Rabipour, Mina
ORCID: 0000-0003-3319-5302, Hassenrück, Floyd
ORCID: 0000-0003-4772-5220, Pallaske, Elena, Röhrig, Fernanda
ORCID: 0009-0006-8850-487X, Hallek, Michael
ORCID: 0000-0002-7425-4455, Alvarez-Idaboy, Juan Raul
ORCID: 0000-0002-2901-5412, Kramer, Oliver
ORCID: 0000-0001-7607-1700 and Rebollido-Rios, Rocio
ORCID: 0000-0002-8910-867X
(2025).
Allosteric Coupling in Full-Length Lyn Kinase Revealed by Molecular Dynamics and Network Analysis.
International Journal of Molecular Sciences, 26 (12).
MDPI.
ISSN 1422-0067
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ijms-26-05835.pdf Bereitstellung unter der CC-Lizenz: Creative Commons Attribution. Download (8MB) |
Abstract
[Artikel-Nr.: 5835] Lyn is a multifunctional Src-family kinase (SFK) that regulates immune signaling and has been implicated in diverse types of cancer. Unlike other SFKs, its full-length structure and regulatory dynamics remain poorly characterized. In this study, we present the first long-timescale molecular dynamics analysis of full-length Lyn, including the SH3, SH2, and SH1 domains, across wildtype, ligand-bound, and cancer-associated mutant states. Using principal component analysis, dynamic cross-correlation matrices, and network-based methods, we show that ATP binding stabilizes the kinase core and promotes interdomain coordination, while the ATP-competitive inhibitor dasatinib and specific mutations (e.g., E290K, I364N) induce conformational decoupling and weaken long-range communication. We identify integration modules and develop an interface-weighted scoring scheme to rank dynamically central residues. This analysis reveals 44 allosteric hubs spanning SH3, SH2, SH1, and interdomain regions. Finally, a random forest classifier trained on 16 MD-derived features highlights key interdomain descriptors, distinguishing functional states with an AUC of 0.98. Our results offer a dynamic and network-level framework for understanding Lyn regulation and identify potential regulatory hotspots for structure-based drug design. More broadly, our approach demonstrates the value of integrating full-length MD simulations with network and machine learning techniques to probe allosteric control in multidomain kinases.
| Item Type: | Article |
| Creators: | Creators Email ORCID ORCID Put Code Pallaske, Elena UNSPECIFIED UNSPECIFIED UNSPECIFIED |
| URN: | urn:nbn:de:hbz:38-800046 |
| Identification Number: | 10.3390/ijms26125835 |
| Journal or Publication Title: | International Journal of Molecular Sciences |
| Volume: | 26 |
| Number: | 12 |
| Number of Pages: | 23 |
| Date: | 18 June 2025 |
| Publisher: | MDPI |
| ISSN: | 1422-0067 |
| Language: | English |
| Faculty: | Central Institutions / Interdisciplinary Research Centers Faculty of Medicine |
| Divisions: | CECAD - Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases Faculty of Medicine > Innere Medizin > Klinik I für Innere Medizin - Hämatologie und Onkologie Zentrum für Molekulare Medizin |
| Subjects: | Medical sciences Medicine |
| Uncontrolled Keywords: | Keywords Language Lyn kinase ; allosteric regulation ; molecular dynamics simulations ; cancer-associated mutations ; machine learning ; dynamic cross-correlation matrix ; correlation network analysis ; multidomain kinases ; Src-family kinases English |
| ['eprint_fieldname_oa_funders' not defined]: | Publikationsfonds UzK |
| Refereed: | Yes |
| URI: | http://kups.ub.uni-koeln.de/id/eprint/80004 |
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https://orcid.org/0000-0003-3319-5302