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Knowledge Based Helix Angle and Residue Distance Restraint Free Energy Terms of GPCRs

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Intelligent Computing Theories and Application (ICIC 2019)

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Abstract

The function of G-protein-coupled receptor (GPCR) in organisms are directly related to its tertiary structure. Protein free energy can well reflect the state stability of protein tertiary structure. Therefore, the research on the free energy of GPCR is of great significance. At present, there is a lack of goldenfree energy constraint GPCR structure in helix domain level in the current researches, which affects GPCR’s three-dimensional structure stability. In this paper, a knowledge-based free energy term with the residue distance and angle of the helix of the GPCR as a constraint is established. The energy term is based on the gaussian distribution model, which accurately expresses the free energy of the GPCR. Compared with other energy functions, the experimental data and the result of this model is more accurate.

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References

  1. Hauser, A.S., Attwood, M.M., Rask-Andersen, M., et al.: Trends in GPCR drug discovery: new agents, targets and indications. Nat. Rev. Drug Discov. 16, 829–842 (2017)

    Article  Google Scholar 

  2. Flock, T., Hauser, A.S., Lund, N., et al.: Selectivity determinants of GPCR–G-protein binding. Nature 545(7654), 317–322 (2017)

    Article  Google Scholar 

  3. Hilger, D., Masureel, M., Kobilka, B.K.: Structure and dynamics of GPCR signaling complexes. Nat. Struct. Mol. Biol. 25(1), 4–12 (2018)

    Article  Google Scholar 

  4. Kang, Y., Zhou, X.E., Xiang, G., et al.: Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser. Nature 523(7562), 561–567 (2015)

    Article  Google Scholar 

  5. Moritsugu, K., Terada, T., Kidera, A.: Free-energy landscape of protein-ligand interactions coupled with protein structural changes. J. Phys. Chem. B 121(4), 731–740 (2017)

    Article  Google Scholar 

  6. Takemura, K., Matubayasi, N., Kitao, A.: Binding free energy analysis of protein-protein docking model structures by evERdock. J. Chem. Phys. 148(10), 105101 (2018)

    Article  Google Scholar 

  7. 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. 330(4), 891–913 (2003)

    Article  Google Scholar 

  8. Lee, H.S., Seok, C., Im, W.: Potential application of alchemical free energy simulations to discriminate GPCR ligand efficacy. J. Chem. Theory Comput. 11(3), 1255–1266 (2015)

    Article  Google Scholar 

  9. Lenselink, E.B., Louvel, J., Forti, A.F., et al.: Predicting binding affinities for GPCR ligands using free-energy perturbation. ACS Omega 1(2), 293–304 (2016)

    Article  Google Scholar 

  10. Advances in free-energy-based simulations of protein folding and ligand binding. Curr. Opin. Struct. Biol. 36, 25–31 (2016)

    Google Scholar 

  11. Suofu, Y., Li, W., Jeanalphonse, F.G., et al.: Dual role of mitochondria in producing melatonin and driving GPCR signaling to block cytochrome c release. Proc. Natl. Acad. Sci. U.S.A. 114(38), E7997–E8006 (2017)

    Article  Google Scholar 

  12. Pavlos, N.J., Friedman, P.A.: GPCR signaling and trafficking: the long and short of it. Trends Endocrinol. Metab. 28(3), 213–226 (2017)

    Article  Google Scholar 

  13. Irannejad, R., Pessino, V., Mika, D., et al.: Functional selectivity of GPCR-directed drug action through location bias. Nat. Chem. Biol. 13(7), 799 (2017)

    Article  Google Scholar 

  14. Eichel, K., Jullié, D., Barsirhyne, B., et al.: Catalytic activation of β-arrestin by GPCRs. Nature 557, 381–386 (2018)

    Article  Google Scholar 

  15. Jean-Charles, P.Y., Kaur, S., Shenoy, S.K.: GPCR signaling via β-arrestin-dependent mechanisms. J. Cardiovasc. Pharmacol. 70(3), 142–158 (2017)

    Article  Google Scholar 

  16. Kumar, B.A., Kumari, P., Sona, C., et al.: GloSensor assay for discovery of GPCR-selective ligands. Methods Cell Biol. 142, 27–50 (2017)

    Article  Google Scholar 

  17. Pándy-Szekeres, G., Munk, C., Tsonkov, T.M., et al.: GPCRdb in 2018: adding GPCR structure models and ligands. Nucleic Acids Res. 46(Database issue), 440–446 (2017)

    Google Scholar 

  18. Mcgregor, K.M., Bécamel, C., Marin, P., et al.: Using melanopsin to study G protein signaling in cortical neurons. J. Neurophysiol. 116(3), 1082–1092 (2016)

    Article  Google Scholar 

  19. Huang, Y., Todd, N., Thathiah, A.: The role of GPCRs in neurodegenerative diseases: avenues for therapeutic intervention. Curr. Opin. Pharmacol. 32, 96–110 (2017)

    Article  Google Scholar 

  20. Gupta, A., Singh, V.: GPCR Signaling in C. Elegans and its implications in immune response. Adv. Immunol. 136, 203–226 (2017)

    Article  Google Scholar 

Download references

Acknowledgement

This paper is supported by the National Natural Science Foundation of China (61772357, 61502329, 61672371, and 61876217), Jiangsu Province 333 Talent Project, Top Talent Project (DZXX-010), Suzhou Foresight Research Project (SYG201704, SNG201610, and SZS201609)

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Correspondence to Hongjie Wu .

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Ling, H., Wu, H., Han, J., Ding, J., Lu, W., Fu, Q. (2019). Knowledge Based Helix Angle and Residue Distance Restraint Free Energy Terms of GPCRs. In: Huang, DS., Jo, KH., Huang, ZK. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science(), vol 11644. Springer, Cham. https://doi.org/10.1007/978-3-030-26969-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-26969-2_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26968-5

  • Online ISBN: 978-3-030-26969-2

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