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Molecular Dynamics Study of Conformational Changes of Tankyrase 2 Binding Subsites upon Ligand Binding
Abstract
The interactions between proteins and ligands are involved in various biological functions. While experimental structures provide key static structural information of ligand-unbound and ligand-bound proteins, dynamic information is often insufficient for understanding the detailed mechanism of protein–ligand binding. Here, we studied the conformational changes of the tankyrase 2 binding pocket upon ligand binding using molecular dynamics simulations of the ligand-unbound and ligand-bound proteins. The ligand-binding pocket has two subsites: the nicotinamide and adenosine subsite. Comparative analysis of these molecular dynamics trajectories revealed that the conformational change of the ligand-binding pocket was characterized by four distinct conformations of the ligand-binding pocket. Two of the four conformations were observed only in molecular dynamics simulations. We found that the pocket conformational change on ligand binding was based on the connection between the nicotinamide and adenosine subsites that are located adjacently in the pocket. From the analysis, we proposed the protein–ligand binding mechanism of tankyrase 2. Finally, we discussed the computational prediction of the ligand binding pose using the tankyrase 2 structures obtained from the molecular dynamics simulations.
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“Furthermore, the analysis of structural dynamics using molecular dynamics simulations provided insights into conformational changes and the stability of protein–ligand complexes [68].”
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Research works printed but not linked: 43
- Hsiao, 2008, Tankyrase function at telomeres, spindle poles, and beyond, Biochimie, 90, 83, 10.1016/j.biochi.2007.07.012 · DOI
- Narwal, 2013, Screening and structural analysis of flavones inhibiting tankyrases, J. Med. Chem., 56, 3507, 10.1021/jm3018783 · DOI
- Huang, 2009, Tankyrase inhibition stabilizes axin and antagonizes Wnt signalling, Nature, 461, 614, 10.1038/nature08356 · DOI
- Narwal, 2012, Structural basis of selective inhibition of human tankyrases, J. Med. Chem., 55, 1360, 10.1021/jm201510p · DOI
- Narwal, 2013, Discovery of tankyrase inhibiting flavones with increased potency and isoenzyme selectivity, J. Med. Chem., 56, 7880, 10.1021/jm401463y · DOI
- Voronkov, 2013, Structural basis and SAR for G007-LK, a lead stage 1,2,4-triazole based specific tankyrase 1/2 inhibitor, J. Med. Chem., 56, 3012, 10.1021/jm4000566 · DOI
- Huang, 2013, Structure-based design of 2-aminopyridine oxazolidinones as potent and selective tankyrase inhibitors, ACS Med. Chem. Lett., 4, 1218, 10.1021/ml4003315 · DOI
- Bregman, 2013, Discovery of novel, induced-pocket binding oxazolidinones as potent, selective, and orally bioavailable tankyrase inhibitors, J. Med. Chem., 56, 4320, 10.1021/jm4000038 · DOI
- Hua, 2013, Development of novel dual binders as potent, selective, and orally bioavailable tankyrase inhibitors, J. Med. Chem., 56, 10003, 10.1021/jm401317z · DOI
- Anumala, 2017, Discovery of a Novel Series of Tankyrase Inhibitors by a Hybridization Approach, J. Med. Chem., 60, 10013, 10.1021/acs.jmedchem.7b00883 · DOI
- Schacke, 2019, PARP-1/2 Inhibitor Olaparib Prevents or Partially Reverts EMT Induced by TGF-beta in NMuMG Cells, Int. J. Mol. Sci., 20, 10.3390/ijms20030518 · DOI
- Chen, 2009, Small molecule-mediated disruption of Wnt-dependent signaling in tissue regeneration and cancer, Nat. Chem. Biol., 5, 100, 10.1038/nchembio.137 · DOI
- Karlberg, 2010, Structural basis for the interaction between tankyrase-2 and a potent Wnt-signaling inhibitor, J. Med. Chem., 53, 5352, 10.1021/jm100249w · DOI
- Ruf, 1998, Inhibitor and NAD+ binding to poly(ADP-ribose) polymerase as derived from crystal structures and homology modeling, Biochemistry, 37, 3893, 10.1021/bi972383s · DOI
- Langelier, 2018, NAD(+) analog reveals PARP-1 substrate-blocking mechanism and allosteric communication from catalytic center to DNA-binding domains, Nat. Commun., 9, 10.1038/s41467-018-03234-8 · DOI
- Lehtiö, 2013, Tankyrases as drug targets, FEBS J., 280, 3576, 10.1111/febs.12320 · DOI
- Haikarainen, 2014, Tankyrases: structure, function and therapeutic implications in cancer, Curr. Pharm. Des., 20, 6472, 10.2174/1381612820666140630101525 · DOI
- Ferri, 2017, Targeting Wnt-driven cancers: Discovery of novel tankyrase inhibitors, Eur. J. Med. Chem., 142, 506, 10.1016/j.ejmech.2017.09.030 · DOI
- Gao, 2017, Are induced fit protein conformational changes caused by ligand-binding predictable? A molecular dynamics investigation, J. Comput. Chem., 38, 1229, 10.1002/jcc.24714 · DOI
- Berman, 2000, The Protein Data Bank and the challenge of structural genomics, Nat. Struct. Biol., 7, 957, 10.1038/80734 · DOI
- Jorgensen, 1983, Morphology of a very extensible insect muscle, Tissue Cell, 15, 639, 10.1016/0040-8166(83)90013-7 · DOI
- Kimura, 2017, Deciphering Cryptic Binding Sites on Proteins by Mixed-Solvent Molecular Dynamics, J. Chem. Inf. Model., 57, 1388, 10.1021/acs.jcim.6b00623 · DOI
- Beglov, 2018, Exploring the structural origins of cryptic sites on proteins, Proc. Natl. Acad. Sci. U.S.A., 115, E3416, 10.1073/pnas.1711490115 · DOI
- An, 2019, Are the Apo Proteins Suitable for the Rational Discovery of Allosteric Drugs?, J. Chem. Inf. Model., 59, 597, 10.1021/acs.jcim.8b00735 · DOI
- Berendsen, 1995, Gromacs - a Message-Passing Parallel Molecular-Dynamics Implementation, Comput. Phys. Commun., 91, 43, 10.1016/0010-4655(95)00042-E · DOI
- Lindahl, 2001, GROMACS 3.0: a package for molecular simulation and trajectory analysis, J. Mol. Model., 7, 306, 10.1007/s008940100045 · DOI
- Van der Spoel, 2005, GROMACS: Fast, flexible, and free, J. Comput. Chem., 26, 1701, 10.1002/jcc.20291 · DOI
- Hess, 2008, GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation, J. Chem. Theory Comput., 4, 435, 10.1021/ct700301q · DOI
- Pronk, 2013, GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit, Bioinformatics, 29, 845, 10.1093/bioinformatics/btt055 · DOI
- Lindorff-Larsen, 2010, Improved side-chain torsion potentials for the Amber ff99SB protein force field, Proteins, 78, 1950, 10.1002/prot.22711 · DOI
- Wang, 2004, Development and testing of a general amber force field, J. Comput. Chem., 25, 1157, 10.1002/jcc.20035 · DOI
- Nosé, 1984, A Molecular-Dynamics Method for Simulations in the Canonical Ensemble, Mol. Phys., 52, 255, 10.1080/00268978400101201 · DOI
- Parrinello, 1981, Polymorphic Transitions in Single-Crystals - a New Molecular-Dynamics Method, J. Appl. Phys., 52, 7182, 10.1063/1.328693 · DOI
- Hess, 1997, LINCS: A linear constraint solver for molecular simulations, J. Comput. Chem., 18, 1463, 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H · DOI
- Essmann, 1995, A Smooth Particle Mesh Ewald Method, J. Chem. Phys., 103, 8577, 10.1063/1.470117 · DOI
- Jones, 1997, Development and validation of a genetic algorithm for flexible docking, J. Mol. Biol., 267, 727, 10.1006/jmbi.1996.0897 · DOI · Paper page
- Verdonk, 2003, Improved protein-ligand docking using GOLD, Proteins, 52, 609, 10.1002/prot.10465 · DOI
- Srinivasan, 1998, Continuum Solvent Studies of the Stability of DNA, RNA, and Phosphoramidate–DNA Helices, J. Am. Chem. Soc., 120, 9401, 10.1021/ja981844+ · DOI
- Kollman, 2000, Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models, Acc. Chem. Res., 33, 889, 10.1021/ar000033j · DOI · Paper page
- Kuhn, 2005, Validation and use of the MM-PBSA approach for drug discovery, J. Med. Chem., 48, 4040, 10.1021/jm049081q · DOI
- Okimoto, 2009, High-performance drug discovery: computational screening by combining docking and molecular dynamics simulations, PLoS Comput. Biol., 5, 10.1371/journal.pcbi.1000528 · DOI
- Okimoto, 2018, Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors, ACS Omega, 3, 4475, 10.1021/acsomega.8b00175 · DOI
- Connolly, 1983, Analytical molecular surface calculation, J. Appl. Crystallogr., 16, 548, 10.1107/S0021889883010985 · DOI
Cited by
Hadi, N., Drioiche, A., Bouchra, E. M., Baammi, S., Abdelaziz Shahat, A., Tagnaout, I., Radi, M., Remok, F., Bouzoubaa, A., & Zair, T. (2024) · Pharmaceuticals · doi:10.3390/ph17070862 · Cited by 30
Metadata
- Authors
- Hirano, Y., Okimoto, N., Fujita, S., & Taiji, M.
- Affiliations
- RIKEN Center for Biosystems Dynamics Research (BDR) , , 6-2-4 Furuedai , , ,
- Venue
- ACS Omega
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-06-29
- Volume
- 6
- Issue
- 27
- Pages
- 17609-17620
- ISSN
- 2470-1343
- PMC
- PMC8280666
- Cited by
- 31
- References
- 0
- Language
- en
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