Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning

Abstract

The phosphorylation of residue T177 produces a significant effect on the conformational dynamics of CDK6. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) are applied to explore the molecular mechanism of the phosphorylation-mediated effect on the conformational dynamics of CDK6 bound by three inhibitors 6ZV, 6ZZ and 0RS, in which 6ZV and 6ZZ have been used to test clinical performance. The DL finds that the β-sheets, αC helix as well as the T-loop are involved in obvious differences of conformation contacts and suggests that the T-loop plays a key role in the function of CDK6. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of T177 leads to alterations of the T-loop conformation and the results from principal component analysis (PCA) indicate that the phosphorylation affects the fluctuation behavior of the β-sheets and the T-loop in CDK6. Interaction networks of inhibitors with CDK6 were analyzed and the information reveals that 6ZV contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. Our MM-GBSA calculations suggest that the binding ability of 6ZV to CDK6 is stronger than 6ZZ and 0RS. We anticipate that this work could provide useful information for further understanding of CDK6 function and developing new promising inhibitors targeting CDK6.