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Molecular Dynamics Protocols for the Study of Cyclodextrin Drug Delivery Systems

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Supramolecules in Drug Discovery and Drug Delivery

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2207))

Abstract

Hypertension treatment is a current therapeutic priority as there is a constantly increasing part of the population that suffers from this risk factor, which may lead to cardiovascular and encephalic episodes and eventually to death. A number of marketed medicines consist of active ingredients that may be relatively potent; however, there is plenty of room to enhance their pharmacological profile and therapeutic index by improving specific physicochemical properties. In this work, we focus on a class of blood pressure regulators, called sartans, and we present the computational scheme for the pharmacological improvement of irbesartan (IRB) as a representative example. IRB has been shown to exert increased pharmacological action compared with other sartans, but it appears to be highly lipophilic and violates Lipinski rule (MLogP >4.15). To circumvent this drawback, proper hydrophilic molecules, such as cyclodextrins, can be used as drug carriers. This chapter describes the combinatory use of computational methods, namely molecular docking, quantum mechanics, molecular dynamics, and free energy calculations, to study the interactions and the energetic contributions that govern the IRB:cyclodextrin association. We provide a detailed computational protocol, which aims to assist the improvement of the pharmacological properties of sartans. This protocol can also be applied to any other drug molecule with diminished hydrophilic character.

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References

  1. Hodgson J (2001) ADMET—turning chemicals into drugs. Nat Biotechnol 19(8):722–726. https://doi.org/10.1038/90761

    Article  CAS  Google Scholar 

  2. Kalepu S, Nekkanti V (2015) Insoluble drug delivery strategies: review of recent advances and business prospects. Acta Pharm Sin B 5(5):442–453. https://doi.org/10.1016/j.apsb.2015.07.003

    Article  Google Scholar 

  3. Loftsson T, Brewster ME (2010) Pharmaceutical applications of cyclodextrins: basic science and product development. J Pharm Pharmacol 62(11):1607–1621. https://doi.org/10.1111/j.2042-7158.2010.01030.x

    Article  CAS  Google Scholar 

  4. Kellici TF, Tzakos AG, Mavromoustakos T (2015) Rational drug design and synthesis of molecules targeting the angiotensin II type 1 and type 2 receptors. Molecules 20(3):3868–3897. https://doi.org/10.3390/molecules20033868

    Article  CAS  Google Scholar 

  5. Hirlekar R, Kadam V (2009) Preformulation study of the inclusion complex irbesartan-beta-cyclodextrin. AAPS PharmSciTech 10(1):276–281. https://doi.org/10.1208/s12249-009-9206-5

    Article  CAS  Google Scholar 

  6. Karplus M, Petsko GA (1990) Molecular dynamics simulations in biology. Nature 347(6294):631–639. https://doi.org/10.1038/347631a0

    Article  CAS  Google Scholar 

  7. Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9(9):646–652. https://doi.org/10.1038/nsb0902-646

    Article  CAS  Google Scholar 

  8. Miranda WE, Ngo VA, Perissinotti LL, Noskov SY (2017) Computational membrane biophysics: from ion channel interactions with drugs to cellular function. Biochim Biophys Acta Proteins Proteom 1865(11 Pt B):1643–1653. https://doi.org/10.1016/j.bbapap.2017.08.008

    Article  CAS  Google Scholar 

  9. Kumari I, Sandhu P, Ahmed M, Akhter Y (2017) Molecular dynamics simulations, challenges and opportunities: a biologist’s prospective. Curr Protein Pept Sci 18(11):1163–1179. https://doi.org/10.2174/1389203718666170622074741

    Article  CAS  Google Scholar 

  10. van der Vaart A (2015) Coupled binding-bending-folding: the complex conformational dynamics of protein-DNA binding studied by atomistic molecular dynamics simulations. Biochim Biophys Acta 1850(5):1091–1098. https://doi.org/10.1016/j.bbagen.2014.08.009

    Article  CAS  Google Scholar 

  11. Boccellino M, Di Domenico M, Donniacuo M, Bitti G, Gritti G, Ambrosio P, Quagliuolo L, Rinaldi B (2018) AT1-receptor blockade: protective effects of irbesartan in cardiomyocytes under hypoxic stress. PLoS One 13(10):e0202297. https://doi.org/10.1371/journal.pone.0202297

    Article  CAS  Google Scholar 

  12. Cheng YZ, Yang SL, Wang JY, Ye M, Zhuo XY, Wang LT, Chen H, Zhang H, Yang L (2018) Irbesartan attenuates advanced glycation end products-mediated damage in diabetes-associated osteoporosis through the AGEs/RAGE pathway. Life Sci 205:184–192. https://doi.org/10.1016/j.lfs.2018.04.042

    Article  CAS  Google Scholar 

  13. Zhang F, Zhou G, Guo L, Lu F, Zhou G (2018) Comparison of clinical efficacy of metoprolol combined with irbesartan and hydrochlorothiazide and non-invasive ventilator in the emergency treatment of patients with severe heart failure. Exp Ther Med 16(6):5059–5066. https://doi.org/10.3892/etm.2018.6828

    Article  CAS  Google Scholar 

  14. Kassler-Taub K, Littlejohn T, Elliott W, Ruddy T, Adler E, Investigators FTILS (1998) Comparative efficacy of two angiotensin II receptor antagonists, irbesartan and losartan, in mild-to-moderate hypertension. Am J Hypertens 11(4):445–453. https://doi.org/10.1016/s0895-7061(97)00491-3

    Article  CAS  Google Scholar 

  15. Thompson MA (2004) Molecular docking using arguslab: an efficient shape-based search algorithm and an enhanced xscore scoring function. Abstr Pap Am Chem S 228:U360–U360

    Google Scholar 

  16. Case DA, Betz RM, Cerutti DS, Cheatham TE, Darden TA, Duke RE, Giese TJ, Gohlke H, Goetz AW, Homeyer N, Izadi S, Janowski P, Kaus J, Kovalenko A, Lee TS, LeGrand S, Li P, Lin C, Luchko T, Luo R, Madej B, Mermelstein D, Merz KM, Monard G, Nguyen H, Nguyen HT, Omelyan I, Onufriev A, Roe DR, Roitberg A, Sagui C, Simmerling CL, Botello-Smith WM, Swails J, Walker RC, Wang J, Wolf RM, Wu X, Xiao L, Kollman PA (2016) AMBER 2016. University of California, San Francisco, CA

    Google Scholar 

  17. Frisch MJ, Trucks G.W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenber, D. J (2009) Gaussian 09. Gaussian, Inc. Wallingford, CT:2–3. doi:111

    Google Scholar 

  18. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25(13):1605–1612. https://doi.org/10.1002/jcc.20084

    Article  CAS  Google Scholar 

  19. Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general amber force field. J Comput Chem 25:1157–1174. https://doi.org/10.1002/jcc.20035

    Article  CAS  Google Scholar 

  20. Kirschner KN, Yongye AB, Tschampel SM, Gonzalez-Outeirino J, Daniels CR, Foley BL, Woods RJ (2008) GLYCAM06: a generalizable biomolecular force field. Carbohydrates. J Comput Chem 29(4):622–655. https://doi.org/10.1002/jcc.20820

    Article  CAS  Google Scholar 

  21. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935. https://doi.org/10.1063/1.445869

    Article  CAS  Google Scholar 

  22. Salomon-Ferrer R, Gotz AW, Poole D, Le Grand S, Walker RC (2013) Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle Mesh Ewald. J Chem Theory Comput 9(9):3878–3888. https://doi.org/10.1021/ct400314y

    Article  CAS  Google Scholar 

  23. Izaguirre JA, Catarello DP, Wozniak JM, Skeel RD (2001) Langevin stabilization of molecular dynamics. J Chem Phys 114(5):2090–2098. https://doi.org/10.1063/1.1332996

    Article  CAS  Google Scholar 

  24. Ryckaert J-P, Ciccotti G, Berendsen HJC (1977) Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys 23(3):327–341. https://doi.org/10.1016/0021-9991(77)90098-5

    Article  CAS  Google Scholar 

  25. Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE 3rd (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33(12):889–897

    Article  CAS  Google Scholar 

  26. Gohlke H, Kiel C, Case DA (2003) 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

    Article  CAS  Google Scholar 

  27. Wang W, Kollman PA (2001) Computational study of protein specificity: the molecular basis of HIV-1 protease drug resistance. Proc Natl Acad Sci U S A 98(26):14937–14942. https://doi.org/10.1073/pnas.251265598

    Article  CAS  Google Scholar 

  28. Kellici TF, Chatziathanasiadou MV, Diamantis D, Chatzikonstantinou AV, Andreadelis I, Christodoulou E, Valsami G, Mavromoustakos T, Tzakos AG (2016) Mapping the interactions and bioactivity of quercetin-(2-hydroxypropyl)-beta-cyclodextrin complex. Int J Pharm 511(1):303–311. https://doi.org/10.1016/j.ijpharm.2016.07.008

    Article  CAS  Google Scholar 

  29. Kellici TF, Ntountaniotis D, Leonis G, Chatziathanasiadou M, Chatzikonstantinou AV, Becker-Baldus J, Glaubitz C, Tzakos AG, Viras K, Chatzigeorgiou P, Tzimas S, Kefala E, Valsami G, Archontaki H, Papadopoulos MG, Mavromoustakos T (2015) Investigation of the interactions of silibinin with 2-hydroxypropyl-beta-cyclodextrin through biophysical techniques and computational methods. Mol Pharm 12(3):954–965. https://doi.org/10.1021/mp5008053

    Article  CAS  Google Scholar 

  30. Roe DR, Cheatham TE (2013) PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput 9(7):3084–3095. https://doi.org/10.1021/ct400341p

    Article  CAS  Google Scholar 

  31. Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins 55(2):383–394. https://doi.org/10.1002/prot.20033

    Article  CAS  Google Scholar 

  32. Hawkins GD, Cramer CJ, Truhlar DG (1996) Parametrized models of aqueous free energies of solvation based on pairwise descreening of solute atomic charges from a dielectric medium. J Phys Chem 100(51):19824–19839. https://doi.org/10.1021/jp961710n

    Article  CAS  Google Scholar 

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Acknowledgments

This work has been co-financed by the European Union and Greek national funds through the program “Support for Researchers with Emphasis on Young Researchers” (call code: EDBM34, ΚΕ 14995) and under the research title “Preparation and study of innovative forms of administration of pharmaceutical molecules targeting at improved pharmacological properties.”

Author information

Authors and Affiliations

  1. Department of Chemistry, National and Kapodistrian University of Athens, Zografou, Greece

    Georgios Leonis, Dimitrios Ntountaniotis, Eirini Christodoulou & Thomas Mavromoustakos

Authors
  1. Georgios Leonis
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  2. Dimitrios Ntountaniotis
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  3. Eirini Christodoulou
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  4. Thomas Mavromoustakos
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Editor information

Editors and Affiliations

  1. Department of Chemistry, National and Kapodistrian University of Athens, Zografou, Greece

    Thomas Mavromoustakos

  2. Department of Chemistry Section of Organic Chemistry and Biochemistry, University of Ioannina, Ioannina, Greece

    Andreas G. Tzakos

  3. Computational Biology and Molecular Simulations Laboratory Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey

    Serdar Durdagi

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Leonis, G., Ntountaniotis, D., Christodoulou, E., Mavromoustakos, T. (2021). Molecular Dynamics Protocols for the Study of Cyclodextrin Drug Delivery Systems. In: Mavromoustakos, T., Tzakos, A.G., Durdagi, S. (eds) Supramolecules in Drug Discovery and Drug Delivery. Methods in Molecular Biology, vol 2207. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0920-0_9

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  • DOI: https://doi.org/10.1007/978-1-0716-0920-0_9

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0919-4

  • Online ISBN: 978-1-0716-0920-0

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