RESEARCH PAPER
Integration of proteomics and bioinformatics in traumatic
brain injury biomarker discovery
1
Department of Basic Sciences, Faculty of Physical Therapy, Alryada University for Science and Technology, Egypt
2
Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Egypt
3
Department of Biomedical Equipment, Faculty of Applied Health Sciences Technology, October 6 University, Egypt
4
Faculty of Health Sciences Technology, Borg Al Arab Technological University, Alexandria, Egypt
These authors had equal contribution to this work
Submission date: 2024-08-19
Final revision date: 2025-02-26
Acceptance date: 2025-02-28
Corresponding author
Mohamed E. Hasan
Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Egypt.
Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Egypt.
BioTechnologia 2025;106(2):123-150
KEYWORDS
TOPICS
ABSTRACT
Background:
Traumatic brain injury (TBI) is a significant medical crisis with no FDA-approved therapies to improve functional outcomes. Key biomarkers, such as glial fibrillary acidic protein (GFAP), S-100 calcium-binding protein B (S-100B), and ubiquitin C-terminal hydrolase L1 (UCH-L1), are crucial for understanding TBI pathology.
Material and methods:
This study integrates proteomic and bioinformatic approaches to explore established TBI biomarkers’ structural and functional complexities: GFAP, S-100B, and UCH-L1.
Results:
Our comprehensive secondary structure and solvent accessibility assessment, conducted with PredictProtein, confirmed the predominance of alpha-helices in GFAP and S-100B, while UCH-L1 displayed a balanced mix of helices (65.00, 67.39, and 40.81%), beta strands (6.20, 0, and 17.94%), and coils (40.81, 17.94, and 41.26%). AlphaFold and I-TASSER were identified as the best servers for full-length tertiary structure prediction for the three target proteins, based on root-mean-square deviation (RMSD), TM-score, and C-score assessments. Protein motif database scans predicted four, eight, and one protein-binding motifs and two, three, and one post-translational modifications for GFAP, S-100B, and UCH-L1, respectively.
Conclusions:
GFAP’s role in axonal transport and synaptic plasticity was emphasized through motifs such as Filament and DUF1664. S-100B’s association with neuroinflammation and oxidative stress post-TBI was supported by the S-100/ICaBP-type calcium-binding domain. UCH-L1’s dualistic impact on TBI was further clarified by the Peptidase_C12 motif. This approach deepens our comprehension of these biomarkers and paves the way for targeted diagnostics in TBI.
Traumatic brain injury (TBI) is a significant medical crisis with no FDA-approved therapies to improve functional outcomes. Key biomarkers, such as glial fibrillary acidic protein (GFAP), S-100 calcium-binding protein B (S-100B), and ubiquitin C-terminal hydrolase L1 (UCH-L1), are crucial for understanding TBI pathology.
Material and methods:
This study integrates proteomic and bioinformatic approaches to explore established TBI biomarkers’ structural and functional complexities: GFAP, S-100B, and UCH-L1.
Results:
Our comprehensive secondary structure and solvent accessibility assessment, conducted with PredictProtein, confirmed the predominance of alpha-helices in GFAP and S-100B, while UCH-L1 displayed a balanced mix of helices (65.00, 67.39, and 40.81%), beta strands (6.20, 0, and 17.94%), and coils (40.81, 17.94, and 41.26%). AlphaFold and I-TASSER were identified as the best servers for full-length tertiary structure prediction for the three target proteins, based on root-mean-square deviation (RMSD), TM-score, and C-score assessments. Protein motif database scans predicted four, eight, and one protein-binding motifs and two, three, and one post-translational modifications for GFAP, S-100B, and UCH-L1, respectively.
Conclusions:
GFAP’s role in axonal transport and synaptic plasticity was emphasized through motifs such as Filament and DUF1664. S-100B’s association with neuroinflammation and oxidative stress post-TBI was supported by the S-100/ICaBP-type calcium-binding domain. UCH-L1’s dualistic impact on TBI was further clarified by the Peptidase_C12 motif. This approach deepens our comprehension of these biomarkers and paves the way for targeted diagnostics in TBI.
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