2026/07/01 by Yanchen Zhu, Matteo T. Degiacomi, Antonia S. J. S. Mey +1 · 1 voice
Biochemistry, Genetics and Molecular Biology · Computer Science · #Computational Drug Discovery Methods #Conformational change #Conformational ensembles #Gene Regulatory Network Analysis #Kinase #Mechanism (biology) #Molecular dynamics #Phosphorylation #Protein Structure and Dynamics #Protein structure #Receptor tyrosine kinase #Tyrosine kinase
paper · doi:10.64898/2026.06.26.734786
published in bioRxiv (Cold Spring Harbor Laboratory) (Cold Spring Harbor Laboratory)
openalex publication_date 2026/07/01 · openalex created_date 2026/07/02 · openalex updated_date 2026/07/29
Protein kinase activation is driven by conformational changes across multiple structural components, including the conserved Asp-Phe-Gly (DFG) motif, but whether these transitions follow a universal mechanism remains unclear. Here we combine over 8.3 milliseconds of distributed unbiased molecular dynamics simulations with Markov state models (MSMs) to compare the conformational landscapes of the ABL1, EGFR and MET kinase domains. To maximize unbiased sampling of functionally relevant conformational space, we use a transfer seeding strategy that steers AlphaFold2 models derived from homologous templates to sample MET conformational states absent from available experimental databases. We find that related DFG-motif geometries separate into distinct kinetic networks. These shared structural states are connected by kinase-specific activation pathways with different regulatory elements controlling the slowest step of activation. Our findings reveal that the shared nomenclature masks distinct transition mechanisms between kinase domains, revealing new regions critical for activity and targetable conformations for inhibitor design.