Allosteric regulation in proteins through residue-residue contact networks

Date

2023-7-28

Author

Çağlayan, Melike

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Proteins play a central role in many biological processes and their function is regulated by various mechanisms including allosteric regulation. Allostery refers to the regulation of protein activity by molecules or ions binding at sites other than the active site. Despite the importance of allostery, understanding the mechanisms of allosteric regulation and identifying allosteric pathways in protein structures has been a challenging task due to the complexity and diversity of protein structures. In this research, we proposed a novel structure-based network approach for examining allosteric protein regions. We represented each protein and protein complex structure as a residue-residue interaction network and used this representation to identify allosteric pathways connecting two distant sites. To validate our method, we applied it to a dataset of 14 proteins of known structure that are regulated allosterically and used statistical metrics to assess the accuracy of the results. Our analysis showed that the residues obtained by our method and their effect on the allosteric pathway were highly accurate. The approach outperformed existing algorithms, with the Steiner-PageRank (S-PR) algorithm showing particularly high true positive rates. The analysis extends to solvent-accessible surface area (SASA) and propensity score evaluation, providing insights into protein core distribution and functional implications for 384 protein structures in 21 different protein categories. This study presents an innovative approach to allosteric pathway deciphering that is poised to reshape protein research, drug discovery, and precision medicine. The novel study techniques and insights enhance protein behavior understanding and pave the way for transformative advances in various fields.

Subject Keywords

Allostery, Protein interaction, Residue-residue contact network, Allosteric paths

URI

https://hdl.handle.net/11511/105163

Collections

Graduate School of Informatics, Thesis