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Combination of anti-hypertensive drugs: a molecular dynamics simulation study

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Abstract

The anti-hypertensive drugs amlodipine, atenolol and lisinopril, in ordinary and PEGylated forms, with different combined-ratios, were studied by molecular dynamics simulations using GROMACS software. Twenty simulation systems were designed to evaluate the interactions of drug mixtures with a dimyristoylphosphatidylcholine (DMPC) lipid bilayer membrane, in the presence of water molecules. In the course of simulations, various properties of the systems were investigated, including drug location, diffusion and mass distribution in the membrane; drug orientation; the lipid chain disorder as a result of drug penetration into the DMPC membrane; the number of hydrogen bonds; and drug surface area. According to the results obtained, combined drugs penetrate deeper into the DMPC lipid bilayer membrane, and the lipid chains remain ordered. Also, the combined PEGylated drugs, at a combination ratio of 1:1:1, enhance drug penetration into the DMPC membrane, reduce drug agglomeration, orient the drug in a proper angle for easy penetration into the membrane, and decrease undesirable lipotoxicity due to distorted membrane self-assembly and thickness.

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References

  1. Yousefpour A, Modarress H, Goharpey F, Amjad-Iranagh S (2015) Interaction of PEGylated anti-hypertensive drugs, amlodipine, atenolol and lisinopril with lipid bilayer membrane: a molecular dynamics simulation study. Biochim Biophys Acta 1848:1687–1698

    Article  CAS  Google Scholar 

  2. Bras NF, Fernandes PA, Ramos MJ (2014) QM/MM study and MD simulations on the hypertension regulator Angiotension-converting enzyme. ACS Catal 4:2587–2597

    Article  CAS  Google Scholar 

  3. Ntountaniotis D, Mali G, Grdadolnik SG, Maria H, Skaltsounis AL, Potamitis C, Siapi E, Chatzigeorgiou P, Rappolt M, Mavromoustakos T (2011) Thermal, dynamic and structural properties of drug AT1 antagonist olmesartan in lipid bilayers. Biochim Biophys Acta 1808:2995–3006

    Article  CAS  Google Scholar 

  4. Laplante LE (1194) Lisinopril versus atenolol in the treatment of patients with mild-to-moderate essential hypertension. Curr Ther Res 55:1027–1037

    Article  Google Scholar 

  5. Pohar A, Likozar B (2014) Dissolution, nucleation, crystal growth, crystal aggregation, and particle breakage of amlodipine salts: modeling crystallization kinetics and thermodynamic equilibrium, scale-up, and optimization. Ind Eng Chem Res 53:10762–10774

    Article  CAS  Google Scholar 

  6. Gotrane DM, Deshmukh RD, Ranade PV, Sonawane SP, Bhawal BM, Gharpure MM, Gurjar MK (2010) A novel method for resolution of amlodipine. Org Process Res Dev 14:640–643

    Article  CAS  Google Scholar 

  7. Caron G, Ermondi G, Damiano A, Novaroli L, Tsinman O, Ruell JA, Avdeef A (2004) Ionization, lipophilicity, and molecular modeling to investigate permeability and other biological properties of amlodipine. Bioorg Med Chem 12:6107–6118

    Article  CAS  Google Scholar 

  8. Akisanya J, Parkins AW, Steed JW (1998) A synthesis of atenolol using a nitrile hydration catalyst. Org Process Res Dev 2:274–276

    Article  CAS  Google Scholar 

  9. Borodi G, Bratu I, Dragan F, Peschar R, Helmholdt RB, Hernanz A (2008) Spectroscopic investigations and crystal structure from synchrotron powder data of the inclusion complex of β-cyclodextrin with atenolol. Spectrochim Acta A 70:1041

    Article  Google Scholar 

  10. Shinde V, Trivedi A, Upadhayay PR, Gupta NL, Kanase DG, Chikate R (2007) Identification of a new impurity in lisinopril. J Pharm Biomed Anal 43:381–386

    Article  CAS  Google Scholar 

  11. Ghann WE, Aras O, Fleiter T, Daniel MC (2012) Syntheses and characterization of Lisinopril-coated gold nanoparticles as highly stable targeted CT contrast agents in cardiovascular diseases. Langmuir 28:10398–10408

    Article  CAS  Google Scholar 

  12. Torres JH, Hernandez JMA, Torres JH, Paz M, Castano VM, Valdes EA (2008) Degradation of lisinopril: a physico-chemical study. J Mol Struct 886:51–58

    Article  Google Scholar 

  13. Bunker A (2012) Poly(ethylene glycol) in drug delivery, why does it work, and can we do better? All atom molecular dynamics simulation provides some answers. Phys Procedia 34:24–33

    Article  Google Scholar 

  14. Banerjee SS, Aher N, Patil R, Khandare J (2012) Poly(ethylene glycol)-prodrug conjugates: concept, design, and applications. J Drug Deliv 2012:103973. doi:10.1155/2012/103973

  15. Magarkar A, Karakas E, Stepniewski M, Rog T, Bunker A (2012) Molecular dynamics simulation of PEGylated bilayer interacting with salt ions: a model of the liposome surface in the bloodstream. J Phys Chem B 116:4212–4219

    Article  CAS  Google Scholar 

  16. Yang C, Lu D, Liu Z (2011) How PEGylation enhances the stability and potency of insulin: a molecular dynamics simulation. Biochemistry 50:2585–2593

    Article  CAS  Google Scholar 

  17. Magarkar A, Róg T, Bunker A (2014) Molecular dynamics simulation of PEGylated membranes with cholesterol: building towards the DOXIL formulation. J Phys Chem C 118:15541–15549

    Article  CAS  Google Scholar 

  18. Han E, Lee H (2013) Effects of PEGylation on the binding interaction of Magainin 2 and Tachyplesin I with lipid bilayer surface. Langmuir 29:14214–14221

    Article  CAS  Google Scholar 

  19. Roberts MJ, Bentley MD, Harris JM (2012) Chemistry for peptide and protein PEGylation. Adv Drug Deliv Rev 64:116–127

    Article  Google Scholar 

  20. Pfister D, Morbidelli M (2014) Process for protein PEGylation. J Control Release 180:134–149

    Article  CAS  Google Scholar 

  21. Blaschke T, Varon J, Werner A, Hasse H (2011) Microcalorimetric study of the adsorption of PEGylated lysozyme on a strong cation exchange resin. J Chromatogr A 1218:4720–4726

    Article  CAS  Google Scholar 

  22. Li W, Zhan P, De Clercq E, Lou H, Liu X (2013) Current drug research on PEGylation with small molecular agents. Prog Polym Sci 38:421–444

    Article  CAS  Google Scholar 

  23. Xue X, Ji S, Mu Q, Hu T (2014) Heat treatment increases the bioactivity of C-terminally PEGylated staphylokinase. Process Biochem 49:1092–1096

    Article  CAS  Google Scholar 

  24. Yang X, Ding Y, Ji T, Zhao X, Wang H, Zhao X, Zhao R, Wei J, Qi S, Nie G (2016) Improvement of the in vitro safety profile and cytoprotective efficacy of amifostine against chemotherapy by PEGylation strategy. Biochem Pharmacol 108:11–21

    Article  CAS  Google Scholar 

  25. Reichert C, Borchard G (2016) Noncovalent PEGylation, an innovative subchapter in the field of protein modification. J Pharm Sci 105:386–390

    Article  CAS  Google Scholar 

  26. Kyluik-Price DL, Scott MD (2016) Effects of methoxypoly (ethylene glycol) mediated immunocamouflage on leukocyte surface marker detection, cell conjugation, activation and alloproliferation. Biomaterials 74:167–177

    Article  CAS  Google Scholar 

  27. Moreno MM, Garidel P, Suwalsky M, Howe J, Brandenburg K (2009) The membrane-activity of ibuprofen, diclofenac, and naproxen: a physico-chemical study with lecithin phospholipids. Biochim Biophys Acta 1788:1296–1303

    Article  CAS  Google Scholar 

  28. Omote H, Al-Shawi MK (2006) Interaction of transported drugs with the lipid bilayer and P-glycoprotein through a solvation exchange mechanism. Biophys J 90:4046–4059

    Article  CAS  Google Scholar 

  29. Boggara MB, Krishnamoorti R (2010) Partitioning of nonsteroidal Antiinflammatory drugs in lipid membranes: a molecular dynamics simulation study. Biophys J 98:586–595

    Article  CAS  Google Scholar 

  30. Fiedler SL, Violi A (2010) Simulation of nanoparticle permeation through a lipid membrane. Biophys J 99:144–152

    Article  CAS  Google Scholar 

  31. Khandelia H, Witzke S, Mouritsen OG (2010) Interaction of salicylate and a terpenoid plant extract with model membranes: reconciling experiments and simulations. Biophys J 99:3887–3894

    Article  CAS  Google Scholar 

  32. Yacoub TJ, Reddy AS, Szleifer I (2011) Structural effects and translocation of doxorubicin in a DPPC/Chol bilayer: the role of cholesterol. Biophys J 101:378–385

    Article  CAS  Google Scholar 

  33. Bennett WFD, Tieleman DP (2013) Computer simulations of lipid membrane domains. Biochim Biophys Acta 1828:1765–1776

    Article  CAS  Google Scholar 

  34. Antunes E, Azoia NG, Matama T, Gomes AC, Paulo AC (2013) The activity of LE10 peptide on biological membranes using molecular dynamics, in vitro and in vivo studies. Colloids Surf B: Biointerfaces 106:240–247

    Article  CAS  Google Scholar 

  35. Pyrkova DV, Tarasova NK, Krylov NA, Nolde DE, Efremov RG (2011) Lateral clustering of lipids in hydrated bilayers composed of Dioleoylphosphatidylcholine and Dipalmitoylphosphatidylcholine. Biochemistry (Moscow) Supplement Series A: Membrane and Cell Biology 5:278–285

    Article  Google Scholar 

  36. Manna M, Róg T, Vattulainen I (2014) The challenges of understanding glycolipid functions: an open outlook based on molecular simulations. Biochim Biophys Acta 1841:1130–1145

    Article  CAS  Google Scholar 

  37. Pourmousa M, Karttunen M (2013) Early stages of interactions of cell penetrating peptide penetrating with a DPPC bilayer. Chem Phys Lipids 169:85–94

    Article  CAS  Google Scholar 

  38. Cramariuc O, Rog T, Javanainen M, Monticelli L, Polishchuk AV, Vattulainen I (2012) Mechanism for translocation of fluoroquinolones across lipid membranes. Biochim Biophys Acta 1818:2563–2571

    Article  CAS  Google Scholar 

  39. Yousefpour A, Amjad-Iranagh S, Nademi Y, Modarress H (2013) Molecular dynamics simulation of nonsteroidal Antiinflammatory drugs, naproxen and Relafen, in a lipid bilayer membrane. Int J Quantum Chem 113:1919–1930

    Article  CAS  Google Scholar 

  40. Amjad-Iranagh S, Yousefpour A, Haghighi P, Modarress H (2013) Effects of protein binding on a lipid bilayer containing local anesthetic articaine, and the potential of mean force calculation: a molecular dynamics simulation approach. J Mol Model 19:3831–3842

    Article  CAS  Google Scholar 

  41. Nademi Y, Amjad-Iranagh S, Yousefpour A, Mousavi SZ, Modarress H (2013) Molecular dynamics simulations and free energy profile of paracetamol in DPPC and DMPC lipid bilayers. J Chem Sci 126:637–647

    Article  Google Scholar 

  42. Khajeh A, Modarress H (2014) The influence of cholesterol on interactions and dynamics of ibuprofen in a lipid bilayer. Biochim Biophys Acta 1838:2431–2438

    Article  CAS  Google Scholar 

  43. Khajeh A, Modarress H (2014) Effect of cholesterol on behavior of 5-fluorouracil (5 FU) in a DMPC lipid bilayer, a molecular dynamics study. Biophys Chem 187–188:43–50

    Article  Google Scholar 

  44. Metzler R, Jeon JH, Cherstvy AG (2016) Non-Brownian diffusion in lipid membranes: experiments and simulations. Biochim Biophys Acta 1858:2451–2467

    Article  CAS  Google Scholar 

  45. Ossman T, Fabre G, Trouillas P (2016) Interaction of wine anthocyanin derivatives with lipid bilayer membranes. Comput Theor Chem 1077:80–86

    Article  CAS  Google Scholar 

  46. Azizi K, Koli MG (2016) Molecular dynamics simulations of oxprenolol and propranolol in a DPPC lipid bilayer. J Mol Graph Model 64:153–164

    Article  CAS  Google Scholar 

  47. Neale C, Pomès R (2016) Sampling errors in free energy simulations of small molecules in lipid bilayers. Biochim Biophys Acta 1858:2539–2548

    Article  CAS  Google Scholar 

  48. YenilmezÇiftçi G, Şenkuytu E, İncir S, Yuksel F, Ölçer Z, Yıldırım T, Kılıç A, Uludağ Y (2016) First paraben substituted cyclotetraphosphazene compounds and DNA interaction analysis with a new automated biosensor. Biosens Bioelectron 80:331–338

    Article  Google Scholar 

  49. Bäckström E, Lundqvist A, Boger E, Svanberg P, Ewing P, Hammarlund-Udenaes M, Friden M (2016) Development of a novel lung slice methodology for profiling of inhaled compounds. J Pharm Sci 105:838–845

    Article  Google Scholar 

  50. Foloppe N, Chen IJ (2016) Towards understanding the unbound state of drug compounds: implications for the intramolecular reorganization energy upon binding. Bioorg Med Chem 24:2159–2189

    Article  CAS  Google Scholar 

  51. Antonios TF, Cappuccio FP, Markandu ND, Sagnella GA, MacGregor GA (1996) A diuretic is more effective than a beta-blocker in hypertensive patients not controlled on amlodipine and lisinopril. Hypertension 27(6):1325–1328

    Article  CAS  Google Scholar 

  52. Cappuccio FP, Markandu ND, Singer DR, MacGregor GA (1993) Amlodipine and lisinopril in combination for the treatment of essential hypertension: efficacy and predictors of response. J Hypertens 11(8):839–847

    Article  CAS  Google Scholar 

  53. Frank J (2008) Managing hypertension using combination therapy. Am Fam Physician 77:1279–1286

    Google Scholar 

  54. Richards T, Tobe S W (2014) Combining other antihypertensive drugs with β-blockers in hypertension: a focus on safety and tolerability. Can J Cardiol S42–S46

  55. Naidu MUR, Usha PR, Rao TRK, Shobha JC (1999) Evaluation of amlodipine, lisinopril, and a combination in the treatment of essential hypertension. Postgrad Med J 76:350–353

    Article  Google Scholar 

  56. Pimenta E, Oparil S (2008) Fixed combinations in the management of hypertension: patient perspectives and rational for development and utility of the olmesartan-amlodipine combination. Vasc Health Risk Manag 4(3):653–664

    CAS  Google Scholar 

  57. Davies RF, Habibi H, Klinke WP, Dessain P, Nadeau C, Phaneuf DC, Lepage S, Raman S, Herbert M, Foris K, Linden W, Buttars JA (1995) Effect of amlodipine, atenolol and their combination on myocardial ischemia during treadmill exercise and ambulatory monitoring. J Am Coll Cardiol 25(3):619–625

    Article  CAS  Google Scholar 

  58. Saha L, Gautam CS (2011) The effect of amlodipine alone and in combination with atenolol on bowel habit in patients with hypertension: an observation. ISRN Gastroenterol. 2011:757141. doi: 10.5402/2011/757141

  59. Ling G, Liu A, Shen F, Cai G, Liu J, Su D (2007) Effects of combination therapy with atenolol and amlodipine on blood pressure control and stroke prevention in stroke-prone spontaneously hypertensive rats. Acta Pharmacol Sin 28(11):1755–1760

    Article  CAS  Google Scholar 

  60. Friedman R, Boye K, Flatmark K (2013) Molecular modelling and simulations in cancer research. Biochim Biophys Acta 1836:1–14

    CAS  Google Scholar 

  61. Lindahl E, Hess B, van der Spoel D (2001) GROMACS 3.0: a package for molecular simulation and trajectory analysis. J Mol Model 7:306–317

    Article  CAS  Google Scholar 

  62. van Der spoel D, Linahl E, Hess B, Groenhof G, Herman AEM, Berendsen JC (2005) GROMACS: fast, flexible and free. J Comput Chem 26:1701–1718

    Article  Google Scholar 

  63. Hess B, Kutzner C, Van der Spoel D, Lindahl E (2008) GROMACS4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Compute 4:435–447

    Article  CAS  Google Scholar 

  64. Berger O, Edholm O, Jähnig F (1997) Molecular dynamics simulations of a fluid bilayer of dipalmitoylphosphatidylcholine at full hydration, constant pressure and constant temperature. Biophys J 72:2002–2013

    Article  CAS  Google Scholar 

  65. Lindahl E, Edholm O (2000) Mesoscopic undulations and thickness fluctuations in lipid bilayers from molecular dynamics simulations. Biophys J 79:426–433

    Article  CAS  Google Scholar 

  66. Högberg CJ, Lyubartsev AP (2006) A molecular dynamics investigation of the influence of hydration and temperature on structural and dynamical properties of a dimyristoylphosphatidylcholine bilayer. J Phys Chem B 110:14326–14336

    Article  Google Scholar 

  67. Benz RW, Castro-Roman F, Tobias DJ, White SH (2005) Experimental validation of molecular dynamics simulations of lipid bilayers: a new approach. Biophys J 88:805–817

    Article  CAS  Google Scholar 

  68. Paloncýová M, Berka K, Otyepka M. Convergence of free energy profile of coumarin in lipid bilayer. J Chem Theory Comput 8:1200–1211

  69. Boulanger Y, Schreier S, Smith IC (1981) Molecular details of anesthetic–lipid interaction as seen by deuterium and phosphorus-31 nuclear magnetic resonance. Biochemistry 20:6824–6830

    Article  CAS  Google Scholar 

  70. Castro V, Stevensson B, Dvinskikh SV, Högberg CJ, Lyubartsev AP, Zimmermann H, Sandström D, Maliniak A (2008) NMR investigations of interactions between anesthetics and lipid bilayers. Biochim Biophys Acta 1778:2604–2611

    Article  CAS  Google Scholar 

  71. Hess B, Bekker H, Berendsen HJC, Fraaije J (1997) Lincs: a linear constraint solver for molecular simulations. J Comput Chem 18:1463–1472

    Article  CAS  Google Scholar 

  72. Hoover WG (1986) Constant–pressure equations of motion. Phys Rev A 34:2499–2500

    Article  CAS  Google Scholar 

  73. Parrinello M, Rahman A (1980) Crystal structure and pair potentials: a molecular dynamics study. Phys Rev Lett 45:1196–1199

    Article  CAS  Google Scholar 

  74. Schuettelkopf AW, van Aalten DMF (2004) PRODRG—a tool for high-throughput crystallography of protein–ligand complexes. Acta Crystallogr D 60:1355–1363

    Article  Google Scholar 

  75. Essmann U, Perera L, Pedersen LG (1995) A smooth particle mesh Ewald method. J Chem Phys 103:8577–8593

    Article  CAS  Google Scholar 

  76. Zheng H, Wu F, Wang B, Wu Y (2011) Molecular dynamics simulation on the interfacial features of phenol extraction by TBP/dodecane in water. Comput Theor Chem 970:66–72

    Article  CAS  Google Scholar 

  77. Allen WJ, Lemkul JA, Bevan DR (2009) GridMat-MD: a grid-based membrane analysis tool for use with molecular dynamics. J Comput Chem 30:1952–1958

    Article  CAS  Google Scholar 

  78. Tieleman DP (2002) http://moose.bio.ucalgary.ca/index.php

  79. Yu L, Zhang L, Sun Y (2015) Protein behavior at surfaces: orientation, conformational transitions and transport. J Chromatogr A 1382:118–134

    Article  CAS  Google Scholar 

  80. Orsi M, Essex JW (2010) Permeability of drugs and hormones through a lipid bilayer: insights from dual-resolution molecular dynamics. Soft Mater 6:3797–3808

    Article  CAS  Google Scholar 

  81. Marrink S-J, Berendsen HJC (1994) Simulation of water transport through a lipid membrane. J Phys Chem 98:4155–4168

    Article  CAS  Google Scholar 

  82. Chen P, Huang Z, Liang J, Cui T, Zhang X, Miao B, Yan L-T (2016) Diffusion and directionality of charged nanoparticles on lipid bilayer membrane. ACS Nano 10:11541–11547

    Article  CAS  Google Scholar 

  83. Garcia-Fandiño R, Piñeiro Á, Trick JL, Sansom MSP (2016) Lipid bilayer membrane perturbation by embedded nanopores: a simulation study. ACS Nano 10:3693–3701

    Article  Google Scholar 

  84. Vögele M, Hummer G (2016) Divergent diffusion coefficients in simulations of fluids and lipid membranes. J Phys Chem. B 120:8722–8732

    Article  Google Scholar 

  85. Kastelowitz N, Yin H (2014) Exosomes and microvesicles: identification and targeting by particle size and lipid chemical probes. Chembiochem 15:923–928

    Article  CAS  Google Scholar 

  86. Matysik A, Kraut RS (2014) TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers. BMC Res Notes 7:274

    Article  Google Scholar 

  87. Yu Cai, Nitesh Shashikanth, Deborah E. Leckband, Daniel K. Schwartz (2016) Cadherin diffusion in supported lipid bilayers exhibits calcium-dependent dynamic heterogeneity. Biophys J 111:2658–2665.

    Article  CAS  Google Scholar 

  88. Moore PB, Lopez CF, Klein ML (2001) Dynamical properties of a hydrated lipid bilayer from a Multinanosecond molecular dynamics simulation. Biophys J 81:2484–2494

    Article  CAS  Google Scholar 

  89. Svobodova B, Groschner K (2016) Mechanisms of lipid regulation and lipid gating in TRPC channels. Cell Calcium 59:271–279

    Article  CAS  Google Scholar 

  90. Leekumjorn S, Wu Y, Sum AK, Chan C (2008) Experimental and computational studies investigating trehalose protection of HepG2 cells from palmitate-induced toxicity. Biophys J 94:2869–2883

    Article  CAS  Google Scholar 

  91. Maris M, Waelkens E, Cnop M, D’Hertog W, Cunha DA, Korf H, Koike T, Overbergh L, Mathieu C (2011) Oleate induced Beta cell dysfunction and apoptosis: a proteomic approach to glucolipotoxicity by an unsaturated fatty acid. J Proteome Res 10:3372–3385

    Article  CAS  Google Scholar 

  92. Maris M, Robert S, Waelkens E, Derua R, Hernangomez MH, D’Hertog W, Cnop M, Mathieu C, Overbergh L (2013) Role of the saturated Nonesterified fatty acid palmitate in Beta cell dysfunction. J Proteome Res 12:347–362

    Article  CAS  Google Scholar 

  93. Villarroya F, Domingo P, Giralt M (2010) Drug-induced lipotoxicity: lipodystrophy associated with HIV-1 infection and antiretroviral treatment. Biochim Biophys Acta 1801:392–399

    Article  CAS  Google Scholar 

  94. Vaz WLC (2008) Lipid bilayers: properties. Wiley encyclopedia of chemical biology. 1–15. doi:10.1002/9780470048672.wecb281

  95. Momeni Bashusqeh S, Rastgoo A (2016) Elastic modulus of free-standing lipid bilayer. Soft Mater 14:210–216

    Article  CAS  Google Scholar 

  96. Waheed Q (2012) Molecular dynamics simulations of biological membranes. PhD Thesis, Royal Institute of Technology. Stockholm, Sweden

  97. Hofsab C, Lindahl E, Edholm O (2003) Molecular dynamics simulations of phospholipid bilayers with cholesterol. Biophys J 84:2192–2206

    Article  Google Scholar 

  98. Khatami MH, Bromberek M, Saika-Voivod I, Booth V (2014) Molecular dynamics simulations of histidine-containing cod antimicrobial peptide paralogs in self-assembled bilayers. Biochim Biophys Acta 1838:2778–2787

    Article  CAS  Google Scholar 

  99. Hanson SM, Newstead S, Swartz KJ, Sansom MSP (2015) Capsaicin interaction with TRPV1 channels in a lipid bilayer: molecular dynamics simulation. Biophys J 108:1425–1434

    Article  CAS  Google Scholar 

  100. Wanga H, Renb X, Meng F (2016) Molecular dynamics simulation of six β-blocker drugs passing across POPC bilayer. Mol Simul 42: 56–63.

  101. Boon J M, Smith B D (2002) Chemical control of phospholipid distribution across bilayer membranes. Med Res Rev 22(3):251–281. doi:10.1002/med.10009

  102. MATLAB, the language of technical computing (R2010a), www.mathworks.com

  103. Wang H, Meng F (2016) Concentration effect of cimetidine with POPC bilayer: a molecular dynamics simulation study. Mol Simul 42: 1292–1297 http://dx.doi.org/10.1080/08927022.2016.1185793.

  104. Lelimousin M, Sansom MSP (2013) Membrane perturbation by carbon nanotube insertion: pathways to internalization. Small 9:3639–3646

    Article  CAS  Google Scholar 

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Acknowledgements

The cooperation of High Performance Computing Research Center (HPCRC) of Amirkabir University of Technology (Tehran Polytechnic) is gratefully appreciated.

Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Ave, Tehran, 15875-4413, Iran

    Abbas Yousefpour, Hamid Modarress & Sepideh Amjad-Iranagh

  2. Department of Polymer Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

    Fatemeh Goharpey

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  1. Abbas Yousefpour
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  2. Hamid Modarress
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  3. Fatemeh Goharpey
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  4. Sepideh Amjad-Iranagh
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Corresponding author

Correspondence to Hamid Modarress.

Electronic supplementary material

Fig. S1

MSD curve of lisinopril in system S1. (GIF 77 kb)

High Resolution Image (TIFF 49 kb)

Fig. S2

MSD curve of PEGylated amlodipine in system S2. (GIF 74 kb)

High Resolution Image (TIFF 46 kb)

Fig. S3

MSD curve of amlodipine in system S3. (GIF 68 kb)

High Resolution Image (TIFF 43 kb)

Fig. S4

MSD curve of PEGylated amlodipine in system S4. (GIF 74 kb)

High Resolution Image (TIFF 46 kb)

Fig. S5

MSD curve of lisinopril in system S5. (GIF 105 kb)

High Resolution Image (TIFF 54 kb)

Fig. S6

MSD curve of PEGylated amlodipine in system S6. (GIF 78 kb)

High Resolution Image (TIFF 49 kb)

Fig. S7

MSD curve of atenolol in system S7. (GIF 75 kb)

High Resolution Image (TIFF 47 kb)

Fig. S8

MSD curve of PEGylated amlodipine in system S8. (GIF 78 kb)

High Resolution Image (TIFF 48 kb)

Fig. S9

MSD curve of lisinopril in system S9. (GIF 80 kb)

High Resolution Image (TIFF 53 kb)

Fig. S10

MSD curve of PEGylated amlodipine in system S10. (GIF 101 kb)

High Resolution Image (TIFF 47 kb)

Fig. S11

MSD curve of atenolol in system S11. (GIF 79 kb)

High Resolution Image (TIFF 53 kb)

Fig. S12

MSD curve of lisinopril in system S12. (GIF 105 kb)

High Resolution Image (TIFF 48 kb)

Fig. S13

MSD curve of atenolol in system S13. (GIF 112 kb)

High Resolution Image (TIFF 49 kb)

Fig. S14

MSD curve of PEGylated atenolol in system S14. (GIF 69 kb)

High Resolution Image (TIFF 43 kb)

Fig. S15

MSD curve of lisinopril in system S15. (GIF 106 kb)

High Resolution Image (TIFF 50 kb)

Fig. S16

MSD curve of PEGylated amlodipine in system S16. (GIF 107 kb)

High Resolution Image (TIFF 49 kb)

Fig. S17

MSD curve of lisinopril in system S17. (GIF 101 kb)

High Resolution Image (TIFF 48 kb)

Fig. S18

MSD curve of PEGylated amlodipine in system S18. (GIF 100 kb)

High Resolution Image (TIFF 46 kb)

Fig. S19

MSD curve of atenolol in system S19. (GIF 110 kb)

High Resolution Image (TIFF 52 kb)

Fig. S20

MSD curve of PEGylated amlodipine in system S20. (GIF 100 kb)

High Resolution Image (TIFF 45 kb)

Fig. S21

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S2. (GIF 31 kb)

High Resolution Image (TIFF 637 kb)

Fig. S22

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S3. (GIF 35 kb)

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Fig. S23

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S4. (GIF 35 kb)

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Fig. S24

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S5. (GIF 38 kb)

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Fig. S25

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S6. (GIF 33 kb)

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Fig. S26

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S7. (GIF 37 kb)

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Fig. S27

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S8. (GIF 34 kb)

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Fig. S28

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S9. (GIF 42 kb)

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Fig. S29

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S10. (GIF 34 kb)

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Fig. S30

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S11. (GIF 38 kb)

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Fig. S31

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S12. (GIF 34 kb)

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Fig. S32

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S14. (GIF 35 kb)

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Fig. S33

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S15. (GIF 33 kb)

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Fig. S34

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S16. (GIF 34 kb)

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Fig. S35

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S17. (GIF 34 kb)

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Fig. S36

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S18. (GIF 34 kb)

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Fig. S37

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S19. (GIF 32 kb)

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Fig. S38

Average net force ratio per each chain (f r=f d/f 0) vs time, where f is the average net force due to chain–chain interactions of the lipid chains in the bilayer membrane, in the presence (f d) and absence (f 0) of the drug, for simulation system S20. (GIF 32 kb)

High Resolution Image (TIFF 635 kb)

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Yousefpour, A., Modarress, H., Goharpey, F. et al. Combination of anti-hypertensive drugs: a molecular dynamics simulation study. J Mol Model 23, 158 (2017). https://doi.org/10.1007/s00894-017-3333-9

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