ABSTRACT
The cell division cycle 25 phosphatases CDC25A, B and C regulate cell cycle transitions by dephosphorylating residues in the conserved glycine-rich loop of CDKs to activate their activity. Here, we present the cryo-EM structure of CDK2-cyclin A in complex with CDC25A at 2.7 Å resolution, providing a detailed structural analysis of the overall complex architecture and key protein-protein interactions that underpin this 86 kDa complex. We further identify a CDC25A C-terminal helix that is critical for complex formation. Sequence conservation analysis suggests CDK1/2-cyclin A, CDK1-cyclin B and CDK2/3-cyclin E are suitable binding partners for CDC25A, whilst CDK4/6-cyclin D complexes appear unlikely substrates. A comparative structural analysis of CDK-containing complexes also confirms the functional importance of the conserved CDK1/2 GDSEID motif. This structure improves our understanding of the roles of CDC25 phosphatases in CDK regulation and may inform the development of CDC25-targeting anticancer strategies.
Subject(s)
Cryoelectron Microscopy , Cyclin A , Cyclin-Dependent Kinase 2 , cdc25 Phosphatases , cdc25 Phosphatases/metabolism , cdc25 Phosphatases/chemistry , cdc25 Phosphatases/ultrastructure , cdc25 Phosphatases/genetics , Cyclin-Dependent Kinase 2/metabolism , Cyclin-Dependent Kinase 2/chemistry , Cyclin-Dependent Kinase 2/ultrastructure , Humans , Cyclin A/metabolism , Cyclin A/chemistry , Protein Binding , Models, Molecular , Amino Acid SequenceABSTRACT
Chromosomes pair and synapse with their homologous partners to segregate correctly at the first meiotic division. Association of telomeres with the LINC (Linker of Nucleoskeleton and Cytoskeleton) complex composed of SUN1 and KASH5 enables telomere-led chromosome movements and telomere bouquet formation, facilitating precise pairwise alignment of homologs. Here, we identify a direct interaction between SUN1 and Speedy A (SPDYA) and determine the crystal structure of human SUN1-SPDYA-CDK2 ternary complex. Analysis of meiosis prophase I process in SPDYA-binding-deficient SUN1 mutant mice reveals that the SUN1-SPDYA interaction is required for the telomere-LINC complex connection and the assembly of a ring-shaped telomere supramolecular architecture at the nuclear envelope, which is critical for efficient homologous pairing and synapsis. Overall, our results provide structural insights into meiotic telomere structure that is essential for meiotic prophase I progression.
Subject(s)
Cell Cycle Proteins/metabolism , Meiotic Prophase I , Membrane Proteins/metabolism , Microtubule-Associated Proteins/metabolism , Nuclear Proteins/metabolism , Telomere/metabolism , Animals , Cell Cycle Proteins/genetics , Cell Cycle Proteins/isolation & purification , Cell Cycle Proteins/ultrastructure , Cell Line, Tumor , Crystallography, X-Ray , Cyclin-Dependent Kinase 2/genetics , Cyclin-Dependent Kinase 2/isolation & purification , Cyclin-Dependent Kinase 2/metabolism , Cyclin-Dependent Kinase 2/ultrastructure , Female , HEK293 Cells , Humans , Male , Membrane Proteins/genetics , Membrane Proteins/isolation & purification , Membrane Proteins/ultrastructure , Mice , Mice, Transgenic , Microtubule-Associated Proteins/genetics , Microtubule-Associated Proteins/isolation & purification , Microtubule-Associated Proteins/ultrastructure , Mutation , Nuclear Proteins/genetics , Nuclear Proteins/isolation & purification , Nuclear Proteins/ultrastructure , Recombinant Proteins/genetics , Recombinant Proteins/isolation & purification , Recombinant Proteins/metabolism , Recombinant Proteins/ultrastructureABSTRACT
Benzodipyrazoles have been previously evaluated for their in vitro CDK2 inhibitory activity. In the current investigation, we identified a six-feature common pharmacophore model (AADDRR.33) which is predicted to be responsible for CDK2 inhibition. An efficient 3D QSAR (r(2 )= 0.98 and q(2 )= 0.82) model was also constructed by employing PLS regression analysis. From the molecular docking studies, we examined the binding patterns of compound 7aa with the target protein and also calculated the binding energy using MM-GBSA calculations. Three hydrogen bonds with Lys 33, Glu 81, and Leu 83 are conserved even after 1000 ps run in a molecular dynamics simulation. We identified the slight displacement in bond lengths and the conformational changes occurred during the dynamics. The results also elucidated the protein residue-ligand interaction fractions which clearly explained the involvement of non-H-bond interactions.
Subject(s)
Cyclin-Dependent Kinase 2/antagonists & inhibitors , Cyclin-Dependent Kinase 2/ultrastructure , Molecular Docking Simulation , Molecular Dynamics Simulation , Protein Interaction Mapping/methods , Pyrazoles/chemistry , Binding Sites , Drug Design , Drug Evaluation, Preclinical , Models, Chemical , Protein Binding , Protein Conformation , Quantitative Structure-Activity RelationshipABSTRACT
BACKGROUND: The mechanisms underlying protein function and associated conformational change are dominated by a series of local entropy fluctuations affecting the global structure yet are mediated by only a few key residues. Transitional Dynamic Analysis (TDA) is a new method to detect these changes in local protein flexibility between different conformations arising from, for example, ligand binding. Additionally, Positional Impact Vertex for Entropy Transfer (PIVET) uses TDA to identify important residue contact changes that have a large impact on global fluctuation. We demonstrate the utility of these methods for Cyclin-dependent kinase 2 (CDK2), a system with crystal structures of this protein in multiple functionally relevant conformations and experimental data revealing the importance of local fluctuation changes for protein function. RESULTS: TDA and PIVET successfully identified select residues that are responsible for conformation specific regional fluctuation in the activation cycle of Cyclin Dependent Kinase 2 (CDK2). The detected local changes in protein flexibility have been experimentally confirmed to be essential for the regulation and function of the kinase. The methodologies also highlighted possible errors in previous molecular dynamic simulations that need to be resolved in order to understand this key player in cell cycle regulation. Finally, the use of entropy compensation as a possible allosteric mechanism for protein function is reported for CDK2. CONCLUSION: The methodologies embodied in TDA and PIVET provide a quick approach to identify local fluctuation change important for protein function and residue contacts that contributes to these changes. Further, these approaches can be used to check for possible errors in protein dynamic simulations and have the potential to facilitate a better understanding of the contribution of entropy to protein allostery and function.
Subject(s)
Cyclin-Dependent Kinase 2/chemistry , Cyclin-Dependent Kinase 2/ultrastructure , Models, Chemical , Models, Molecular , Sequence Analysis, Protein/methods , Algorithms , Amino Acid Sequence , Binding Sites , Computer Simulation , Isomerism , Kinetics , Molecular Sequence Data , Protein Binding , Protein Conformation , Structure-Activity Relationship , ThermodynamicsABSTRACT
We report a combined quantum mechanics/molecular mechanics (QM/MM) study to determine the protein-ligand interaction energy between CDK2 (cyclin-dependent kinase 2) and five inhibitors with the N(2)-substituted 6-cyclohexyl-methoxy-purine scaffold. The computational results in this work show that the QM/MM interaction energy is strongly correlated to the biological activity and can be used as a predictor, at least within a family of substrates. A detailed analysis of the protein-ligand structures obtained from molecular dynamics simulations shows specific interactions within the active site that, in some cases, have not been reported before to our knowledge. The computed interaction energy gauges the strength of protein-ligand interactions. Finally, energy decomposition and multiple regression analyses were performed to check the contribution of the electrostatic and van der Waals energies to the total interaction energy and to show the capabilities of the computational model to identify new potent inhibitors.