In silico Study on the Binding Interactions of SSTA and 18F-SSTA Towards Somatostatin Receptor Subtype 2


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Background: Somatostatin analogs (SSTAs) are versatile drugs that target a group of proteins known as somatostatin receptors. SSTAs are used for the treatment and PET-molecular imaging of Neuro Endocrine Tumors (NET), for they are labeled with the radionuclide 18F, a positron emitter radionuclide.

Objective: The aim of this work was to theoretically study the binding interactions of SSTA labeled with 18F (half-life of 109.7 min) and somatostatin receptor subtype 2. As the labeling of SSTA with 18F required the use of a prosthetic group, a hydrophilicity enhancer, and a linker, the influence of these traits on the interactions of 18F-SSTA with the SSTR-2 binding site was studied.

Methods: The binding modes of 18F-labeled analogues with SSTR-2 were studied by using protein homology modelling, non-equilibrium molecular dynamics, and molecular docking calculations, by means of three docking software: MVD, MOE, and VINA.

Results: The results showed the main role of Asp122, Asn276, Phe272 and Phe294 from the SSTR-2 binding site, which form interactions with residues Lys, Trp, Tyr, and Thr from 18F-labeled somatostatin analogues.

Conclusion: The interaction between Lys (from 18F-SSTA) and Asp122 (from SSTR-2) was identified as the most energetic and considered the one that drives the binding between 18F-SSTA and SSTR-2 (the anchor interaction). Despite the presence of prosthetic groups, linkers, and hydrophilicity enhancers, all the studied 18F-SSTA formed the anchor interaction. The trend in the results agreed with the experimental reports, identifying the main role of Asp122 in the binding of somatostatin-14 to SSTR-2.

Sobre autores

David Pérez

Unidad Radiofarmacia‑Ciclotrón, División de Investigación, Facultad de Medicina, Universidad Nacional Autónoma de México

Autor responsável pela correspondência
Email: info@benthamscience.net

Rodrigo Razo-Hernández

Centro de Investigación en Dinámica Celular, Instituto de Investigación en Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos

Autor responsável pela correspondência
Email: info@benthamscience.net

Miguel Ávila-Rodríguez

Unidad Radiofarmacia‑Ciclotrón, División de Investigación, Facultad de Medicina,, Universidad Nacional Autónoma de México

Autor responsável pela correspondência
Email: info@benthamscience.net

Bibliografia

  1. Dasgupta, P. Somatostatin analogues: Multiple roles in cellular proliferation, neoplasia, and angiogenesis. Pharmacol. Ther., 2004, 102(1), 61-85. doi: 10.1016/j.pharmthera.2004.02.002 PMID: 15056499
  2. Klomp, M.J.; Dalm, S.U.; de Jong, M.; Feelders, R.A.; Hofland, J.; Hofland, L.J. Epigenetic regulation of somatostatin and somatostatin receptors in neuroendocrine tumors and other types of cancer. Rev. Endocr. Metab. Disord., 2021, 22(3), 495-510. doi: 10.1007/s11154-020-09607-z PMID: 33085037
  3. Mizutani, G.; Nakanishi, Y.; Watanabe, N.; Honma, T.; Obana, Y.; Seki, T.; Ohni, S.; Nemoto, N. Expression of somatostatin receptor (SSTR) subtypes (SSTR-1, 2A, 3, 4 and 5) in neuroendocrine tumors using real-time RT-PCR method and immunohistochemistry. Acta Histochem. Cytochem., 2012, 45(3), 167-176. doi: 10.1267/ahc.12006 PMID: 22829710
  4. Keskin, O.; Yalcin, S. A review of the use of somatostatin analogs in oncology. OncoTargets Ther., 2013, 6, 471-483. PMID: 23667314
  5. Kaltsas, G.A.; Besser, G.M.; Grossman, A.B. The diagnosis and medical management of advanced neuroendocrine tumors. Endocr. Rev., 2004, 25(3), 458-511. doi: 10.1210/er.2003-0014 PMID: 15180952
  6. Johnbeck, C.B.; Knigge, U.; Loft, A.; Berthelsen, A.K.; Mortensen, J.; Oturai, P.; Langer, S.W.; Elema, D.R.; Kjaer, A. Head-to-Head Comparison of 64Cu-DOTATATE and 68Ga-DOTATOC PET/CT: A prospective study of 59 patients with neuroendocrine tumors. J. Nucl. Med., 2017, 58(3), 451-457. doi: 10.2967/jnumed.116.180430 PMID: 27660147
  7. Smit Duijzentkunst, D.A.; Kwekkeboom, D.J.; Bodei, L. Somatostatin receptor 2-targeting compounds. J. Nucl. Med., 2017, 58(Suppl. 2), 54S-60S. doi: 10.2967/jnumed.117.191015 PMID: 28864613
  8. Richter, S.; Wuest, F. 18 F-labeled peptides: The future is bright. Molecules, 2014, 19(12), 20536-20556. doi: 10.3390/molecules191220536 PMID: 25493636
  9. Jacobson, O.; Zhu, L.; Ma, Y.; Weiss, I.D.; Sun, X.; Niu, G.; Kiesewetter, D.O.; Chen, X. Rapid and simple one-step F-18 labeling of peptides. Bioconjug. Chem., 2011, 22(3), 422-428. doi: 10.1021/bc100437q PMID: 21338096
  10. Liu, S.; Shen, B.T.; Chin, F. Recent progress in radiofluorination of peptides for PET molecular imaging. Curr. Org. Synth., 2011, 8, 584-592. doi: 10.2174/157017911796117197
  11. Wester, H.J.; Brockmann, J.; Rösch, F.; Wutz, W.; Herzog, H.; Smith-Jones, P.; Stolz, B.; Bruns, C.; Stöcklin, G. PET-pharmacokinetics of 18F-octreotide: A comparison with 67Ga-DFO and 86Y-DTPA-octreotide. Nucl. Med. Biol., 1997, 24(4), 275-286. doi: 10.1016/S0969-8051(97)00039-5 PMID: 9257325
  12. Wester, H.J.; Schottelius, M.; Poethko, T.; Bruus-Jensen, K.; Schwaiger, M. Radiolabeled carbohydrated somatostatin analogs: A review of the current status. Cancer Biother. Radiopharm., 2004, 19(2), 231-244. doi: 10.1089/108497804323072011 PMID: 15186604
  13. Schottelius, M.; Poethko, T.; Herz, M.; Reubi, J.C.; Kessler, H.; Schwaiger, M.; Wester, H.J. First (18)F-labeled tracer suitable for routine clinical imaging of sst receptor-expressing tumors using positron emission tomography. Clin. Cancer Res., 2004, 10(11), 3593-3606. doi: 10.1158/1078-0432.CCR-03-0359 PMID: 15173065
  14. Strnad, J.; Hadcock, J.R. Identification of a critical aspartate residue in transmembrane domain three necessary for the binding of somatostatin to the somatostatin receptor SSTR2. Biochem. Biophys. Res. Commun., 1995, 216(3), 913-921. doi: 10.1006/bbrc.1995.2708 PMID: 7488212
  15. Liapakis, G.; Fitzpatrick, D.; Hoeger, C.; Rivier, J.; Vandlen, R.; Reisine, T. Identification of ligand binding determinants in the somatostatin receptor subtypes 1 and 2. J. Biol. Chem., 1996, 271(34), 20331-20339. doi: 10.1074/jbc.271.34.20331 PMID: 8702767
  16. Kaupmann, K.; Bruns, C.; Raulf, F.; Weber, H.P.; Mattes, H.; Lübbert, H. Two amino acids, located in transmembrane domains VI and VII, determine the selectivity of the peptide agonist SMS 201-995 for the SSTR2 somatostatin receptor. EMBO J., 1995, 14(4), 727-735. doi: 10.1002/j.1460-2075.1995.tb07051.x PMID: 7882976
  17. Modlin, I.M.; Pavel, M.; Kidd, M.; Gustafsson, B.I. Review article: Somatostatin analogues in the treatment of gastroenteropancreatic neuroendocrine (carcinoid) tumours. Aliment. Pharmacol. Ther., 2010, 31(2), 169-188. PMID: 19845567
  18. Kumar Nagarajan, S.; Babu, S.; Sohn, H.; Devaraju, P.; Madhavan, T. Toward a better understanding of the interaction between somatostatin receptor 2 and its ligands: A structural characterization study using molecular dynamics and conceptual density functional theory. J. Biomol. Struct. Dyn., 2019, 37(12), 3081-3102. doi: 10.1080/07391102.2018.1508368 PMID: 30079808
  19. Nagarajan, S.K.; Babu, S.; Kulkarni, S.A.; Vadivelu, A.; Devaraju, P.; Sohn, H.; Madhavan, T. Understanding the influence of lipid bilayers and ligand molecules in determining the conformational dynamics of somatostatin receptor 2. Sci. Rep., 2021, 11(1), 7677. doi: 10.1038/s41598-021-87422-5 PMID: 33828200
  20. Wavefunction Inc. SPARTAN´20.
  21. Bienert, S.; Waterhouse, A.; de Beer, T.A.P.; Tauriello, G.; Studer, G.; Bordoli, L.; Schwede, T. The SWISS-MODEL Repository-new features and functionality. Nucleic Acids Res., 2017, 45(D1), D313-D319. doi: 10.1093/nar/gkw1132 PMID: 27899672
  22. Fenalti, G.; Giguere, P.M.; Katritch, V.; Huang, X.P.; Thompson, A.A.; Cherezov, V.; Roth, B.L.; Stevens, R.C. Molecular control of δ-opioid receptor signalling. Nature, 2014, 506(7487), 191-196. doi: 10.1038/nature12944 PMID: 24413399
  23. Bateman, A.; Martin, M.J.; Orchard, S.; Magrane, M.; Agivetova, R.; Ahmad, S.; Alpi, E.; Bowler-Barnett, E.H.; Britto, R.; Bursteinas, B.; Bye-A-Jee, H.; Coetzee, R.; Cukura, A.; Da Silva, A.; Denny, P.; Dogan, T.; Ebenezer, T.G.; Fan, J.; Castro, L.G.; Garmiri, P.; Georghiou, G.; Gonzales, L.; Hatton-Ellis, E.; Hussein, A.; Ignatchenko, A.; Insana, G.; Ishtiaq, R.; Jokinen, P.; Joshi, V.; Jyothi, D.; Lock, A.; Lopez, R.; Luciani, A.; Luo, J.; Lussi, Y.; MacDougall, A.; Madeira, F.; Mahmoudy, M.; Menchi, M.; Mishra, A.; Moulang, K.; Nightingale, A.; Oliveira, C.S.; Pundir, S.; Qi, G.; Raj, S.; Rice, D.; Lopez, M.R.; Saidi, R.; Sampson, J.; Sawford, T.; Speretta, E.; Turner, E.; Tyagi, N.; Vasudev, P.; Volynkin, V.; Warner, K.; Watkins, X.; Zaru, R.; Zellner, H.; Bridge, A.; Poux, S.; Redaschi, N.; Aimo, L.; Argoud-Puy, G.; Auchincloss, A.; Axelsen, K.; Bansal, P.; Baratin, D.; Blatter, M-C.; Bolleman, J.; Boutet, E.; Breuza, L.; Casals-Casas, C.; de Castro, E.; Echioukh, K.C.; Coudert, E.; Cuche, B.; Doche, M.; Dornevil, D.; Estreicher, A.; Famiglietti, M.L.; Feuermann, M.; Gasteiger, E.; Gehant, S.; Gerritsen, V.; Gos, A.; Gruaz-Gumowski, N.; Hinz, U.; Hulo, C.; Hyka-Nouspikel, N.; Jungo, F.; Keller, G.; Kerhornou, A.; Lara, V.; Le Mercier, P.; Lieberherr, D.; Lombardot, T.; Martin, X.; Masson, P.; Morgat, A.; Neto, T.B.; Paesano, S.; Pedruzzi, I.; Pilbout, S.; Pourcel, L.; Pozzato, M.; Pruess, M.; Rivoire, C.; Sigrist, C.; Sonesson, K.; Stutz, A.; Sundaram, S.; Tognolli, M.; Verbregue, L.; Wu, C.H.; Arighi, C.N.; Arminski, L.; Chen, C.; Chen, Y.; Garavelli, J.S.; Huang, H.; Laiho, K.; McGarvey, P.; Natale, D.A.; Ross, K.; Vinayaka, C.R.; Wang, Q.; Wang, Y.; Yeh, L-S.; Zhang, J.; Ruch, P.; Teodoro, D. UniProt: The universal protein knowledgebase in 2021. Nucleic Acids Res., 2021, 49(D1), D480-D489. doi: 10.1093/nar/gkaa1100 PMID: 33237286
  24. Roy, A.; Kucukural, A.; Zhang, Y. I-TASSER: A unified platform for automated protein structure and function prediction. Nat. Protoc., 2010, 5(4), 725-738. doi: 10.1038/nprot.2010.5 PMID: 20360767
  25. Yang, J.; Zhang, Y. I-TASSER server: New development for protein structure and function predictions. Nucleic Acids Res., 2015, 43(W1), W174-W181. doi: 10.1093/nar/gkv342 PMID: 25883148
  26. Baek, M.; DiMaio, F.; Anishchenko, I.; Dauparas, J.; Ovchinnikov, S.; Lee, G.R.; Wang, J.; Cong, Q.; Kinch, L.N.; Schaeffer, R.D.; Millán, C.; Park, H.; Adams, C.; Glassman, C.R.; DeGiovanni, A.; Pereira, J.H.; Rodrigues, A.V.; van Dijk, A.A.; Ebrecht, A.C.; Opperman, D.J.; Sagmeister, T.; Buhlheller, C.; Pavkov-Keller, T.; Rathinaswamy, M.K.; Dalwadi, U.; Yip, C.K.; Burke, J.E.; Garcia, K.C.; Grishin, N.V.; Adams, P.D.; Read, R.J.; Baker, D. Accurate prediction of protein structures and interactions using a three-track neural network. Science, 2021, 373(6557), 871-876. doi: 10.1126/science.abj8754 PMID: 34282049
  27. Skolnick, J.; Gao, M.; Zhou, H.; Singh, S. AlphaFold 2: Why it works and its implications for understanding the relationships of protein sequence, structure, and function. J. Chem. Inf. Model., 2021, 61(10), 4827-4831. doi: 10.1021/acs.jcim.1c01114 PMID: 34586808
  28. Jumper, J.; Evans, R.; Pritzel, A.; Green, T.; Figurnov, M.; Ronneberger, O.; Tunyasuvunakool, K.; Bates, R.; Žídek, A.; Potapenko, A.; Bridgland, A.; Meyer, C.; Kohl, S.A.A.; Ballard, A.J.; Cowie, A.; Romera-Paredes, B.; Nikolov, S.; Jain, R.; Adler, J.; Back, T.; Petersen, S.; Reiman, D.; Clancy, E.; Zielinski, M.; Steinegger, M.; Pacholska, M.; Berghammer, T.; Bodenstein, S.; Silver, D.; Vinyals, O.; Senior, A.W.; Kavukcuoglu, K.; Kohli, P.; Hassabis, D. Highly accurate protein structure prediction with AlphaFold. Nature, 2021, 596(7873), 583-589. doi: 10.1038/s41586-021-03819-2 PMID: 34265844
  29. Laskowski, R.; Rullmann, J.A.C.; MacArthur, M.; Kaptein, R.; Thornton, J. AQUA and PROCHECK-NMR: Programs for checking the quality of protein structures solved by NMR. J. Biomol. NMR, 1996, 8(4), 477-486. doi: 10.1007/BF00228148 PMID: 9008363
  30. Laskowski, R.A.; MacArthur, M.W.; Moss, D.S.; Thornton, J.M. PROCHECK: A program to check the stereochemical quality of protein structures. J. Appl. Cryst., 1993, 26(2), 283-291. doi: 10.1107/S0021889892009944
  31. Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera?A visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612. doi: 10.1002/jcc.20084 PMID: 15264254
  32. Volkamer, A.; Kuhn, D.; Grombacher, T.; Rippmann, F.; Rarey, M. Combining global and local measures for structure-based druggability predictions. J. Chem. Inf. Model., 2012, 52(2), 360-372. doi: 10.1021/ci200454v PMID: 22148551
  33. Fährrolfes, R.; Bietz, S.; Flachsenberg, F.; Meyder, A.; Nittinger, E.; Otto, T.; Volkamer, A.; Rarey, M. ProteinsPlus: A web portal for structure analysis of macromolecules. Nucleic Acids Res., 2017, 45(W1), W337-W343. doi: 10.1093/nar/gkx333 PMID: 28472372
  34. Thomsen, R.; Christensen, M.H. MolDock: A new technique for high-accuracy molecular docking. J. Med. Chem., 2006, 49(11), 3315-3321. doi: 10.1021/jm051197e PMID: 16722650
  35. Chemical Computing Group ULC. Molecular Operating Environment (MOE).
  36. Kokh, D.B.; Czodrowski, P.; Rippmann, F.; Wade, R.C. Perturbation approaches for exploring protein binding site flexibility to predict transient binding pockets. J. Chem. Theory Comput., 2016, 12(8), 4100-4113. doi: 10.1021/acs.jctc.6b00101 PMID: 27399277
  37. Yuan, J.H.; Han, S.B.; Richter, S.; Wade, R.C.; Kokh, D.B. Druggability assessment in TRAPP using machine learning approaches. J. Chem. Inf. Model., 2020, 60(3), 1685-1699. doi: 10.1021/acs.jcim.9b01185 PMID: 32105476
  38. Stank, A.; Kokh, D.B.; Horn, M.; Sizikova, E.; Neil, R.; Panecka, J.; Richter, S.; Wade, R.C. TRAPP webserver: Predicting protein binding site flexibility and detecting transient binding pockets. Nucleic Acids Res., 2017, 45(W1), W325-W330. doi: 10.1093/nar/gkx277 PMID: 28431137
  39. Dallakyan, S.; Olson, A.J. Small-molecule library screening by docking with PyRx. Methods Mol. Biol., 2015, 1263, 243-250. doi: 10.1007/978-1-4939-2269-7_19 PMID: 25618350
  40. Johnbeck, C.B.; Knigge, U.; Kjær, A. PET tracers for somatostatin receptor imaging of neuroendocrine tumors: Current status and review of the literature. Future Oncol., 2014, 10(14), 2259-2277. doi: 10.2217/fon.14.139 PMID: 25471038
  41. Naydenova, E.; Wesselinova, D.; Staykova, S.; Danalev, D.; Dzimbova, T. Synthesis, in vitro biological activity and docking of new analogs of BIM-23052 containing unnatural amino acids. Amino Acids, 2019, 51(9), 1247-1257. doi: 10.1007/s00726-019-02758-7 PMID: 31350614
  42. Kozakov, D.; Hall, D.R.; Xia, B.; Porter, K.A.; Padhorny, D.; Yueh, C.; Beglov, D.; Vajda, S. The ClusPro web server for protein-protein docking. Nat. Protoc., 2017, 12(2), 255-278. doi: 10.1038/nprot.2016.169 PMID: 28079879
  43. BIOVIA DS. Discovery Studio Visualizer,
  44. Iddon, L.; Leyton, J.; Indrevoll, B.; Glaser, M.; Robins, E.G.; George, A.J.T.; Cuthbertson, A.; Luthra, S.K.; Aboagye, E.O. Synthesis and in vitro evaluation of 18Ffluoroethyl triazole labelled Tyr3octreotate analogues using click chemistry. Bioorg. Med. Chem. Lett., 2011, 21(10), 3122-3127. doi: 10.1016/j.bmcl.2011.03.016 PMID: 21458258
  45. Leyton, J.; Iddon, L.; Perumal, M.; Indrevoll, B.; Glaser, M.; Robins, E.; George, A.J.T.; Cuthbertson, A.; Luthra, S.K.; Aboagye, E.O. Targeting somatostatin receptors: Preclinical evaluation of novel 18F-fluoroethyltriazole-Tyr3-octreotate analogs for PET. J. Nucl. Med., 2011, 52(9), 1441-1448. doi: 10.2967/jnumed.111.088906 PMID: 21852355
  46. Yang, J.; Yan, R.; Roy, A.; Xu, D.; Poisson, J.; Zhang, Y. The I-TASSER Suite: protein structure and function prediction. Nat. Methods, 2015, 12(1), 7-8. doi: 10.1038/nmeth.3213 PMID: 25549265
  47. Nagarajan, S.K.; Babu, S.; Sohn, H.; Madhavan, T. Molecular-level understanding of the somatostatin receptor 1 (SSTR1)-Ligand binding: A structural biology study based on computational methods. ACS Omega, 2020, 5(33), 21145-21161. doi: 10.1021/acsomega.0c02847 PMID: 32875251
  48. Studer, G.; Rempfer, C.; Waterhouse, A.M.; Gumienny, R.; Haas, J.; Schwede, T. QMEANDisCo-distance constraints applied on model quality estimation. Bioinformatics, 2020, 36(6), 1765-1771. doi: 10.1093/bioinformatics/btz828 PMID: 31697312
  49. Waldmann, C.M.; Stuparu, A.D.; van Dam, R.M.; Slavik, R. The search for an alternative to 68GaGa-DOTA-TATE in neuroendocrine tumor theranostics: Current state of 18f-labeled somatostatin analog development. Theranostics, 2019, 9(5), 1336-1347. doi: 10.7150/thno.31806 PMID: 30867834
  50. Maschauer, S; Prante, O. Sweetening pharmaceutical radiochemistry by 18F- fluoroglycosylation: A short review. BioMed. Res. Int., 2014, 214748. doi: 10.1155/2014/214748
  51. Maschauer, S.; Heilmann, M.; Wängler, C.; Schirrmacher, R.; Prante, O. Radiosynthesis and preclinical evaluation of 18F-fluoroglycosylated octreotate for somatostatin receptor imaging. Bioconjug. Chem., 2016, 27(11), 2707-2714. doi: 10.1021/acs.bioconjchem.6b00472 PMID: 27715017
  52. Wester, H.J.; Schottelius, M.; Scheidhauer, K.; Reubi, J.C.; Wolf, I.; Schwaiger, M. Comparison of radioiodinated TOC, TOCA and Mtr-TOCA: the effect of carbohydration on the pharmacokinetics. Eur. J. Nucl. Med. Mol. Imaging, 2002, 29(1), 28-38. doi: 10.1007/s00259-001-0669-1 PMID: 11807604
  53. H. Wester, M.; Schottelius, K.; Scheidhauer, G.; Meisetschläger, M.; Herz, F.; Rau & M., Schwaiger. PET imaging of somatostatin receptors: design, synthesis and preclinical evaluation of a novel 18 F-labelled, carbohydrated analogue of octreotide. Eur. J. Nucl. Med. Mol. Imaging, 2003, 30(1), 117-122. doi: 10.1007/s00259-002-1012-1 PMID: 12483418

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