G.F. Kurakin Resident, Department of Biochemistry and Laboratory Medicine, Tver State Medical University (Tver) E-mail: N.P. Lopina Ph.D. (Chem.), Associate Professor, Department of Chemistry, Tver State Medical University (Tver) G.E. Bordina Ph.D. (Biol.), Associate Professor, Department of Chemistry, Tver State Medical University (Tver)

Isovaltrate, a valepotriate contained in valerian roots, is an inverse agonist of adenosine A1 receptor with micromolar affinity. Here, we present results of molecular modelling of its binding to this receptor by flexible docking with Galaxy7TM web server. We modelled isovaltrate binding to human and rat adenosine A1 receptor. The modelling has shown that isovaltrate mimics xanthine antagonists upon binding to adenosine A1 receptor. It occu-pies similar position and forms analogous interactions: hydrogen bond with Asn254 and hydrophobic contacts with Phe171, Leu250, Ile274. Despite lacking aromatic structure, bicyclic core formed vast hydrophobic interactions with Phe171 positioning itself similar to xanthine and flavonoid core. Other studied valepotriates, valtrate and deacetylisovaltrate, were unabe to fully mimic there interactions. We proposed that xanthine, flavonoid and isovaltrate binding is provided by common structural features: flat or almost flat bicyclic core, hydrogen bond acceptor attached to it and side chains. Obtained modelling data can be used for designing new adenosine receptor blockers and sedative drugs.

adenosine receptors
computational modelling

  1. Awang D.V.C. Valerian // In: Encyclopedia of Dietary Supplements, Second Edition. Ed. by P. Coates, J. Betz, M. Blackman, G. Cragg, M. Levine, J. Moss, J. White. Boca Raton, CRC Press, 2010.
  2. Patočka J., Jakl J. Biomedically relevant chemical constituents of Valeriana officinalis // Journal of applied biomedicine. 2010; 8(1): 11–18.
  3. Dingermann T., Loew D. Phytopharmakologie: experimentelle und klinische Pharmakologie pflanzlicherArzneimittel. Stuttgart: Wiss. Verlagsges. mbH. 2003. XIV, 367 S.
  4. Lacher S. K., Mayer R., Sichardt K., Nieber K., Müller C. E.. Inter-action of valerian extracts of different polarity with adenosine recep-tors: identification of isovaltrate as an inverse agonist at A1 recep-tors // Biochemical pharmacology. 2007; 73(2): 248–258.
  5. Sachdeva S., Gupta M. Adenosine and its receptors as therapeutic targets: an overview // Saudi Pharmaceutical Journal. 2013; 21(3): 245–253.
  6. Schingnitz G., Küfner-Mühl U., Ensinger H., Lehr E., Kuhn F. J. Selective A1-antagonists for treatment of cognitive deficits // Nucle-osides & Nucleotides. 1991; 10(5): 1067–1076.
  7. Daina A., Michielin O., Zoete V. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules // Nucleic acids research. 2019.
  8. Berman H. M., Westbrook J., Feng Z., Gilliland G., Bhat T. N., Weissig H., Shindyalov I. N., Bourne, P. E. The Protein Data Bank // Nucleic Acids Res. 2000; 28 (1): 235–242.
  9. Draper-Joyce C.J., Khoshouei M., Thal D. M. et al. Structure of the adenosine-bound human adenosine A1 receptor–Gi complex // Nature. 2018; 558 (7711): 559–563.
  10. Jarmolinska A.I., Kadlof M., Dabrowski-Tumanski P., Sulkowska J.I. GapRepairer – a server to model a structural gap and validate it using topological analysis // Bioinformatics. 2018; 1: 8.
  11. Waterhouse A., Bertoni M., Bienert S., Studer G., Tauriello G., Gumienny R., Heer F.T., de Beer T.A.P., Rempfer C., Bordoli L., Lepore R., Schwede T. SWISS-MODEL: homology modelling of protein structures and complexes// Nucleic Acids Res. 2018; 46 (W1): W296–W303.
  12. The UniProt Consortium. UniProt: the universal protein knowledgebase // Nucleic Acids Research. 2017; 45 (D1): D158–D169.
  13. Kim S., Thiessen P. A., Bolton E. E. et al. PubChem Substance and Compound databases // Nucleic Acids Res. 2016; 44(Database is-sue): D1202–D1213.
  14. Irwin J.J., Sterling T., Mysinger M.M., Bolstad E.S., Coleman R.G. ZINC: a free tool to discover chemistry for biology // Journal of chemical information and modeling. 2012; 52 (7): 1757–1768.
  15. Lee G.R., Seok C. Galaxy7TM: flexible GPCR–ligand docking by structure refinement // Nucleic acids research. 2016; 44 (W1): W502–W506.
  16. Pettersen E.F., Goddard T.D., Huang C.C., Couch G.S., Green-blatt D.M., Meng E.C., Ferrin T.E. UCSF Chimera – a visualiza-tion system for exploratory research and analysis // Journal of com-putational chemistry. 2004; 25 (13): 1605–1612.
  17. Jiménez Luna J., Skalic M., Martinez-Rosell G., De Fabritiis G.. KDEEP: Protein-ligand absolute binding affinity prediction via 3D-convolutional neural networks // Journal of chemical information and modeling. 2018; 58 (2): 287–296.
  18. Doré A. S., Robertson N., Errey J. C. et al. Structure of the adeno-sine A2A receptor in complex with ZM241385 and the xanthines XAC and caffeine // Structure. 2011; 19(9): 1283–1293.
  19. Cheng R.K.Y., Segala E., Robertson N., Deflorian F., Doré A.S., Errey J.C., Fiez-Vandal C., Marshall F.H., Cooke R.M. Structures of human A1 and A2A adenosine receptors with xanthines reveal de-terminants of selectivity // Structure. 2017; 25(8): 1275–1285. e4.
  20. Kurakin G. F., Lopina N. P., Bordina G. E. Komp'juternoe modelirovanie vzaimodejstvija flavonoidov s adenozinovymi retseptorami // Voprosy biologicheskoj, meditsinskoj i farma-tsevticheskoj himii. 2019; 22(1): 42–47 (Kurakin G.F., Lopina N.P., Bordina G.E. Computational modelling of interaction between flavonoids and adenosine receptors [In Russian] // Problems of bio-logical, medicinal and pharmaceutical chemistry. 2019; 22(1): 42–47).
  21. Harding S.D., Sharman J.L., Faccenda E. et al. The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY // Nucl. Acids Res. 2018; 46(D1): D1091–D1106.