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Combined docking, molecular dynamics simulations and spectroscopic studies for the rational design of a dipeptide ligand for affinity chromatography separation of human serum albumin

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Abstract

A computational approach to designing a peptide-based ligand for the purification of human serum albumin (HSA) was undertaken using molecular docking and molecular dynamics (MD) simulation. A three-step procedure was performed to design a specific ligand for HSA. Based on the candidate pocket structure of HSA (warfarin binding site), a peptide library was built. These peptides were then docked into the pocket of HSA using the GOLD program. The GOLDscore values were used to determine the affinity of peptides for HSA. Consequently, the dipeptide Trp–Trp, which shows a high GOLDscore value, was selected and linked to a spacer arm of Lys[CO(CH2)5NH] on the surface of ECH-lysine sepharose 4 gel. For further evaluation, the Autodock Vina program was used to dock the linked compound into the pocket of HSA. The docking simulation was performed to obtain a first guess of the binding structure of the spacer–Trp–Trp–HSA complex and subsequently analyzed by MD simulations to assess the reliability of the docking results. These MD simulations indicated that the ligand–HSA complex remains stable, and water molecules can bridge between the ligand and the protein by hydrogen bonds. Finally, absorption spectroscopic studies were performed to illustrate the appropriateness of the binding affinity of the designed ligand toward HSA. These studies demonstrate that the designed dipeptide can bind preferentially to the warfarin binding site.

Three-step computational approach to the design of a dipeptide ligand for human serum albumin purification exploiting structure-based docking and molecular dynamics simulation

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References

  1. Brgles M, Clifton J, Walsh R, Huang F, Rucevic M, Cao L, Hixson D, Müller E, Dj J (2011) Selectivity of monolithic supports under overloading conditions and their use for separation of human plasma and isolation of low abundance proteins. J Chromatogr A 1218:2389–2395

    Article  CAS  Google Scholar 

  2. Nice EC, Rothacker J, Weinstock J, Lim L, Catimel B (2007) Use of multidimensional separation protocols for the purification of trace components in complex biological samples for proteomics analysis. J Chromatogr A 1168:190–210

    Article  CAS  Google Scholar 

  3. Anderson NL, Anderson NG (2002) The human plasma proteome. Mol Cell Proteomics 1:845–867

    Article  CAS  Google Scholar 

  4. Issaq HJ (2001) The role of separation science in proteomics research. Electrophoresis 22:3629–3638

    Article  CAS  Google Scholar 

  5. Zhu G, Zhao P, Deng N, Tao D, Sun L, Liang Z, Zhang L, Zhang Y (2012) Single chain variable fragment displaying M13 phage library functionalized magnetic microsphere-based protein equalizer for human serum protein analysis. Anal Chem 84:7633–7637

    Article  CAS  Google Scholar 

  6. Anderson LN, Polanski M, Pieper R et al (2004) The human plasma proteome. Mol Cell Proteomics 3:311–326

    Article  CAS  Google Scholar 

  7. Ray S, Reddy PJ, Jain R, Gollapalli K, Moiyadi A, Srivastava S (2011) Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead. Proteomics 11:2139–2161. doi:10.1002/pmic.201000460

    Article  CAS  Google Scholar 

  8. Liu FF, Dong XY, Wang T, Sun Y (2007) Rational design of peptide ligand for affinity chromatography of tissue-type plasminogen activator by the combination of docking and molecular dynamics simulations. J Chromatogr A 1175:249–258

    Article  CAS  Google Scholar 

  9. Ren D, Penner NA, Slentz BE et al (2004) Contributions of commercial sorbents to the selectivity in immobilized metal affinity chromatography with Cu(II). J Chromatogr A 1031:87–92

    Article  CAS  Google Scholar 

  10. Affinity chromatography Handbook; principles and methods. GE Healthcare, product code 18-1022-29.

  11. Qiao Y, Li P, Chen Y, Feng J, Wang J, Wang W, Ma Y, Sun P, Yuan Z (2010) Design, optimization and evaluation of specific affinity adsorbent for oligopeptides. J Chromatogr A 1217:7539–7546

    Article  CAS  Google Scholar 

  12. Qiao Y, Zhao J, Li P, Wang J, Feng J, Wang W, Sun H, Ma Y, Yuan Z (2010) Adsorbents with high selectivity for uremic middle molecular peptides containing the Asp-Phe-Leu-Ala-Glu sequence. Langmuir 26:7181–7187

    Article  CAS  Google Scholar 

  13. Labrou NE, Eliopoulos E, Clonis YD (1999) Molecular modeling for the design of biomimetic chimeric ligand. Aplication to the purification of bovine heart l-lactate dehydrogenase. Biotechnol Bioeng 63:322–332

    Article  CAS  Google Scholar 

  14. Liu FF, Wang T, Dong XY, Sun Y (2007) Rational design of affinity peptide ligand by flexible docking simulation. J Chromatogr A 1146:41–50

    Article  CAS  Google Scholar 

  15. Platis D, Sotriffer CA, Clonis Y, Labrou NE (2006) Rational design of affinity peptide ligand by flexible docking simulation. J Chromatogr A 1128:138–151

    Article  CAS  Google Scholar 

  16. Ghasemi JB, Tavakoli H (2012) Improvement of the prediction power of the CoMFA and CoMSIA models on Histamine H3 antagonists by different variable selection methods. Sci Pharm 80:547–566. doi:10.3797/scipharm.1204-19

    Article  CAS  Google Scholar 

  17. Ghasemi JB, Meftahi N, Pirhadi S, Tavakoli H (2013) Docking and pharmacophore-based alignment comparative molecular field analysis three-dimensional quantitative structure–activity relationship analysis of dihydrofolate reductase inhibitors by linear and nonlinear calibration methods. J Chemometr 27:287–296

    Article  CAS  Google Scholar 

  18. Ghasemi JB, Aghaee E, Jabbari A (2013) Docking, CoMFA and CoMSIA studies of a series of N-benzoylated phenoxazines and phenothiazines derivatives as antiproliferative agents. Bull Korean Chem Soc 34:899–906

    Article  CAS  Google Scholar 

  19. Budin N, Majeux N, Tenette-Souaille C, Caflisch A (2001) Structure-based ligand design by a build-up approach and genetic algorithm search in conformational space. J Comput Chem 22:1956–1970

    Article  CAS  Google Scholar 

  20. Pirhadi S, Shiri F, Ghasemi JB (2013) Methods and applications of structure based pharmacophores in drug discovery. Curr Top Med Chem 13:1036–1047

    Article  CAS  Google Scholar 

  21. Ardakani A, Ghasemi JB (2013) Identification of novel inhibitors of HIV-1 integrase using pharmacophore-based virtual screening combined with molecular docking strategies. Med Chem Res 22:5545–5556

    Article  CAS  Google Scholar 

  22. Warren GL, Andrews CW, Capelli AM et al (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49:5912–5931

    Article  CAS  Google Scholar 

  23. Sousa SF, Fernandes PA, Ramos MJ (2006) Protein-ligand docking: current status and future challenges. Proteins 65:15–26

    Article  CAS  Google Scholar 

  24. Rupasinghe CN, Spaller MR (2006) The interplay between structure-based design and combinatorial chemistry. Curr Opin Chem Biol 10:188–193

    Article  CAS  Google Scholar 

  25. Kroemer RT (2007) Structure-based drug design: docking and scoring. Curr Protein Pept Sc 8:312–328

    Article  CAS  Google Scholar 

  26. Hunter WN (2009) Structure-based ligand design and the promise held for antiprotozoan drug discovery. J Biol Chem 284:11749–11753

    Article  CAS  Google Scholar 

  27. Stahl M, Rarey M (2001) Detailed analysis of scoring functions for virtual screening. J Med Chem 44:1035–1042

    Article  CAS  Google Scholar 

  28. Kuntz ID, Blaney JM, Oatley SJ, Langridge R, Ferrin TE (1982) A geometric approach to macromolecule-ligand interactions. J Mol Biol 161:269–288

    Article  CAS  Google Scholar 

  29. Ewing TJA, Kuntz ID (1997) Critical evaluation of search algorithms for automated molecular docking and database screening. J Comput Chem 18:1176–1189

    Article  Google Scholar 

  30. Rarey M, Kramer B, Lengauer T, Klebe G (1996) A fast flexible docking method using an incremental construction algorithm. J Mol Biol 261:470–489

    Article  CAS  Google Scholar 

  31. Rarey M, Kramer B, Lengauer T (1999) The particle concept: placing discrete water molecules during protein-ligand docking predictions. Proteins 34:17–28

    Article  CAS  Google Scholar 

  32. Morris GM, Goodsell DS, Halliday RS et al (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comp Chem 19:1639–1662

    Article  CAS  Google Scholar 

  33. Goodsell DS, Morris GM, Olson AJ (1996) Automated docking of flexible ligands: applications of autodock. J Mol Recognit 9:1–5

    Article  CAS  Google Scholar 

  34. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748

    Article  CAS  Google Scholar 

  35. Kitchen DB, Decornez H, Furr JR, Bajorath J (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3:935–949. doi:10.1038/nrd1549

    Article  CAS  Google Scholar 

  36. Alonso H, Bliznyuk AA, Gready JE (2006) Combining docking and molecular dynamic simulations in drug design. Med Res Rev 26:531–568

    Article  CAS  Google Scholar 

  37. Ghasemi JB, Hooshmand S (2013) 3D-QSAR, docking and molecular dynamics for factor Xa inhibitors as anticoagulant agents. Mol Simul 39:453–471

    Article  CAS  Google Scholar 

  38. Manetti F, Locatelli GA, Maga G et al (2006) A combination of docking/dynamics simulations and pharmacophoric modeling to discover new dual c-Src/Abl kinase inhibitors. J Med Chem 49:3278–3286

    Article  CAS  Google Scholar 

  39. Li L, Wei DQ, Wang JF, Chou KC (2007) Computational studies of the binding mechanism of calmodulin with chrysin. Biochem Biophys Res Commun 358:1102–1107

    Article  CAS  Google Scholar 

  40. Kesner TF, Elcock AH (2006) Computational sampling of a cryptic drug binding site in a protein receptor: explicit solvent molecular dynamics and inhibitor docking to p38 map kinase. J Mol Biol 359:202–214

    Article  Google Scholar 

  41. Arabanian A, Mohammadnejad M, Balalaie S, Gross JH (2009) Synthesis of novel Gn-RH analogues using Ugi-4MCR. Bioorg Med Chem Lett 19:887–890

    Article  CAS  Google Scholar 

  42. Arabanian A, Mohammadnejad M, Balalaie S (2010) A novel and efficient approach for the amidation of C-terminal peptides. J Iran Chem Soc 7:840–845

    Article  CAS  Google Scholar 

  43. Rezaee Z, Arabanian A, Balalaie S, Ahmadiani A, Nasoohi S (2012) Semicarbazide substitution enhances enkephalins resistance to ace induced hydrolysis. Int J Pept Res Ther 18:305

    Article  CAS  Google Scholar 

  44. Tahoori F, Sheikhnejad R, Balalaie S, Sadjadi M (2013) Synthesis of novel peptides through Ugi-ligation and their anti-cancer activities. Amino Acids 45:975–981

    Article  CAS  Google Scholar 

  45. Abdi K, Nafisi S, Manouchehri F, Bonsaii M, Khalaj A (2012) Interaction of 5-Fluorouracil and its derivatives with bovine serum albumin. J Photochem Photobiol B 107:20–26

    Article  CAS  Google Scholar 

  46. Fani N, Bordbar AK, Ghayeb Y (2013) Spectroscopic, docking and molecular dynamics simulation studies on the interaction of two Schiff base complexes with human serum albumin. J Lumin 141:166–172

    Article  CAS  Google Scholar 

  47. Petitpas I, Bhattacharya AA, Twine S, East M, Curry S (2001) Crystal structure analysis of warfarin binding to human serum albumin. J Biol Chem 276:22804–22809

    Article  CAS  Google Scholar 

  48. Discovery Studio. Accelrys software Inc, San Diego, CA, 2009. http://www.accelrys.com.

  49. Politi A, Durdagi S, Moutevelis-Minakakis P, Kokotos G, Mavromoustakos T (2010) Development of accurate binding affinity predictions of novel rennin inhibitors through molecular docking studies. J Mol Graph Model 29:425–435

    Article  CAS  Google Scholar 

  50. Kerwin SM (2010) ChemBioOffice Ultra 2010 suite. J Am Chem Soc 132:2466–2467

    Article  CAS  Google Scholar 

  51. Momany FA, Rone RJ (1992) Validation of the general purpose QUANTA 3.2/CHARMm force field. J Comput Chem 13:888–900

    Article  CAS  Google Scholar 

  52. Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. J Comput Chem 31:455–461

    CAS  Google Scholar 

  53. Cosconati S, Forli S, Perryman AL, Harris R, Goodsell DS, Olson AJ (2010) Virtual screening with AutoDock: theory and practice. Expert Opin Drug Discov 5:597–607

    Article  CAS  Google Scholar 

  54. Forli S, Olson AJ (2012) A force field with discrete displaceable waters and desolvations entropy for hydrated ligand docking. J Med Chem 55:623–638

    Article  CAS  Google Scholar 

  55. Sanner MF, Huey R, Dallakyan S, Karnati S et al (2007) AutoDockTools, Version 1.4.5, The Scripps Research Institute, La Jolla, CA

  56. Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC, GROMACS: fast, flexible, and free. J Comput Chem 26:1701–1718.

  57. Lindorff-Larsen K, Piana S, Palmo K et al (2010) Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins 78:1950–1958

    CAS  Google Scholar 

  58. Pettersen EF, Goddard TD, Huang CC et al (2004) UCSF Chimera–a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612

    Article  CAS  Google Scholar 

  59. Pearlman DA, Case DA, Caldwell JW et al (1995) Amber, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 91:1–41

    Article  CAS  Google Scholar 

  60. Case DA, Cheatham TE, Darden T et al (2005) The amber biomolecular simulation programs. J Comput Chem 26:1668–1688

    Article  CAS  Google Scholar 

  61. Molecular Operating Environment (MOE) from chemical computing group Inc., Montreal, QC, Canada, 2013

  62. Berendsen HIC, Postma JPM, Van Gunsteren W, Hermans J (1981) Interaction models for water in relation to protein hydration. In: Pullman B (ed) Intermolecular forces. Reidel, Dordrecht, pp 331–342

    Chapter  Google Scholar 

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

    Article  CAS  Google Scholar 

  64. Darden T, York D, Pedersen L (1993) Particle Mesh Ewald-an N.Log(N) method for Ewald sums in large systems. J Chem Phys 98:10089–10092

    Article  CAS  Google Scholar 

  65. Dismer F, Hubbuch J (2010) 3D structure-based protein retention prediction for ion-exchange chromatography. J Chromatogr A 1217:1343–1353

    Article  CAS  Google Scholar 

  66. Honma T (2003) Recent advances in de novo design strategy for practical lead identification. Med Res Rev 23:606–632

    Article  CAS  Google Scholar 

  67. O’Carra P, Barry S, Griffin T (1974) Spacer arms in affinity chromatography: use of hydrophilic arms to control or eliminate non-biospecific adsorption effects. FEBS Lett 43:169–175

    Article  Google Scholar 

  68. Lowe CR (1977) The synthesis of several 8-substituted derivatives of adenosine 5′-monophosphate to study the effect of the nature of the spacer arm in affinity chromatography. Eur J Biochem 73:265–274. doi:10.1111/j.1432-1033.1977.tb11316.x

    Article  CAS  Google Scholar 

  69. Busini V, Moiani D, Moscatelli D, Zamolo L, Cavallotti C (2006) Investigation of the influence of spacer arm on the structural evolution of affinity ligands supported on agarose. J Phys Chem B 110:23564–23577

    Article  CAS  Google Scholar 

  70. Levy Y, Onuchic JN (2006) Water mediation in protein folding and molecular recognition. Annu Rev Biophys Biomol Struct 35:389–415. doi:10.1146/annurev.biophys.35.040405.102134

    Article  CAS  Google Scholar 

  71. Ni Y, Zhang X, Kokot S (2009) Spectrometric and voltammetric studies of the interaction between quercetin and bovine serum albumin using warfarin as site marker with the aid of chemometrics. Spectrochim Acta A 71:1865–1872

    Article  Google Scholar 

  72. Connolly MJ (1983) J Appl Cryst 16:548–558

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Authors and Affiliations

  1. Drug Design in Silico Laboratory, Chemistry Faculty, KN Toosi University of Technology, 15875-4416, 470 Mirdamad Ave. West, 19697, Tehran, Iran

    Elham Aghaee, Jahan B. Ghasemi & Firouzeh Manouchehri

  2. Peptide research Center, Chemistry Faculty, K N Toosi University of Technology, Tehran, Iran

    Saeed Balalaie

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  1. Elham Aghaee
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  2. Jahan B. Ghasemi
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  3. Firouzeh Manouchehri
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  4. Saeed Balalaie
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Correspondence to Jahan B. Ghasemi.

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Aghaee, E., Ghasemi, J.B., Manouchehri, F. et al. Combined docking, molecular dynamics simulations and spectroscopic studies for the rational design of a dipeptide ligand for affinity chromatography separation of human serum albumin. J Mol Model 20, 2446 (2014). https://doi.org/10.1007/s00894-014-2446-7

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