaccine (MEV‐DV4) targeting the conserved capsid protein of DENV4 using integrated reverse vaccinology and immunoinformatics approaches. Conserved, antigenic, non‐allergenic, and non‐toxic B‐cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were identified and assembled with a β‐defensin adjuvant and PADRE sequence using optimized linkers. The final construct demonstrated high antigenicity (0.8559), structural stability, favorable physicochemical properties, and excellent solubility. Structural validation confirmed 97.6% of residues in favored Ramachandran regions. Molecular docking revealed strong interactions with TLR4 and TLR8, particularly MEV–TLR8, and molecular dynamics simulations supported the overall stability of the complex. Immune simulations predicted robust humoral and cellular responses with strong memory formation. Experimental validation in an albino mouse model using an alum‐adjuvanted MEV‐DV4 formulation showed early and potent antibody responses, with peak HI titers at day 21. Notably, antibody titers induced by MEV‐DV4 were statistically comparable to those produced by a commercial inactivated dengue vaccine at all tested time points ( p > 0.05), while no adverse reactions were observed. These computational and experimental findings demonstrate that MEV‐DV4 is a safe, immunogenic, and promising serotype‐specific vaccine candidate against DENV4. Further neutralization and challenge studies are warranted to advance its preclinical development.