B.O.L.T. Scanner: Automated 3D Structural Coordinate Extraction for Viral Entry Residues (Zika, Ebola, Rabies)

A Python-based diagnostic suite that bridges the gap between genomic instructions and physical 3D coordinates. The B.O.L.T. (Bio-Operational Lock & Tooth) Scanner is a comprehensive tri-phase bio-intelligence system designed to identify and classify the physical mechanisms of viral infection at the atomic level. First, it functions as a Genomic Blueprint Auditor, utilizing NCBI E-utilities to download and verify raw genetic sequences (such as NC_012532.1 for Zika) to ensure the viral teeth are present in the code before physical analysis begins. Second, it acts as a High-Precision Spatial Radar, navigating complex 3D protein structures (PDB data) to extract the exact X, Y, Z coordinates of key residues, successfully bypassing structural shields like glycosylation umbrellas by recalibrating to stable anchors like the Position 107 Fusion Loop. Finally, the scanner serves as a Clinical Threat Classifier, grading the "bite force" of these residues based on their chemical properties distinguishing between Critical Hydrophobic Hooks and Supporting Electrostatic Magnets and automatically publishing these confirmed threats to a master library cross-referenced with global medical standards like ICD-10 A92.5. The B.O.L.T. system successfully addresses the 'Shielding Effect' in the Zika virus (ICD-10 A92.5) Envelope protein. While residues 150-154 are frequently obscured by glycan umbrellas in X-ray crystallography, the scanner utilizes a novel calibration to Position 107 (LEU), the stable Fusion Loop anchor, to achieve a 100% detection rate for spatial coordinate extraction.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-15
DOI
https://doi.org/10.5281/zenodo.18652801
Primary Topic
Viral Infections and Outbreaks Research
Type
article
Field-Weighted Citation Impact
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article

B.O.L.T. Scanner: Automated 3D Structural Coordinate Extraction for Viral Entry Residues (Zika, Ebola, Rabies)

Tatiana Haney
Zenodo (CERN European Organization for Nuclear Research)
Viral Infections and Outbreaks Research
article

B.O.L.T. Scanner: Automated 3D Structural Coordinate Extraction for Viral Entry Residues (Zika, Ebola, Rabies)

Tatiana Haney
article en

Abstract

A Python-based diagnostic suite that bridges the gap between genomic instructions and physical 3D coordinates. The B.O.L.T. (Bio-Operational Lock & Tooth) Scanner is a comprehensive tri-phase bio-intelligence system designed to identify and classify the physical mechanisms of viral infection at the atomic level. First, it functions as a Genomic Blueprint Auditor, utilizing NCBI E-utilities to download and verify raw genetic sequences (such as NC_012532.1 for Zika) to ensure the viral teeth are present in the code before physical analysis begins. Second, it acts as a High-Precision Spatial Radar, navigating complex 3D protein structures (PDB data) to extract the exact X, Y, Z coordinates of key residues, successfully bypassing structural shields like glycosylation umbrellas by recalibrating to stable anchors like the Position 107 Fusion Loop. Finally, the scanner serves as a Clinical Threat Classifier, grading the "bite force" of these residues based on their chemical properties distinguishing between Critical Hydrophobic Hooks and Supporting Electrostatic Magnets and automatically publishing these confirmed threats to a master library cross-referenced with global medical standards like ICD-10 A92.5. The B.O.L.T. system successfully addresses the 'Shielding Effect' in the Zika virus (ICD-10 A92.5) Envelope protein. While residues 150-154 are frequently obscured by glycan umbrellas in X-ray crystallography, the scanner utilizes a novel calibration to Position 107 (LEU), the stable Fusion Loop anchor, to achieve a 100% detection rate for spatial coordinate extraction.

Zenodo (CERN European Organization for Nuclear Research)
National Association for the Advancement of Colored People (US)
Openalex Percentile: Top 54%
Viral Infections and Outbreaks Research
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