Search Results (106)

Rhodococcus equi (R. equi) primarily induces fatal pulmonary and extrapulmonary pyogenic granulomatous infections in foals, imposing substantial economic burdens on the equine industry. The emergence and spread of multidrug-resistant (MDR) R. equi have led to a therapeutic impasse in clinical settings. Although vaccination is a proven strategy against MDR pathogens, no commercial vaccine is currently available for R. equi. In this study, we employed a bioinformatics approach to systematically identify and prioritize antigenic epitopes derived from R. equi for multi-epitope vaccine design. Using ABCPred, NetMHCpan EL, and IEDB servers, 27 MHC-I and 9 MHC-II epitopes were selected from five previously validated R. equi vaccine candidates: ABC transporter, PBD2, NlpC/P60, Esterase, and M23. These epitopes were coupled with distinct peptide linkers to construct six multi-epitope vaccine constructs, designated V1–V6. The physicochemical properties, antigenicity, immunogenicity, and toxicity of the six vaccine constructs were analyzed, and the V3 and V4 constructs were ultimately selected. Using the HDOCK and Gromacs tools, the intermolecular interactions, binding affinity, and thermal stability of the V3 and V4 constructs with the equine MHC molecules EQCA-I and EQCA-II were evaluated. The results confirm that V3 and V4 exhibit strong binding affinity to EQCA-I and EQCA-II, with stable conformations following binding, indicating theoretical potential to induce humoral and cellular immunity in foals. Recombinant plasmids for V3 and V4 were constructed, and the V3 and V4 proteins were successfully prepared, confirming the feasibility of prokaryotic expression for these vaccine constructs. Immunization assays in SPF BALB/c mice showed that the multi-epitope vaccines elicited robust antigen-specific IgG antibody responses, reflecting preliminary humoral immunogenicity. However, these murine data have translational limitations, as they cannot fully represent equine immune responses. The findings establish a crucial theoretical foundation for the advancement of vaccines targeting R. equi while offering a reference for the design of vaccines against other drug-resistant microbial pathogens. Full article

Molecular mechanics/the Poisson–Boltzmann surface area (MM-PBSA) is a popular method for binding energy estimation. Several programs have been developed for performing MM-PBSA calculations in conjunction with Gromacs, the most popular molecular dynamics (MD) software. However, current programs are limited to Linux-based systems and lack cross-platform usability. To address this, we present s_mmpbsa, a lite and cross-platform MM-PBSA program, to support binding energy calculation on native Windows platforms without a subsystem. By incorporating electrostatic screening and interaction entropy, s_mmpbsa achieves improved binding free energy calculation accuracy, validated on a dataset of HIV-1 protease inhibitor complexes. In addition, s_mmpbsa achieves enhanced performance with g_mmpbsa in the same parameters and conditions. Indeed, s_mmpbsa offers an efficient and practical solution for interaction energy calculation from MD simulations in Gromacs, providing valuable protocols for further molecular design applications such as computational enzyme design and molecular screening. Full article

Background/Objectives: KRAS G12D is one of the most frequent oncogenic mutations in pancreatic ductal adenocarcinoma (PDAC) and remains challenging to target because of its limited druggable binding pockets. This study aimed to develop a machine learning-based framework for rapid virtual screening of potential KRAS G12D inhibitors. Methods: A molecular–protein fusion prediction framework, MPFF-IS, was constructed by integrating the ESM2 protein language model with an MPNN-GNN molecular graph network to enable joint representation learning of protein and compound features. The model was trained using a KRAS G12D inhibitor dataset and applied to screen compounds from multiple chemical libraries. AutoDock Vina docking and 300 ns GROMACS molecular dynamics simulations were subsequently performed for structural validation. Results: MPFF-IS achieved favorable predictive performance on the test dataset and identified 2663 candidate compounds from more than 134,000 screened molecules. Several candidate ligands exhibited favorable binding affinity, stable proteinligand interactions, and enhanced structural stability compared with reference inhibitors, including MRTX1133 and BI-2852. Molecular dynamics analyses further supported the stability of the predicted complexes and the involvement of key binding residues within the KRAS G12D pocket. Conclusions: These findings demonstrate that MPFF-IS can efficiently identify potential KRAS G12D inhibitors and may provide a useful computational framework for precision drug discovery targeting difficult oncogenic proteins. Full article

Monkeypox virus (MPXV) is emerging as a global public health concern due to its nature of spread. There are limited treatment options, as the sole drug for treatment is lacking, highlighting the need for new therapeutic options. The use of computer-aided drugs discovery such as molecular docking, molecular dynamic (MD) simulations and post-simulation analysis are important tools in identifying potential compounds that can target specific proteins of the virus, such as DNA polymerase to stop virus replication. This study employed molecular docking and molecular simulation with the aim to identify potential inhibitors for MPXV treatment from the ZINC Database. Molecular docking was performed using PyRx 0.8 version after virtual screening of the ZINC database using the Tranches tool; then, toxicity prediction of the selected compounds was performed using the ProTox-3.0 web server. Molecular dynamics simulation was conducted using GROMACS version 4.5 to evaluate the structural stability and dynamic behavior of the protein–ligand complex for the best interacting compound. Furthermore, post-simulation analysis was conducted using standard GROMACS utilities for visualizing time-dependent properties from MD simulations. A total of 16 compounds were shortlisted based on their molecular docking scores and interaction profiles with the monkeypox virus DNA polymerase (PDB ID: 8HG1). The leading compound, ZINC000019418450, demonstrated strong binding affinity (−7.4 kcal/mol). According to post-simulation analysis, all top compounds formed between one and five hydrogen bonds and up to eleven hydrophobic contacts with residues within the active site, thus providing strong geometric and energetic evidence for binding stability. Notably, our identification of ZINC000104288636 as a Class 6 compound with an LD₅₀ of 23,000 mg/kg adds translational value by highlighting candidates with low predicted acute toxicity. Overall, this study lays a solid foundation for the rational design of next-generation monkeypox antiviral therapeutics. Future work is needed for experimental validation of prioritized compounds to assess their biochemical efficacy and pharmacological potential. Full article

In the pathological cascade of cerebral ischemia, the pyroptosis axis mediated by the NLRP3 inflammasome in activated microglia is a core link driving neuroinflammation and secondary brain injury. Quercetin has been proven to possess multi-target neuroprotective activity, and its anti-inflammatory effect has attracted particular attention. However, direct molecular evidence is lacking regarding how quercetin precisely regulates the NLRP3/Caspase-1/GSDMD core pyroptosis axis in microglia in cerebral ischemia models and whether it can directly target NLRP3 to inhibit this axis, thereby alleviating cerebral ischemic injury. This study aimed to investigate the molecular mechanism by which quercetin alleviates cerebral ischemic injury through inhibiting the pyroptosis axis, combining cellular and animal models with molecular docking and molecular dynamics simulations. The oxygen-glucose deprivation (OGD) model of BV2 microglia and the photothrombotic (PT) model of focal cortical ischemia in male C57BL/6 mice were used to detect the ameliorative effect of quercetin on cerebral ischemia-related injury through cellular and animal experiments. AutoDock Vina 1.5.7 and GROMACS 2025.3 software were employed for molecular docking and molecular dynamics simulations, respectively, to analyze the binding mode and complex stability between quercetin and the NLRP3 protein. The results showed that quercetin could significantly ameliorate OGD-induced injury in BV2 cells and downregulate the expression of pyroptosis and inflammation-related proteins and factors. Meanwhile, it relieved motor dysfunction in PT mice, attenuated cortical neuronal injury, and inhibited the activation of the cerebral pyroptosis axis. At the molecular level, molecular simulation predictions indicated that quercetin might specifically bind to the NACHT domain of the NLRP3 protein, forming a complex with a stable conformation, and van der Waals interactions served as the main driving force for binding. This study confirmed that quercetin can directly bind to the NLRP3 protein and alleviate cerebral ischemia-induced inflammatory injury by inhibiting the activation of the NLRP3/Caspase-1/GSDMD pyroptosis axis and the release of downstream inflammatory factors. Combined with the molecular simulation results, a predictive hypothesis is proposed: direct binding of quercetin to the NLRP3 protein is one of its core mechanisms of action. These findings provide direct experimental evidence for the development of NLRP3-based drugs against ischemic brain injury. Full article

Microplastics (MPs) are pervasive in marine ecosystems, yet the molecular mechanisms underlying their sublethal effects on zooplankton remain poorly understood. Here, we integrated transcriptomic screening with sequence homology analysis, structural modeling, and molecular dynamics (MD) simulations to examine protein–polymer interaction behavior in the tropical euphausiid Euphausia distinguenda. Transcriptomic analysis identified three MP-responsive proteins; two isoforms (P1, P2) were consistently downregulated following exposure to polyethylene microspheres, while a third candidate (P3) was upregulated but excluded from modeling due to insufficient homology. Structural models of P1 and P2 were generated using AlphaFold2 (ColabFold implementation) and evaluated through comparative structural analyses. MD simulations (100 ns) were conducted using representative polymer oligomers LDPE used as a polyethylene analog and PET and PC included as contrast polymers, which revealed pronounced protein-specific differences and polymer-dependent modulation of interaction stability. Nonbonded Lennard–Jones and Coulomb interaction energies indicated substantially greater intermolecular contact stabilization for P2 than for P1 across all polymers, with LDPE yielding the lowest mean polymer RMSD for P2, and PET for P1. Together, these results indicate that MP–protein interactions in E. distinguenda are consistent with a dominant role of protein structural coherence and dynamic surface compatibility rather than by static structural complementarity or specific binding affinity and provide a reproducible basis for exploring molecular-scale responses to MP exposure in ecologically relevant zooplankton. Full article

Rapid antigenic drift in the coronavirus spike protein motivates alternative antiviral strategies. We target the conserved nucleocapsid (N) protein—central to RNA binding, genome packaging, and replication—and perform a comparative, cross-species 3D structure-based in silico evaluation. A library of 494 compounds (natural, phytochemical, synthetic) was docked with AutoDock Vina against the MERS-CoV N–terminal RNA–binding domain (NTD; PDB 7DYD) and the C–terminal dimerization domains (CTD) of SARS-CoV (2CJR) and SARS-CoV-2 (8R6E), reflecting the availability of high-resolution, functionally relevant domain structures for each virus. Top-ranked poses underwent ADME profiling and 100 ns GROMACS molecular-dynamics (MD) simulations. Myricetin 3-O-β-D-Galactopyranoside (myricetin) showed the most favorable predicted docking scores across targets (−8.9 kcal/mol, MERS–NTD; −10.1, SARS–CTD; −9.8, SARS-CoV-2 CTD). Curcumin showed moderate predicted affinity (−7.1 to −8.1), while MCC950 achieved consistently favorable docking score (−7.9 to −9.0). ADME results highlighted a trade-off: glycosylated flavonoids offered rich interaction networks but violated oral drug-likeness criteria (e.g., high TPSA), whereas MCC950 met Lipinski/Veber guidelines, supporting translational potential. MD analyses revealed ligand- and target-specific stability: myricetin maintained persistent binding over 100 ns in the SARS-CoV-2 CTD with lower RMSD than comparators; curcumin exhibited transient stability (~30 ns) in MERS- and SARS-bound complexes; MCC950 showed intermittent interactions. Collectively, these findings suggest that the conserved N protein RNA-binding groove represents a resistance-resilient target for broad-spectrum antiviral discovery. Natural flavonoids provide promising scaffolds for optimization, and MCC950 warrants further exploration given its drug-like profile. As this study is purely computational, the results are hypothesis-generating and should be validated via RNA-binding disruption assays, antiviral cell studies, and in vivo models. Full article

Background: The extracellular-signal-regulated kinase (ERK) cascade regulates cell proliferation, differentiation, and survival, and ERK2 mediates substrate phosphorylation, influencing gene expression and cellular functions. Methods: In the current study, a pool of new molecules was generated using the DeLA-Drug, a machine learning (ML)-assisted de novo design tool. The chemical space was reduced through a similarity search against active ERK2 inhibitors and molecular docking with AutoDock vina, followed by pharmacokinetic assessment in DeepPK. Poses of the final selected molecules were refined in DiffDock, and dynamicity was assessed through molecular dynamics (MD) simulation. Finally, the free-energy perturbation (FEP)-based binding affinity was explored in Gromacs2023.4. Results: From the above approaches, four molecules (Ek1, Ek2, Ek3, and Ek4) were identified as promising candidates with favorable binding interactions. Molecular docking revealed that the selected molecules exhibited higher binding affinity for ERK2, ranging from −9.50 to −10.50 kcal/mol. The dynamics assessment via MD simulation clearly revealed their strong association with ERK2, corroborated by the lower deviation of the ERK2 backbone in dynamic states. All four screened molecules have satisfactory pharmacokinetic properties, medicinal chemistry properties, and good synthetic accessibility scores, indicating their potential as drug-like compounds under Lipinski’s rule of five to inhibit or modulate ERK2 activity. The FEP energy of Ek1 was found to be −26.85 kJ/mol, which is higher than the standard molecule (−22.77 kJ/mol) and indicates its strong affinity toward ERK2. Conclusions: These results suggest that all proposed ERK2 modulators are potential avenues for future drug discovery targeting ERK2, subject to experimental validation. Full article

Hydrogel fluorescent microspheres function as versatile tracers with applications spanning across biomedicine, complex plasma systems, hydrodynamics, and drug delivery. However, the controlled release of fluorescent material in hydrogel microspheres is challenging to achieve. The fluorescent hydrogel microsphere (namely poly(ethylene glycol) diacrylate@rhodamine B-tannic acid, PEGDA@RhB-TA) was fabricated by incorporating tannic acid and RhB into PEGDA microspheres. The stable encapsulation and responsive release of RhB can be achieved by leveraging the non-covalent interactions between TA and RhB. RhB was stably encapsulated within PEGDA microspheres through noncovalent interactions (hydrophobic interactions, hydrogen bonding, π–π, and ion–π interactions) between RhB and TA. Both molecular dynamics simulations by GROMACS and experimental results confirmed the noncovalent binding mechanisms between RhB and TA. The microspheres retained RhB following 24 h immersion in a highly concentrated salt solution (1 M NaCl) and exhibited minimal RhB release (7.1%) under heating at 80 °C for 24 h. However, PEGDA@RhB-TA microspheres underwent rapid RhB release in a 50% v/v ethanol–water solution, liberating 73% of the encapsulated dye within 24 h. TA within the PEGDA@RhB-TA microsphere acts as a molecular lock by forming non-covalent interactions with RhB, significantly enhancing the stability of encapsulated RhB, and enabling the responsive release of RhB under specific conditions. Upon introduction into a microfluidic chip, PEGDA@RhB-TA microspheres enable the calculation of flow velocity through position tracking using high-speed camera imaging and fluorescence microscopy. These microspheres overcome the dual challenges of tracer stability and controlled release, making them suitable for fluid tracing and measuring flow rates. Full article

Background/Objectives: Software is now core infrastructure in biomedical science, yet fragmented workflows across subfields hinder reproducibility and delay the translation of data into actionable decisions. There is a critical need for a cross-disciplinary synthesis to bridge these silos and establish a unified framework for software maturity. This narrative review addresses this gap by synthesizing representative software ecosystems across three major pillars: bioinformatics, molecular modeling/simulations, and epidemiology/public health. Methods: A narrative review of articles indexed in PubMed/NCBI, Web of Science, and Scopus between 2000 and 2025 was conducted. Domain-specific terms related to bioinformatics, molecular modeling, docking, molecular dynamics, epidemiology, public health, and workflow management were combined with software- and algorithm-focused keywords. Studies describing, validating, or applying documented tools with biomedical relevance were included. Results: Across domains, mature data standards and reference resources (e.g., FASTQ, BAM/CRAM, VCF, mzML), widely adopted platforms (e.g., BLAST+ (v2.16.0, NCBI, Bethesda, MD, USA), Bioconductor (v3.20, Bioconductor Foundation, Seattle, WA, USA), AutoDock Vina (v1.2.5, Scripps Research, La Jolla, CA, USA), GROMACS (v2024.3, GROMACS Team, Stockholm, Sweden), Epi Info (v7.2.6, CDC, Atlanta, GA, USA), QGIS (v3.40, QGIS.org, Gossau, Switzerland), and increasing use of workflow engines were identified. Software pipelines routinely transform molecular and surveillance data into interpretable features supporting hypothesis generation. Conclusions: Integrated, standards-based, and validated software pipelines can shorten the path from measurement to decision in biomedicine and public health. Future progress depends on reproducibility practices, benchmarking, user-centered design, portable implementations, and responsible deployment of machine learning. Full article

We present a computational study that precedes the potential interactions between SARS-CoV-2 helicase (NSP13) and selected host proteins implicated in chaperone-assisted folding and polyamine metabolism. Using structure-based modelling and protein–protein docking (BioLuminate v4.6), followed by all-atom molecular dynamics (MD) simulations (GROMACS v2018.6), and comparative MM-GBSA scoring (HawkDock v2), we evaluated the stability and interface properties of NSP13 complexes with cytosolic heat shock proteins; heat shock protein 40 (HSP40), heat shock protein 70 (HSP70), heat shock protein 90 (HSP90) and the polyamine biosynthesis enzyme ornithine decarboxylase (ODC). Docking, MD, and interface analyses indicate distinct complex behaviours: HSP70-NSP13 complexes sampled compact conformations, HSP90-NSP13 ensembles displayed greater conformational heterogeneity but more favourable comparative MM-GBSA estimates, and ODC-NSP13 interfaces were comparatively well packed. Per-residue contact mapping identified a small set of recurrent NSP13 residues, Lys22 and Asn51, as putative interaction hotspots. The reported findings herein generate testable hypotheses about NSP13 recruitment of host chaperones and modulation of polyamine metabolism that may inform downstream experimental studies. Full article

Cedrus atlantica wood tar (CAWT) is traditionally used as a medicinal product, especially in low- and middle-income countries. Despite its traditional use, scientific support for its efficacy remains limited. This study evaluated the biological properties of CAWT using an integrated approach that combined qualitative and quantitative phytochemical analysis, disc diffusion and microdilution tests for antimicrobial assays (disc diffusion and microdilution), antioxidant activity (DPPH and ferric-reducing power assays), in silico ADMET/toxicity, docking, and MD/MMGBSA and provided a balanced comparison with reference antioxidants. This study demonstrated that CAWT is rich in secondary metabolites linked to biological activity, including polyphenols (307.39 ± 58.45 mg GAE/g), tannins (124.42 ± 6.14 mg TAE/g), and flavonoids (15.62 ± 2.53 mg QE/g). For free radical scavenging, CAWT inhibited DPPH with an IC50 of 19.781 ± 2.51 µg/mL and showed ferric-reducing activity with an IC50 of 83.7 ± 2.88 µg/mL for its antimicrobial activity against Pseudomonas aeruginosa; inhibition zones reached 35.66 ± 0.58 mm. In silico analysis, Swiss ADMET and pkCSM predicted ≥94% intestinal absorption, no cytochrome P450 liabilities, and low acute toxicity for six dominant terpenoids. Docking pinpointed trans-cadina-1(6),4-diene and α/β-himachalene as high-affinity ligands of LasR and gyrase B (ΔG ≈ −8 kcal mol⁻¹). A 100 ns GROMACS run confirmed stable hydrophobic locking of the lead LasR complex (RMSD 0.22 nm), while MM/GBSA calculated a dispersion-dominated binding free energy of −37 kcal mol⁻¹. Overall, CAWT showed in vitro antioxidant activity (DPPH and ferric-reducing assays) and inhibitory effects in disc diffusion assays, while in silico predictions for major terpenoids suggested favorable oral absorption and low acute toxicity. However, chemical composition analysis and bio-guided fractionation are necessary to confirm the antimicrobial activity and to validate the compounds responsible for the observed effects. Full article

Carbapenem-resistant Enterobacterales (CREs) pose a critical threat to global public health, largely driven by the enzymatic activity of Klebsiella pneumoniae carbapenemase-2 (KPC-2), a class A serine β-lactamase that hydrolyzes most β-lactam antibiotics. While β-lactamase inhibitors like avibactam offer temporary relief, emerging KPC variants demand novel, sustainable inhibitory scaffolds. This study aimed to identify and characterize potential natural inhibitors of KPC-2 from Pongamia pinnata, leveraging a comprehensive in silico workflow. A curated library of 86 phytochemicals was docked against the active site of KPC-2 (PDB ID: 3DW0). The top-performing ligands were subjected to ADMET profiling (pkCSM), and 100 ns molecular dynamics simulations (GROMACS) to evaluate structural stability and interaction persistence, using avibactam as control. Ponganone V exhibited the most favorable binding energy (−9.0 kcal/mol), engaging Ser70 via a hydrogen bond and forming π–π interactions with Trp105. Glabrachromene II demonstrated a broader interaction network but reduced long-term stability. ADMET analysis confirmed high intestinal absorption, non-mutagenicity, and absence of hERG inhibition for both ligands. Molecular dynamics simulations revealed that Ponganone V maintained compact structure and stable hydrogen bonding throughout the 100 ns trajectory, closely mirroring the behavior of avibactam, whereas Glabrachromene II displayed increased fluctuation and loss of compactness beyond 80 ns. Principal Component Analysis (PCA) further supported these findings, with Ponganone V showing restricted conformational motion and a single deep free energy basin, while avibactam and Glabrachromene II exhibited broader conformational sampling and multiple energy minima. The integrated computational findings highlight Ponganone V as a potent and pharmacologically viable natural KPC-2 inhibitor, with strong binding affinity, sustained structural stability, and minimal toxicity. This study underscores the untapped potential of Pongamia pinnata phytochemicals as future anti-resistance therapeutics and provides a rational basis for their experimental validation. Full article

The transition to sustainable aviation fuel (SAF) is critical for reducing the carbon footprint of the aviation sector while ensuring compatibility with current engines and infrastructure. Regulatory constraints, such as ASTM D7566, currently limit SAF blending to 50% in commercial flights, emphasizing the need for accurate evaluation of SAF properties to enable broader adoption. This review presents an updated overview of fuel studies evaluating key thermophysical and transport properties of hydrocarbon-based SAFs—including density, viscosity, specific energy, flash point, and thermal stability—with particular emphasis on molecular dynamics (MD) simulations. Among the MD simulations, the OPLS-AA force field demonstrates high accuracy in modeling liquid-phase hydrocarbons and shows strong agreement with experimental data. Coupled with MD engines like LAMMPS and GROMACS, it enables scalable and efficient simulations of SAF blends. Emerging research trends highlight integrative approaches that combine classical MD and machine learning (ML) in fuel property prediction, and force-field optimization to improve predictive capability. Future research in fuel is moving toward multi-force-field coupling using reactive frameworks such as ReaxFF for studying pyrolysis and oxidation, and data-driven experiments with in situ simulation feedback loops to accelerate SAF design and facilitate wider implementation in aviation. Full article

Cholangiocarcinoma is a rare but highly lethal cancer of the biliary epithelium, marked by heterogeneous molecular subtypes, unclear etiology, and poor five-year survival, highlighting the need for new diagnostic and therapeutic strategies; therefore, this study integrates genomic, transcriptomic, single-cell, methylomic, and molecular-dynamics data to pinpoint pathogenic variants. We performed an integrative multi-omics analysis of publicly available datasets. Somatic variants from 23 tumor samples in The Cancer Genome Atlas were annotated with 11 pathogenicity tools (AUC ≥ 0.86 across EVE, REVEL, SIFT, AlphaMissense, DEOGEN2 were the most stringent). Differential gene expression was assessed in matched bulk RNA-seq (tumor vs. non-tumor) using DESeq2 with Benjamini–Hochberg FDR correction. A single-cell RNA-seq dataset comprising 23,782 cells from an intrahepatic cholangiocarcinoma was clustered with marker genes identified by Wilcoxon rank-sum tests. Illumina 450 K methylation arrays (52 tumors, 12 normal livers) were analyzed with limma and DMRcate to detect differentially methylated probes and regions. AlphaFold3 models of wild-type and MAP2K1^R49C were subjected to 50 ns all-atom molecular-dynamics simulations in GROMACS; conformational shifts were quantified by RMSD/RMSF and stability tested with FoldX5. Twenty-four tumor-specific missense variants were detected. The four highest-confidence pathogenic substitutions (EVE, REVEL, SIFT, AlphaMissense, DEOGEN2) occurred in TUBB3, FLNC, ABCA1, and MAP2K1. Bulk RNA-seq confirmed significant dysregulation of these genes and enrichment of extracellular-matrix organization, cytoskeletal remodeling, MAPK signaling, and cholesterol-efflux pathways. Single-cell analysis resolved 23 transcriptionally distinct clusters; proliferative malignant cholangiocytes selectively over-expressed ABCA1 and MAP2K1, indicating tumor-cell specificity. Methylome profiling identified 148,928 DMPs and 7040 DMRs; promoter hypomethylation of TUBB3 and ABCA1 correlated with their transcriptional activation. Substituting Arg-49 with Cys in MAP2K1 dismantles the Arg-centred hydrogen-bond/salt-bridge cluster, reduces hydrophobic packing, and, corroborated by 50 ns MD (Welch’s t = −58.06, p = 3.17 × 10⁻²³⁰) and FoldX5 ($\mathrm{\Delta }\mathrm{\Delta }$G = +2.3 kcal mol⁻¹), significantly destabilises the protein, manifesting as higher backbone RMSD and increased local flexibility relative to wild type. This multi-omics, public data-driven synthesis delineates a coherent network of genomic, epigenomic, transcriptomic, and structural vulnerabilities, offering a rational framework for therapeutic targeting of cholangiocarcinoma. This study reveals novel bile duct-associated variations that expand our understanding of cholangiocarcinoma pathogenesis and provide potential targets for precision medicine approaches. Full article