Theoretical Studies on the Selectivity Mechanisms of Glycogen Synthase Kinase 3β (GSK3β) with Pyrazine ATP-competitive Inhibitors by 3DQSAR, Molecular Docking, Molecular Dynamics Simulation and Free Energy Calculations

Author(s): Jingyu Zhu*, Yuanqing Wu, Lei Xu, Jian Jin*

Journal Name: Current Computer-Aided Drug Design

Volume 16 , Issue 1 , 2020

Become EABM
Become Reviewer

Graphical Abstract:


Abstract:

Background: Glycogen synthase kinase-3 (GSK3) is associated with various key biological processes and has been considered as an important therapeutic target for the treatment of many diseases. Great efforts have been made on the development of GSK3 inhibitors, especially ATP-competitive GSK3β inhibitor, but it is still a great challenge to develop selective GSK3β inhibitors because of the high sequence homology with other kinases.

Objective: In order to reveal the selectivity mechanisms of GSK3β inhibition at the molecular level, a series of ATP-competitive GSK3β inhibitor was analyzed by a systematic computational method, combining 3DQSAR, molecular docking, molecular dynamic simulations and free energy calculations.

Methods: Firstly, 3D-QSAR with CoMFA was built to explore the general structure activity relationships. Secondly, CDOCKER and Flexible docking were employed to predicted the reasonable docking poses of all studied inhibitors. And then, both GSK3β and CDK2 complexes were selected to conduct molecular dynamics simulations. Finally, the free energy calculations were employed to find the key selective-residues.

Results: CoMFA model suggested the steric, hydrophobic fields play key roles in the bioactivities of inhibitors, and the binding mechanisms were well analyzed through molecular docking. The binding free energies predicted are in good agreement with the experimental bioactivities and the free energy calculations showed that the binding of GSK3β/inhibitors was mainly contributed from hydrogen bonding and hydrophobic interaction.

Conclusion: Some key residues for selective binding were highlighted, which may afford important guidance for the rational design of novel ATP-competitive GSK3β inhibitors.

Keywords: GSK3β ATP-competitive inhibitors, selective inhibitors, 3D-QSAR CoMFA, molecular docking, molecular dynamics simulation, free energy calculation.

[1]
Hu, X.L.; Guo, C.; Hou, J.Q.; Feng, J.H.; Zhang, X.Q.; Xiong, F.; Ye, W.C.; Wang, H. Stereoisomers of Schisandrin B are potent ATP competitive GSK-3beta inhibitors with neuroprotective effects against Alzheimer’s disease: Stereochemistry and biological activity. ACS Chem. Neurosci., 2019, 10(2), 996-1007.
[http://dx.doi.org/10.1021/acschemneuro.8b00252] [PMID: 29944335]
[2]
Frame, S.; Cohen, P. GSK3 takes centre stage more than 20 years after its discovery. Biochem. J., 2001, 359(Pt 1), 1-16.
[http://dx.doi.org/10.1042/bj3590001] [PMID: 11563964]
[3]
Pandey, M.K.; DeGrado, T.R. Glycogen synthase kinase-3 (GSK-3)-targeted therapy and imaging. Theranostics, 2016, 6(4), 571-593.
[http://dx.doi.org/10.7150/thno.14334] [PMID: 26941849]
[4]
Cohen, P.; Frame, S. The renaissance of GSK3. Nat. Rev. Mol. Cell Biol., 2001, 2(10), 769-776.
[http://dx.doi.org/10.1038/35096075] [PMID: 11584304]
[5]
Diehl, J.A.; Cheng, M.; Roussel, M.F.; Sherr, C.J. Glycogen synthase kinase-3beta regulates cyclin D1 proteolysis and subcellular localization. Genes Dev., 1998, 12(22), 3499-3511.
[http://dx.doi.org/10.1101/gad.12.22.3499] [PMID: 9832503]
[6]
Zhang, M.; Zhang, P.; Liu, Y.; Zhou, Y. GSK3 inhibitor AR-A014418 promotes osteogenic differentiation of human adipose-derived stem cells via ERK and mTORC2/Akt signaling pathway. Biochem. Biophys. Res. Commun., 2017, 490(2), 182-188.
[http://dx.doi.org/10.1016/j.bbrc.2017.06.018] [PMID: 28602697]
[7]
Maqbool, M.; Hoda, N. GSK3 inhibitors in the therapeutic development of diabetes, cancer and neurodegeneration: Past, present and future. Curr. Pharm. Des., 2017, 23(29), 4332-4350.
[http://dx.doi.org/10.2174/1381612823666170714141450] [PMID: 28714403]
[8]
Abdul, A.U.R.M.; De Silva, B.; Gary, R.K. The GSK3 kinase inhibitor lithium produces unexpected hyperphosphorylation of β-catenin, a GSK3 substrate, in human glioblastoma cells. Biol. Open, 2018, 7(1)bio030874
[http://dx.doi.org/10.1242/bio.030874] [PMID: 29212798]
[9]
Cohen, P.; Goedert, M. GSK3 inhibitors: Development and therapeutic potential. Nat. Rev. Drug Discov., 2004, 3(6), 479-487.
[http://dx.doi.org/10.1038/nrd1415] [PMID: 15173837]
[10]
Penas, C.; Mishra, J.K.; Wood, S.D.; Schürer, S.C.; Roush, W.R.; Ayad, N.G. GSK3 inhibitors stabilize Wee1 and reduce cerebellar granule cell progenitor proliferation. Cell Cycle, 2015, 14(3), 417-424.
[http://dx.doi.org/10.4161/15384101.2014.974439] [PMID: 25616418]
[11]
Force, T.; Woodgett, J.R. Unique and overlapping functions of GSK-3 isoforms in cell differentiation and proliferation and cardiovascular development. J. Biol. Chem., 2009, 284(15), 9643-9647.
[http://dx.doi.org/10.1074/jbc.R800077200] [PMID: 19064989]
[12]
Dey, A.; Hao, S.; Wosiski-Kuhn, M.; Stranahan, A.M. Glucocorticoid-mediated activation of GSK3β promotes tau phosphorylation and impairs memory in type 2 diabetes. Neurobiol. Aging, 2017, 57, 75-83.
[http://dx.doi.org/10.1016/j.neurobiolaging.2017.05.010] [PMID: 28609678]
[13]
Swinney, Z.T.; Haubrich, B.A.; Xia, S.; Ramesha, C.; Gomez, S.R.; Guyett, P.; Mensa-Wilmot, K.; Swinney, D.C. A four-point screening method for assessing molecular mechanism of action (MMOA) identifies tideglusib as a time-dependent inhibitor of trypanosoma brucei GSK3beta. PLoS Negl. Trop. Dis., 2016, 10(3) e0004506
[http://dx.doi.org/10.1371/journal.pntd.0004506] [PMID: 26942720]
[14]
Saura, C.; Roda, D.; Roselló, S.; Oliveira, M.; Macarulla, T.; Pérez-Fidalgo, J.A.; Morales-Barrera, R.; Sanchis-García, J.M.; Musib, L.; Budha, N.; Zhu, J.; Nannini, M.; Chan, W.Y.; Sanabria Bohórquez, S.M.; Meng, R.D.; Lin, K.; Yan, Y.; Patel, P.; Baselga, J.; Tabernero, J.; Cervantes, A. A first-in-human phase I study of the ATP-competitive AKT inhibitor ipatasertib demonstrates robust and safe targeting of AKT in patients with solid tumors. Cancer Discov., 2017, 7(1), 102-113.
[http://dx.doi.org/10.1158/2159-8290.CD-16-0512] [PMID: 27872130]
[15]
Wagman, A.S.; Johnson, K.W.; Bussiere, D.E. Discovery and development of GSK3 inhibitors for the treatment of type 2 diabetes. Curr. Pharm. Des., 2004, 10(10), 1105-1137.
[http://dx.doi.org/10.2174/1381612043452668] [PMID: 15078145]
[16]
Martinez, A.; Castro, A.; Dorronsoro, I.; Alonso, M. Glycogen synthase kinase 3 (GSK-3) inhibitors as new promising drugs for diabetes, neurodegeneration, cancer, and inflammation. Med. Res. Rev., 2002, 22(4), 373-384.
[http://dx.doi.org/10.1002/med.10011] [PMID: 12111750]
[17]
Zhao, S.; Zhu, J.; Xu, L.; Jin, J. Theoretical studies on the selective mechanisms of GSK3β and CDK2 by molecular dynamics simulations and free energy calculations. Chem. Biol. Drug Des., 2017, 89(6), 846-855.
[http://dx.doi.org/10.1111/cbdd.12907] [PMID: 27863047]
[18]
Arfeen, M.; Bharatam, P.V. Design of glycogen synthase kinase-3 inhibitors: An overview on recent advancements. Curr. Pharm. Des., 2013, 19(26), 4755-4775.
[http://dx.doi.org/10.2174/1381612811319260007] [PMID: 23260024]
[19]
García, I.; Fall, Y.; Gómez, G. QSAR, docking, and CoMFA studies of GSK3 inhibitors. Curr. Pharm. Des., 2010, 16(24), 2666-2675.
[http://dx.doi.org/10.2174/138161210792389225] [PMID: 20642432]
[20]
Patil, R.; Sawant, S. Molecular dynamics guided receptor independent 4D QSAR studies of substituted coumarins as anticancer agents. Curr Comput Aided Drug Des, 2015, 11(1), 39-50.
[http://dx.doi.org/10.2174/1573409911666150617113933] [PMID: 26081557]
[21]
Yang, Y.; Qin, J.; Liu, H.; Yao, X. Molecular dynamics simulation, free energy calculation and structure-based 3D-QSAR studies of B-RAF kinase inhibitors. J. Chem. Inf. Model., 2011, 51(3), 680-692.
[http://dx.doi.org/10.1021/ci100427j] [PMID: 21338122]
[22]
Yu, H.; Fang, Y.; Lu, X.; Liu, Y.; Zhang, H. Combined 3D-QSAR, molecular docking, molecular dynamics simulation, and binding free energy calculation studies on the 5-hydroxy-2H-pyridazin-3-one derivatives as HCV NS5B polymerase inhibitors. Chem. Biol. Drug Des., 2014, 83(1), 89-105.
[http://dx.doi.org/10.1111/cbdd.12203] [PMID: 23941500]
[23]
Balasubramanian, P.K.; Balupuri, A.; Kang, H.Y.; Cho, S.J. Receptor-guided 3D-QSAR studies, molecular dynamics simulation and free energy calculations of Btk kinase inhibitors. BMC Syst. Biol., 2017, 11(Suppl. 2), 6.
[http://dx.doi.org/10.1186/s12918-017-0385-5] [PMID: 28361711]
[24]
Chaudhari, H.K.; Pahelkar, A.R. 3D QSAR, docking, molecular dynamics simulations and MM-GBSA studies of extended side chain of the antitubercular drug (6S) 2-Nitro-6-[4- (trifluoromethoxy) benzyl] oxy-6,7-dihydro-5H-imidazo[2,1-b] [1,3] oxazine. Infect. Dis. Drug Tar., 2018.
[25]
Fu, G.; Liu, S.; Nan, X.; Dale, O.R.; Zhao, Z.; Chen, Y.; Wilkins, D.E.; Manly, S.P.; Cutler, S.J.; Doerksen, R.J. Quantitative structure-activity relationship analysis and a combined ligand-based/structure-based virtual screening study for Glycogen Synthase Kinase-3. Mol. Inform., 2014, 33(9), 627-640.
[http://dx.doi.org/10.1002/minf.201400045] [PMID: 27486081]
[26]
Akhtar, M.; Bharatam, P.V. 3D-QSAR and molecular docking studies on 3-anilino-4-arylmaleimide derivatives as glycogen synthase kinase-3β inhibitors. Chem. Biol. Drug Des., 2012, 79(4), 560-571.
[http://dx.doi.org/10.1111/j.1747-0285.2011.01291.x] [PMID: 22168279]
[27]
Quesada-Romero, L.; Caballero, J. Docking and quantitative structure-activity relationship of oxadiazole derivates as inhibitors of GSK3β. Mol. Divers., 2014, 18(1), 149-159.
[http://dx.doi.org/10.1007/s11030-013-9483-5] [PMID: 24081608]
[28]
Berg, S.; Bergh, M.; Hellberg, S.; Högdin, K.; Lo-Alfredsson, Y.; Söderman, P.; von Berg, S.; Weigelt, T.; Ormö, M.; Xue, Y.; Tucker, J.; Neelissen, J.; Jerning, E.; Nilsson, Y.; Bhat, R. Discovery of novel potent and highly selective glycogen synthase kinase-3β (GSK3β) inhibitors for Alzheimer’s disease: design, synthesis, and characterization of pyrazines. J. Med. Chem., 2012, 55(21), 9107-9119.
[http://dx.doi.org/10.1021/jm201724m] [PMID: 22489897]
[29]
Case, D.A.; Cheatham, T.E., III; Darden, T.; Gohlke, H.; Luo, R.; Merz, K.M., Jr; Onufriev, A.; Simmerling, C.; Wang, B.; Woods, R.J. The Amber biomolecular simulation programs. J. Comput. Chem., 2005, 26(16), 1668-1688.
[http://dx.doi.org/10.1002/jcc.20290] [PMID: 16200636]
[30]
Wang, J.; Wolf, R.M.; Caldwell, J.W.; Kollman, P.A.; Case, D.A. Development and testing of a general amber force field. J. Comput. Chem., 2004, 25(9), 1157-1174.
[http://dx.doi.org/10.1002/jcc.20035] [PMID: 15116359]
[31]
Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M.C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; Caldwell, J.; Wang, J.; Kollman, P. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem., 2003, 24(16), 1999-2012.
[http://dx.doi.org/10.1002/jcc.10349] [PMID: 14531054]
[32]
Pedersen, M.; Klarlund, M.; Jacobsen, S.; Svendsen, A.J.; Frisch, M. Validity of rheumatoid arthritis diagnoses in the Danish National Patient Registry. Eur. J. Epidemiol., 2004, 19(12), 1097-1103.
[http://dx.doi.org/10.1007/s10654-004-1025-0] [PMID: 15678789]
[33]
Pan, P.; Yu, H.; Liu, Q.; Kong, X.; Chen, H.; Chen, J.; Liu, Q.; Li, D.; Kang, Y.; Sun, H.; Zhou, W.; Tian, S.; Cui, S.; Zhu, F.; Li, Y.; Huang, Y.; Hou, T. Combating drug-resistant mutants of anaplastic lymphoma kinase with potent and selective type-I(1/2) inhibitors by stabilizing unique DFG-shifted loop conformation. ACS Cent. Sci., 2017, 3(11), 1208-1220.
[http://dx.doi.org/10.1021/acscentsci.7b00419] [PMID: 29202023]
[34]
Sun, H.; Duan, L.; Chen, F.; Liu, H.; Wang, Z.; Pan, P.; Zhu, F.; Zhang, J.Z.H.; Hou, T. Assessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approaches. Phys. Chem. Chem. Phys., 2018, 20(21), 14450-14460.
[http://dx.doi.org/10.1039/C7CP07623A] [PMID: 29785435]
[35]
Zhu, J.; Li, K.; Xu, L.; Jin, J. Insight into the selective mechanism of phosphoinositide 3-kinase gamma with benzothiazole and thiazolopiperidine gamma-specific inhibitors by in silico approaches. Chem. Biol. Drug Des., 2018.
[PMID: 30582283]
[36]
Hou, T.; Wang, J.; Li, Y.; Wang, W. Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. J. Chem. Inf. Model., 2011, 51(1), 69-82.
[http://dx.doi.org/10.1021/ci100275a] [PMID: 21117705]
[37]
Gohlke, H.; Kiel, C.; Case, D.A. Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes. J. Mol. Biol., 2003, 330(4), 891-913.
[http://dx.doi.org/10.1016/S0022-2836(03)00610-7] [PMID: 12850155]
[38]
Hou, T.; Li, Y.; Wang, W. Prediction of peptides binding to the PKA RIIalpha subunit using a hierarchical strategy. Bioinformatics, 2011, 27(13), 1814-1821.
[http://dx.doi.org/10.1093/bioinformatics/btr294] [PMID: 21586518]
[39]
Sun, H.; Li, Y.; Shen, M.; Tian, S.; Xu, L.; Pan, P.; Guan, Y.; Hou, T. Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring. Phys. Chem. Chem. Phys., 2014, 16(40), 22035-22045.
[http://dx.doi.org/10.1039/C4CP03179B] [PMID: 25205360]
[40]
Chen, F.; Sun, H.; Wang, J.; Zhu, F.; Liu, H.; Wang, Z.; Lei, T.; Li, Y.; Hou, T. Assessing the performance of MM/PBSA and MM/GBSA methods. Predicting binding free energies and poses of protein-RNA complexes. RNA, 2018, 24(9), 1183-1194.
[http://dx.doi.org/10.1261/rna.065896.118] [PMID: 29930024]
[41]
Zhang, C.; Hou, T.; Feng, Z.; Li, Y. Structure-based development of antagonists for chemokine receptor CXCR4. Curr Comput Aided Drug Des, 2013, 9(1), 60-75.
[http://dx.doi.org/10.2174/1573409911309010006] [PMID: 22734712]
[42]
Xu, L.; Kong, R.; Zhu, J.; Sun, H.; Chang, S. Unraveling the conformational determinants of LARP7 and 7SK small nuclear RNA by theoretical approaches. Mol. Biosyst., 2016, 12(8), 2613-2621.
[http://dx.doi.org/10.1039/C6MB00252H] [PMID: 27301448]
[43]
Liu, N.; Zhou, W.; Guo, Y.; Wang, J.; Fu, W.; Sun, H.; Li, D.; Duan, M.; Hou, T. Molecular dynamics simulations revealed the regulation of ligands to the interactions between androgen receptor and its coactivator. J. Chem. Inf. Model., 2018, 58(8), 1652-1661.
[http://dx.doi.org/10.1021/acs.jcim.8b00283] [PMID: 29993249]
[44]
Shen, M.; Zhou, S.; Li, Y.; Li, D.; Hou, T. Theoretical study on the interaction of pyrrolopyrimidine derivatives as LIMK2 inhibitors: Insight into structure-based inhibitor design. Mol. Biosyst., 2013, 9(10), 2435-2446.
[http://dx.doi.org/10.1039/c3mb70168a] [PMID: 23881296]
[45]
Shen, M.; Zhou, S.; Li, Y.; Pan, P.; Zhang, L.; Hou, T. Discovery and optimization of triazine derivatives as ROCK1 inhibitors: Molecular docking, molecular dynamics simulations and free energy calculations. Mol. Biosyst., 2013, 9(3), 361-374.
[http://dx.doi.org/10.1039/c2mb25408e] [PMID: 23340525]
[46]
Zhu, J.; Li, Y.; Yu, H.; Zhang, L.; Mao, X.; Hou, T. Insight into the structural requirements of narlaprevir-type inhibitors of NS3/NS4A protease based on HQSAR and molecular field analyses. Comb. Chem. High Throughput Screen., 2012, 15(6), 439-450.
[http://dx.doi.org/10.2174/138620712800563918] [PMID: 22263860]
[47]
Zhu, J.; Pan, P.; Li, Y.; Wang, M.; Li, D.; Cao, B.; Mao, X.; Hou, T. Theoretical studies on beta and delta isoform-specific binding mechanisms of phosphoinositide 3-kinase inhibitors. Mol. Biosyst., 2014, 10(3), 454-466.
[http://dx.doi.org/10.1039/C3MB70314B] [PMID: 24336903]
[48]
Tian, S.; Sun, H.; Pan, P.; Li, D.; Zhen, X.; Li, Y.; Hou, T. Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility. J. Chem. Inf. Model., 2014, 54(10), 2664-2679.
[http://dx.doi.org/10.1021/ci500414b] [PMID: 25233367]
[49]
Tian, S.; Sun, H.; Li, Y.; Pan, P.; Li, D.; Hou, T. Development and evaluation of an integrated virtual screening strategy by combining molecular docking and pharmacophore searching based on multiple protein structures. J. Chem. Inf. Model., 2013, 53(10), 2743-2756.
[http://dx.doi.org/10.1021/ci400382r] [PMID: 24010823]
[50]
AbdulHameed. M.D.; Hamza, A.; Liu, J.; Zhan, C.G. Combined 3D-QSAR modeling and molecular docking study on indolinone derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1. J. Chem. Inf. Model., 2008, 48(9), 1760-1772.
[http://dx.doi.org/10.1021/ci800147v] [PMID: 18717540]


Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 16
ISSUE: 1
Year: 2020
Page: [17 - 30]
Pages: 14
DOI: 10.2174/1573409915666190708102459
Price: $65

Article Metrics

PDF: 32
HTML: 6
EPUB: 1