Axis Mũndũ: A Computational Framework for Structural Stasis Analysis and Vaccine Target Prioritization During the 2026 Bundibugyo Ebolavirus Emergency
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This preprint presents the Axis Mũndũ Computational Framework, an interdisciplinary computational biology approach developed in response to the 2026 Bundibugyo orthoebolavirus (BDBV) outbreak in East-Central Africa. The framework integrates structural biophysics, thermodynamic modeling, machine learning, immunoinformatics, and low-resource computational architectures to investigate viral stability, therapeutic vulnerabilities, and vaccine target discovery.
The study introduces a novel structural classification methodology based on parity-state analysis and thermodynamic stasis mapping, implemented through the RNASmartSpine architecture and a Stasis-Breaker simulation engine. Using genomic and proteomic datasets, the framework identifies candidate regions associated with structural stability, models perturbation-induced conformational disruption, and evaluates multi-epitope vaccine constructs using antigenicity, allergenicity, HLA-binding affinity, cross-homology assessment, and accessibility-aware prioritization.
Key contributions include:
Development of the Axis Mũndũ structural stasis framework for pathogen analysis.
Introduction of the RNASmartSpine low-resource structural prediction architecture.
Computational identification of candidate BDBV vaccine epitopes.
Accessibility-integrated immunogenicity auditing for epitope prioritization.
Comparative oncovirology analysis involving HPV-16 and KSHV.
Policy recommendations for decentralized African computational biodefense and scientific sovereignty.
This work is presented as a computational and theoretical preprint. All findings remain subject to experimental validation through structural biology, immunological assays, animal studies, and clinical investigation.
Associated datasets, computational outputs, and methodological documentation are provided to support independent replication, benchmarking, and future refinement.