BackgroundAplastic anaemia is a haematological disorder characterized by immune-mediated destruction of haematopoietic stem cells and bone marrow failure. Although immunosuppressive therapies are currently used, their lack of target specificity underscores the need for systematic approaches to identify precise therapeutic targets and explore drug repurposing opportunities.MethodsA hybrid computational framework integrating literature-based discovery and database-driven validation was employed to construct a multi-layered biomedical knowledge graph. Semantic predications were extracted from SemMedDB and filtered using Unified Medical Language System semantic types to identify disease-, gene-, and drug-related entities. A tripartite disease–gene–drug network was constructed and subsequently extended into a heterogeneous knowledge graph by incorporating pathway-level interactions derived from enrichment analysis using clusterProfiler and KEGG. Drug–gene associations were further supported using curated resources such as DrugBank and DGIdb. Validation of gene–disease associations was performed using DisGeNET.ResultsThe constructed knowledge graph revealed key genes, including CSF2, IL6, EPO, HLA-DRB1, and CD4, which are central to immune dysregulation and haematopoietic impairment. Pathway enrichment analysis identified critical pathways such as haematopoietic cell lineage, JAK–STAT signaling, cytokine–cytokine receptor interaction, and MAPK/ERK cascades, highlighting the interplay between immune signaling and bone marrow dysfunction. Integration of drug-related predications enabled the identification of both clinically used immunosuppressants and potential repurposing candidates, including mycophenolate mofetil, mizoribine, everolimus, and camostat mesylate. Mechanistic mapping of these drugs to key pathways suggests their potential to modulate aberrant immune responses and restore haematopoietic balance.ConclusionThis study demonstrates the utility of a knowledge graph–based framework for integrating heterogeneous biomedical data to uncover multi-level interactions in aplastic anaemia. The approach enables systematic identification of biologically relevant genes, pathways, and drug candidates, supporting hypothesis-driven drug repurposing. While the findings are supported by literature and database validation, they remain exploratory and warrant further experimental and clinical investigation.
Leptospirosis, a widespread zoonotic disease caused by pathogenic spirochetes of the genus Leptospira, represents a severe global public health and economic burden. The pathogenic success of Leptospira relies on a complex repertoire of virulence factors, including proteases that facilitate tissue invasion, nutrient acquisition, and immune evasion. While carboxypeptidases play critical roles in bacterial cell wall maintenance and virulence in several pathogens, the functional and structural characteristics of these enzymes in Leptospira remain poorly understood. This study performed a comprehensive in silico characterization of nine predicted carboxypeptidases from Leptospira interrogans serovar Copenhageni strain Fiocruz L1-130, evaluating physicochemical properties, subcellular localization, operon organization, and sequence conservation were evaluated. Additionally, functional domains were annotated, tertiary structures were modeled and virulence signatures, allergenic profiles, and T- and B-cell epitopes were systematically assessed. These in silico data suggest that L. interrogans putative carboxypeptidases are highly conserved and may play roles in host-pathogen interactions. Structural and immunogenic profiling indicates that LIC_12303 and LIC_13152 are potential candidates for the development of novel subunit vaccines against leptospirosis.
IntroductionCisplatin is an effective chemotherapeutic agent; however, oxidative stress and apoptosis-associated signalling contribute to both its therapeutic effects and dose-limiting toxicities. This study investigated the phytochemical composition and antioxidant properties of Magnolia officinalis bark extract and explored the predicted interactions of selected constituents with the apoptosis-associated proteins caspase-3 and BCL-2.MethodsPhenolic and flavonoid contents, DPPH and ABTS radical-scavenging activities, chromatographic–mass spectrometric profiling, molecular docking, pharmacokinetic and toxicity predictions, 100-ns molecular dynamics simulations, and MM/GBSA calculations were employed.ResultsAmong the solvent extracts evaluated, the methanolic extract exhibited the highest phenolic (64.55 ± 0.65 mg GAE/g dry extract) and flavonoid (21.90 ± 0.55 mg QE/g dry extract) contents. It also demonstrated concentration-dependent DPPH and ABTS radical-scavenging activities, with IC₅₀ values of 143.02 and 326.01 µg/mL, respectively. Phytochemical profiling provided tentative evidence for multiple constituents, with magnolol and honokiol prioritised for computational evaluation. Molecular docking and dynamics analyses indicated predicted protein–ligand interactions and complex-specific conformational behaviour, including substantial magnolol displacement or rearrangement in the caspase-3 system during approximately 45–65 ns.DiscussionThe findings provide insights into the antioxidant and phytochemical properties of Magnolia officinalis bark extract and identify candidate constituents for further investigation. However, the computational results are hypothesis-generating and do not establish functional modulation of caspase-3 or BCL-2. Because cisplatin exposure and target-specific activity were not experimentally evaluated, conclusions regarding cytoprotection, chemosensitisation, or target activation/inhibition cannot be drawn. Further validation using target-specific biochemical assays and cisplatin-exposed cellular models is warranted.
Circular RNAs are specialized single-stranded molecules having covalently closed termini. They were once thought to be mere transcriptional artefacts. However, they have now been identified as significant players in tumorigenesis, neurodegeneration and other diseases. Though generally classified as non-coding, certain circular RNAs demonstrate the ability to encode proteins, reshaping our understanding of their biological roles. CircAβ-a, a circRNA that contains the amyloid beta (Aβ)-coding region of the APP gene, acts as an alternative source of Aβ peptides. The discovery of circAβ-a suggests that Aβ peptides can be generated through a non-canonical translation mechanism, independent of APP processing and that Aβ peptides are the key contributors to Alzheimer’s Disease pathogenesis. CircAβ-a is efficiently translated into Aβ175, which is further processed into Aβ peptides. Inhibiting circAβ-a translation or modifying its expression might help in reducing Aβ accumulation in brain. To develop effective inhibitors for Aβ peptides, it is crucial to understand its structural characteristics, functional properties and interaction patterns. This study focuses on characterizing the Aβ175 protein by predicting its structural features to explore its potential as an alternative biomarker, which can be verified through wet-lab experiments, for the treatment of Alzheimer’s Disease.
