همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

Targeting Protein in Neurodegenerative Diseases: A Computational Approach

نویسندگان :

Reyhaneh Ebrahimi¹ Seyed Hassan Alavi² Fayaz Soleymani³ Fatemeh Zare-Mirakabad⁴

1- Computational Biology Research Canter (CBRC), Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran , Iran 2- Computational Biology Research Canter (CBRC), Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran , Iran 3- Department of Biochemistry & Biology University of Potsdam 4- – Computational Biology Research Canter (CBRC) , Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran

کلمات کلیدی :

Neurodegenerative diseases،PPI،Graph Attention Networks،Drug target discovery

چکیده :

Neurodegenerative diseases, including Alzheimer’s, Parkinson’s, Huntington’s, and amyotrophic lateral sclerosis (ALS), pose significant challenges to global healthcare due to their complexity and severe impact on patients. A shared pathogenic feature of these diseases is protein misfolding and aggregation, which leads to neuronal death. Traditional experimental methods for identifying disease-associated proteins are limited by the nervous system’s complexity and the difficulty of obtaining biological samples. This study introduces a novel computational model, ITPND, which combines features of single proteins with protein-protein interaction (PPI) networks to identify proteins linked to neurodegenerative diseases. By leveraging Graph Attention Networks (GAT) and the ProtBERT model, our approach effectively classifies proteins by extracting significant features from sequences and PPI graphs. The model outperforms existing methods, achieving an accuracy of 80%, a precision of 85%, and a recall of 90%. Biological validation through pathway enrichment analysis confirms the involvement of predicted proteins in critical neurodegenerative pathways. Furthermore, drug-protein interaction analysis reveals potential therapeutic candidates, underscoring the model’s utility in drug target discovery. This approach provides new insights into the molecular mechanisms of neurodegenerative diseases and potential therapeutic interventions.