6hk7
Crystal structure of GSK-3B in complex with pyrazine inhibitor C50
Structural highlights
Function[GSK3B_HUMAN] Constitutively active protein kinase that acts as a negative regulator in the hormonal control of glucose homeostasis, Wnt signaling and regulation of transcription factors and microtubules, by phosphorylating and inactivating glycogen synthase (GYS1 or GYS2), EIF2B, CTNNB1/beta-catenin, APC, AXIN1, DPYSL2/CRMP2, JUN, NFATC1/NFATC, MAPT/TAU and MACF1. Requires primed phosphorylation of the majority of its substrates. In skeletal muscle, contributes to insulin regulation of glycogen synthesis by phosphorylating and inhibiting GYS1 activity and hence glycogen synthesis. May also mediate the development of insulin resistance by regulating activation of transcription factors. Regulates protein synthesis by controlling the activity of initiation factor 2B (EIF2BE/EIF2B5) in the same manner as glycogen synthase. In Wnt signaling, GSK3B forms a multimeric complex with APC, AXIN1 and CTNNB1/beta-catenin and phosphorylates the N-terminus of CTNNB1 leading to its degradation mediated by ubiquitin/proteasomes. Phosphorylates JUN at sites proximal to its DNA-binding domain, thereby reducing its affinity for DNA. Phosphorylates NFATC1/NFATC on conserved serine residues promoting NFATC1/NFATC nuclear export, shutting off NFATC1/NFATC gene regulation, and thereby opposing the action of calcineurin. Phosphorylates MAPT/TAU on 'Thr-548', decreasing significantly MAPT/TAU ability to bind and stabilize microtubules. MAPT/TAU is the principal component of neurofibrillary tangles in Alzheimer disease. Plays an important role in ERBB2-dependent stabilization of microtubules at the cell cortex. Phosphorylates MACF1, inhibiting its binding to microtubules which is critical for its role in bulge stem cell migration and skin wound repair. Probably regulates NF-kappa-B (NFKB1) at the transcriptional level and is required for the NF-kappa-B-mediated anti-apoptotic response to TNF-alpha (TNF/TNFA). Negatively regulates replication in pancreatic beta-cells, resulting in apoptosis, loss of beta-cells and diabetes. Phosphorylates MUC1 in breast cancer cells, decreasing the interaction of MUC1 with CTNNB1/beta-catenin. Is necessary for the establishment of neuronal polarity and axon outgrowth. Phosphorylates MARK2, leading to inhibit its activity. Phosphorylates SIK1 at 'Thr-182', leading to sustain its activity. Phosphorylates ZC3HAV1 which enhances its antiviral activity. Phosphorylates SFPQ at 'Thr-687' upon T-cell activation.[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] Publication Abstract from PubMedIt is widely accepted that drug-target association and dissociation rates directly affect drug efficacy and safety. To rationally optimize drug binding kinetics, one must know the atomic arrangement of the protein-ligand complex during the binding/unbinding process in order to detect stable and metastable states. Whereas experimental approaches can determine kinetic constants with fairly good accuracy, computational approaches based on molecular dynamics (MD) simulations can deliver the atomistic details of the unbinding process. Furthermore, they can also be utilized prospectively to predict residence time (i.e., the inverse of unbinding kinetics constant, koff) with an acceptable level of accuracy. Here, we report a novel method based on adiabatic bias MD with an electrostatics-like collective variable (dubbed elABMD) for sampling protein-ligand dissociation events in two kinases. elABMD correctly ranked a ligand series on glucokinase, in agreement with experimental data and previous calculations. Subsequently, we applied the new method prospectively to a congeneric series of GSK-3beta inhibitors. For this series, new crystal structures were generated and the residence time was experimentally measured with surface plasmon resonance (SPR). There was good agreement between computational predictions and experimental measures, suggesting that elABMD is an innovative and efficient tool for calculating residence times. Investigating Drug-Target Residence Time in Kinases through Enhanced Sampling Simulations.,Gobbo D, Piretti V, Di Martino RMC, Tripathi SK, Giabbai B, Storici P, Demitri N, Girotto S, Decherchi S, Cavalli A J Chem Theory Comput. 2019 Jul 12. doi: 10.1021/acs.jctc.9b00104. PMID:31246463[13] From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine. References
| ||||||||||||||||||||||
