Skip to main content

Advertisement

SpringerLink
Log in

Distinct binding of cetirizine enantiomers to human serum albumin and the human histamine receptor H1

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

Cetirizine, a major metabolite of hydroxyzine, became a marketed second-generation H1 antihistamine that is orally active and has a rapid onset of action, long duration of effects and a very good safety record at recommended doses. The approved drug is a racemic mixture of (S)-cetirizine and (R)-cetirizine, the latter being the levorotary enantiomer that also exists in the market as a third-generation, non-sedating and highly selective antihistamine. Both enantiomers bind tightly to the human histamine H1 receptor (hH1R) and behave as inverse agonists but the affinity and residence time of (R)-cetirizine are greater than those of (S)-cetirizine. In blood plasma, cetirizine exists in the zwitterionic form and more than 90% of the circulating drug is bound to human serum albumin (HSA), which acts as an inactive reservoir. Independent X-ray crystallographic work has solved the structure of the hH1R:doxepin complex and has identified two drug-binding sites for cetirizine on equine serum albumin (ESA). Given this background, we decided to model a membrane-embedded hH1R in complex with either (R)- or (S)-cetirizine and also the complexes of both ESA and HSA with these two enantiomeric drugs to analyze possible differences in binding modes between enantiomers and also among targets. The ensuing molecular dynamics simulations in explicit solvent and additional computational chemistry calculations provided structural and energetic information about all of these complexes that is normally beyond current experimental possibilities. Overall, we found very good agreement between our binding energy estimates and extant biochemical and pharmacological evidence. A much higher degree of solvent exposure in the cetirizine-binding site(s) of HSA and ESA relative to the more occluded orthosteric binding site in hH1R is translated into larger positional fluctuations and considerably lower affinities for these two nonspecific targets. Whereas it is demonstrated that the two known pockets in ESA provide enough stability for cetirizine binding, only one such site does so in HSA due to a number of amino acid replacements. At the histamine-binding site in hH1R, the distinct interactions established between the phenyl and chlorophenyl moieties of the two enantiomers with the amino acids lining up the pocket and between their free carboxylates and Lys179 in the second extracellular loop account for the improved pharmacological profile of (R)-cetirizine.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Notes

  1. The amino acid superscripts refer to the GPCRDB numbering scheme that accounts for helix bulges and constrictions [17] (see ‘Methods’).

Abbreviations

BBB:

Blood–brain barrier

CBS1:

Cetirizine-binding site 1

CBS2:

Cetirizine-binding site 2

ECL:

Extracellular loop

ESA:

Equine serum albumin

HSA:

Human serum albumin

ICL:

Intracellular loop

MM-ISMSA:

Molecular mechanics implicit solvent model surface area

TFQ:

Tryptophan fluorescence quenching

TM:

Transmembrane

uMD:

Unbiased molecular dynamics

References

  1. Strolin Benedetti M, Whomsley R, Baltes E (2006) Involvement of enzymes other than CYPs in the oxidative metabolism of xenobiotics. Expert Opin Drug Metab Toxicol 2(6):895–921. https://doi.org/10.1517/17425255.2.6.895

    Article  CAS  PubMed  Google Scholar 

  2. Philpot EE (2000) Safety of second generation antihistamines. Allergy Asthma Proc 21(1):15–20

    Article  CAS  PubMed  Google Scholar 

  3. Curran MP, Scott LJ, Perry CM (2004) Cetirizine: a review of its use in allergic disorders. Drugs 64(5):523–561. https://doi.org/10.2165/00003495-200464050-00008

    Article  CAS  PubMed  Google Scholar 

  4. Maruko T, Nakahara T, Sakamoto K, Saito M, Sugimoto N, Takuwa Y, Ishii K (2005) Involvement of the bg subunits of G proteins in the cAMP response induced by stimulation of the histamine H1 receptor. Naunyn Schmiedebergs Arch Pharmacol 372(2):153–159. https://doi.org/10.1007/s00210-005-0001-x

    Article  CAS  PubMed  Google Scholar 

  5. Li H, Choe NH, Wright DT, Adler KB (1995) Histamine provokes turnover of inositol phospholipids in guinea pig and human airway epithelial cells via an H1-receptor/G protein-dependent mechanism. Am J Respir Cell Mol Biol 12(4):416–424. https://doi.org/10.1165/ajrcmb.12.4.7695921

    Article  CAS  PubMed  Google Scholar 

  6. Church DS, Church MK (2011) Pharmacology of antihistamines. World Allergy Organ J 4(Suppl 3):S22. https://doi.org/10.1097/1939-4551-4-s3-s22

    Article  PubMed  PubMed Central  Google Scholar 

  7. Leurs R, Church MK, Taglialatela M (2002) H1-antihistamines: inverse agonism, anti-inflammatory actions and cardiac effects. Clin Exp Allergy 32(4):489–498

    Article  CAS  PubMed  Google Scholar 

  8. Bakker RA, Wieland K, Timmerman H, Leurs R (2000) Constitutive activity of the histamine H1 receptor reveals inverse agonism of histamine H1 receptor antagonists. Eur J Pharmacol 387(1):R5–7

    Article  CAS  PubMed  Google Scholar 

  9. Pagliara A, Testa B, Carrupt PA, Jolliet P, Morin C, Morin D, Urien S, Tillement JP, Rihoux JP (1998) Molecular properties and pharmacokinetic behavior of cetirizine, a zwitterionic H1-receptor antagonist. J Med Chem 41(6):853–863. https://doi.org/10.1021/jm9704311

    Article  CAS  PubMed  Google Scholar 

  10. Gillard M, Van Der Perren C, Moguilevsky N, Massingham R, Chatelain P (2002) Binding characteristics of cetirizine and levocetirizine to human H1 histamine receptors: contribution of Lys191 and Thr194. Mol Pharmacol 61(2):391–399

    Article  CAS  PubMed  Google Scholar 

  11. Jongejan A, Bruysters M, Ballesteros JA, Haaksma E, Bakker RA, Pardo L, Leurs R (2005) Linking agonist binding to histamine H1 receptor activation. Nat Chem Biol 1(2):98–103. https://doi.org/10.1038/nchembio714

    Article  CAS  PubMed  Google Scholar 

  12. Moguilevsky N, Varsalona F, Guillaume JP, Noyer M, Gillard M, Daliers J, Henichart JP, Bollen A (1995) Pharmacological and functional characterisation of the wild-type and site-directed mutants of the human H1 histamine receptor stably expressed in CHO cells. J Recept Signal Transduct Res 15(1–4):91–102. https://doi.org/10.3109/10799899509045210

    Article  CAS  PubMed  Google Scholar 

  13. Wermuth CG, Ganellin CR, Lindberg P, Mitscher LA (1998) Glossary of terms used in medicinal chemistry (IUPAC Recommendations 1998). Pure Appl Chem 70(5):1129–1143. https://doi.org/10.1351/pac199870051129

    Article  CAS  Google Scholar 

  14. Shiroishi M, Kobayashi T (2017) Structural analysis of the histamine H1 receptor. Handb Exp Pharmacol 241:21–30. https://doi.org/10.1007/164_2016_10

    Article  CAS  PubMed  Google Scholar 

  15. Shimamura T, Shiroishi M, Weyand S, Tsujimoto H, Winter G, Katritch V, Abagyan R, Cherezov V, Liu W, Han GW, Kobayashi T, Stevens RC, Iwata S (2011) Structure of the human histamine H1 receptor complex with doxepin. Nature 475(7354):65–70. https://doi.org/10.1038/nature10236

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wieland K, Laak AM, Smit MJ, Kuhne R, Timmerman H, Leurs R (1999) Mutational analysis of the antagonist-binding site of the histamine H1 receptor. J Biol Chem 274(42):29994–30000

    Article  CAS  PubMed  Google Scholar 

  17. Isberg V, de Graaf C, Bortolato A, Cherezov V, Katritch V, Marshall FH, Mordalski S, Pin JP, Stevens RC, Vriend G, Gloriam DE (2015) Generic GPCR residue numbers—aligning topology maps while minding the gaps. Trends Pharmacol Sci 36(1):22–31. https://doi.org/10.1016/j.tips.2014.11.001

    Article  CAS  PubMed  Google Scholar 

  18. Kooistra AJ, Kuhne S, de Esch IJ, Leurs R, de Graaf C (2013) A structural chemogenomics analysis of aminergic GPCRs: lessons for histamine receptor ligand design. Br J Pharmacol 170(1):101–126. https://doi.org/10.1111/bph.12248

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Selvam B, Shamsi Z, Shukla D (2018) Universality of the sodium ion binding mechanism in class A G-protein-coupled receptors. Angew Chem Int Ed Engl 57(12):3048–3053. https://doi.org/10.1002/anie.201708889

    Article  CAS  PubMed  Google Scholar 

  20. Fasano M, Curry S, Terreno E, Galliano M, Fanali G, Narciso P, Notari S, Ascenzi P (2005) The extraordinary ligand binding properties of human serum albumin. IUBMB Life 57(12):787–796. https://doi.org/10.1080/15216540500404093

    Article  CAS  PubMed  Google Scholar 

  21. Sudlow G, Birkett DJ, Wade DN (1975) The characterization of two specific drug binding sites on human serum albumin. Mol Pharmacol 11(6):824–832

    CAS  PubMed  Google Scholar 

  22. Sudlow G, Birkett DJ, Wade DN (1976) Further characterization of specific drug binding sites on human serum albumin. Mol Pharmacol 12(6):1052–1061

    CAS  PubMed  Google Scholar 

  23. Ghuman J, Zunszain PA, Petitpas I, Bhattacharya AA, Otagiri M, Curry S (2005) Structural basis of the drug-binding specificity of human serum albumin. J Mol Biol 353(1):38–52. https://doi.org/10.1016/j.jmb.2005.07.075

    Article  CAS  PubMed  Google Scholar 

  24. He XM, Carter DC (1992) Atomic structure and chemistry of human serum albumin. Nature 358(6383):209–215. https://doi.org/10.1038/358209a0

    Article  CAS  PubMed  Google Scholar 

  25. Jensen RA (2001) Orthologs and paralogs—we need to get it right. Genome Biol 2(8):INTERACTIONS1002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Wang ZM, Ho JX, Ruble JR, Rose J, Ruker F, Ellenburg M, Murphy R, Click J, Soistman E, Wilkerson L (1830) Carter DC (2013) Structural studies of several clinically important oncology drugs in complex with human serum albumin. Biochim Biophys Acta 12:5356–5374. https://doi.org/10.1016/j.bbagen.2013.06.032

    Article  CAS  Google Scholar 

  27. Curry S (2009) Lessons from the crystallographic analysis of small molecule binding to human serum albumin. Drug Metab Pharmacokinet 24(4):342–357. https://doi.org/10.2133/dmpk.24.342

    Article  CAS  PubMed  Google Scholar 

  28. Handing KB, Shabalin IG, Szlachta K, Majorek KA, Minor W (2016) Crystal structure of equine serum albumin in complex with cetirizine reveals a novel drug binding site. Mol Immunol 71:143–151. https://doi.org/10.1016/j.molimm.2016.02.003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Liu X, Du Y, Sun W, Kou J, Yu B (2009) Study on the interaction of levocetirizine dihydrochloride with human serum albumin by molecular spectroscopy. Spectrochim Acta A 74(5):1189–1196. https://doi.org/10.1016/j.saa.2009.09.033

    Article  CAS  Google Scholar 

  30. Bree F, Thiault L, Gautiers G, Benedetti MS, Baltes E, Rihoux J-P, Tillement J-P (2002) Blood distribution of levocetirizine, a new non-sedating histamine H1-receptor antagonist, in humans. Fundam Clin Pharmacol 16(6):471–478. https://doi.org/10.1046/j.1472-8206.2002.00111.x

    Article  CAS  PubMed  Google Scholar 

  31. Hegde AH, Sandhya B, Kalanur SS, Seetharamappa J (2011) Binding mechanism of bioactive cetirizine hydrochloride to Sudlow’s site I of serum albumins. J Solution Chem 40(2):182–197. https://doi.org/10.1007/s10953-010-9640-8

    Article  CAS  Google Scholar 

  32. Majorek KA, Porebski PJ, Dayal A, Zimmerman MD, Jablonska K, Stewart AJ, Chruszcz M, Minor W (2012) Structural and immunologic characterization of bovine, horse, and rabbit serum albumins. Mol Immunol 52(3–4):174–182. https://doi.org/10.1016/j.molimm.2012.05.011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Sekula B, Zielinski K, Bujacz A (2013) Crystallographic studies of the complexes of bovine and equine serum albumin with 3,5-diiodosalicylic acid. Int J Biol Macromol 60:316–324. https://doi.org/10.1016/j.ijbiomac.2013.06.004

    Article  CAS  PubMed  Google Scholar 

  34. Czub MP, Venkataramany BS, Majorek KA, Handing KB, Porebski PJ, Beeram SR, Suh K, Woolfork AG, Hage DS, Shabalin IG, Minor W (2019) Testosterone meets albumin—the molecular mechanism of sex hormone transport by serum albumins. Chem Sci 10(6):1607–1618. https://doi.org/10.1039/c8sc04397c

    Article  CAS  PubMed  Google Scholar 

  35. Bhattacharya AA, Curry S, Franks NP (2000) Binding of the general anesthetics propofol and halothane to human serum albumin. High resolution crystal structures. J Biol Chem 275(49):38731–38738. https://doi.org/10.1074/jbc.M005460200

    Article  CAS  PubMed  Google Scholar 

  36. Czub MP, Handing KB, Venkataramany BS, Cooper DR, Shabalin IG, Minor W (2020) Albumin-based transport of nonsteroidal anti-inflammatory drugs in mammalian blood plasma. J Med Chem. https://doi.org/10.1021/acs.jmedchem.0c00225

    Article  PubMed  PubMed Central  Google Scholar 

  37. Geschwindner S, Ulander J, Johansson P (2015) Ligand binding thermodynamics in drug discovery: still a hot tip? J Med Chem 58(16):6321–6335. https://doi.org/10.1021/jm501511f

    Article  CAS  PubMed  Google Scholar 

  38. Setny P, Baron R, McCammon JA (2010) How can hydrophobic association be enthalpy driven? J Chem Theory Comput 6(9):2866–2871. https://doi.org/10.1021/ct1003077

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Chmielewska A, Konieczna L, Baczek T (2016) A novel two-step liquid-liquid extraction procedure combined with stationary phase immobilized human serum albumin for the chiral separation of cetirizine enantiomers along with M and P parabens. Molecules. https://doi.org/10.3390/molecules21121654

    Article  PubMed  PubMed Central  Google Scholar 

  40. Liu K, Watanabe E, Kokubo H (2017) Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations. J Comput Aided Mol Des 31(2):201–211. https://doi.org/10.1007/s10822-016-0005-2

    Article  CAS  PubMed  Google Scholar 

  41. McRobb FM, Negri A, Beuming T, Sherman W (2016) Molecular dynamics techniques for modeling G protein-coupled receptors. Curr Opin Pharmacol 30:69–75. https://doi.org/10.1016/j.coph.2016.07.001

    Article  CAS  PubMed  Google Scholar 

  42. Morreale A, Gil-Redondo R, Ortiz AR (2007) A new implicit solvent model for protein-ligand docking. Proteins 67(3):606–616. https://doi.org/10.1002/prot.21269

    Article  CAS  PubMed  Google Scholar 

  43. Klett J, Núñez-Salgado A, Dos Santos HG, Cortés-Cabrera Á, Perona A, Gil-Redondo R, Abia D, Gago F, Morreale A (2012) MM-ISMSA: an ultrafast and accurate scoring function for protein–protein docking. J Chem Theory Comput 8(9):3395–3408. https://doi.org/10.1021/ct300497z

    Article  CAS  PubMed  Google Scholar 

  44. Genheden S, Ryde U (2015) The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin Drug Discov 10(5):449–461. https://doi.org/10.1517/17460441.2015.1032936

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Steinbrecher T, Labahn A (2010) Towards accurate free energy calculations in ligand protein-binding studies. Curr Med Chem 17(8):767–785

    Article  CAS  PubMed  Google Scholar 

  46. Lenselink EB, Louvel J, Forti AF, van Veldhoven JPD, de Vries H, Mulder-Krieger T, McRobb FM, Negri A, Goose J, Abel R, van Vlijmen HWT, Wang L, Harder E, Sherman W, Adriaan IJP, Beuming T (2016) Predicting binding affinities for GPCR ligands using free-energy perturbation. ACS Omega 1(2):293–304. https://doi.org/10.1021/acsomega.6b00086

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Gumbart JC, Roux B, Chipot C (2013) Standard binding free energies from computer simulations: what is the best strategy? J Chem Theory Comput 9(1):794–802. https://doi.org/10.1021/ct3008099

    Article  CAS  PubMed  Google Scholar 

  48. Lee HS, Seok C, Im W (2015) Potential application of alchemical free energy simulations to discriminate GPCR ligand efficacy. J Chem Theory Comput 11(3):1255–1266. https://doi.org/10.1021/ct5008907

    Article  CAS  PubMed  Google Scholar 

  49. Salari R, Joseph T, Lohia R, Henin J, Brannigan G (2018) A streamlined, general approach for computing ligand binding free energies and its application to GPCR-bound cholesterol. J Chem Theory Comput 14(12):6560–6573. https://doi.org/10.1021/acs.jctc.8b00447

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Lipkowitz KB (2000) Atomistic modeling of enantioselective binding. Acc Chem Res 33(8):555–562

    Article  CAS  PubMed  Google Scholar 

  51. DeLano WL (2013) The PyMOL molecular graphics system, 1st.3 edn. Schrödinger, LLC., New York

    Google Scholar 

  52. Tetko IV, Gasteiger J, Todeschini R, Mauri A, Livingstone D, Ertl P, Palyulin VA, Radchenko EV, Zefirov NS, Makarenko AS, Tanchuk VY, Prokopenko VV (2005) Virtual computational chemistry laboratory–design and description. J Comput Aided Mol Des 19(6):453–463. https://doi.org/10.1007/s10822-005-8694-y

    Article  CAS  PubMed  Google Scholar 

  53. Marosi A, Kovacs Z, Beni S, Kokosi J, Noszal B (2009) Triprotic acid-base microequilibria and pharmacokinetic sequelae of cetirizine. Eur J Pharm Sci 37(3–4):321–328. https://doi.org/10.1016/j.ejps.2009.03.001

    Article  CAS  PubMed  Google Scholar 

  54. Brown ID, McMahon B (2002) CIF: the computer language of crystallography. Acta Crystallogr B 58(Pt 3 Pt 1):317–324

    Article  PubMed  Google Scholar 

  55. Moriarty NW, Grosse-Kunstleve RW, Adams PD (2009) electronic Ligand Builder and Optimization Workbench (eLBOW): a tool for ligand coordinate and restraint generation. Acta Crystallogr D 65(10):1074–1080. https://doi.org/10.1107/s0907444909029436

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery JA Jr, Peralta JE, Ogliaro F, Bearpark MJ, Heyd J, Brothers EN, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell AP, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam NJ, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, Dapprich S, Daniels AD, Farkas Ö, Foresman JB, Ortiz JV, Cioslowski J, Fox DJ (2009) Gaussian 09. Gaussian Inc, Wallingford, CT

    Google Scholar 

  57. Walker RC, Crowley MF, Case DA (2008) The implementation of a fast and accurate QM/MM potential method in AMBER. J Comput Chem 29(7):1019–1031. https://doi.org/10.1002/jcc.20857

    Article  CAS  PubMed  Google Scholar 

  58. Jakalian A, Jack DB, Bayly CI (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem 23(16):1623–1641. https://doi.org/10.1002/jcc.10128

    Article  CAS  PubMed  Google Scholar 

  59. Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C (2015) ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput 11(8):3696–3713. https://doi.org/10.1021/acs.jctc.5b00255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. de la Fuente JA, Manzanaro S, Martin MJ, de Quesada TG, Reymundo I, Luengo SM, Gago F (2003) Synthesis, activity, and molecular modeling studies of novel human aldose reductase inhibitors based on a marine natural product. J Med Chem 46(24):5208–5221. https://doi.org/10.1021/jm030957n

    Article  CAS  PubMed  Google Scholar 

  61. Adams PD, Afonine PV, Bunkoczi G, Chen VB, Davis IW, Echols N, Headd JJ, Hung LW, Kapral GJ, Grosse-Kunstleve RW, McCoy AJ, Moriarty NW, Oeffner R, Read RJ, Richardson DC, Richardson JS, Terwilliger TC, Zwart PH (2010) PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr D 66(Pt 2):213–221. https://doi.org/10.1107/S0907444909052925

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Adams PD, Afonine PV, Bunkoczi G, Chen VB, Echols N, Headd JJ, Hung LW, Jain S, Kapral GJ, Grosse Kunstleve RW, McCoy AJ, Moriarty NW, Oeffner RD, Read RJ, Richardson DC, Richardson JS, Terwilliger TC, Zwart PH (2011) The Phenix software for automated determination of macromolecular structures. Methods 55(1):94–106. https://doi.org/10.1016/j.ymeth.2011.07.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Emsley P, Lohkamp B, Scott WG, Cowtan K (2010) Features and development of Coot. Acta Crystallogr D 66(Pt 4):486–501. https://doi.org/10.1107/S0907444910007493

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Urzhumtsev A, Afonine PV, Van Benschoten AH, Fraser JS, Adams PD (2015) From deep TLS validation to ensembles of atomic models built from elemental motions. Acta Crystallogr D 71(Pt 8):1668–1683. https://doi.org/10.1107/S1399004715011426

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Holm L (2019) Benchmarking fold detection by DaliLite vol 5. Bioinformatics. https://doi.org/10.1093/bioinformatics/btz536

    Article  PubMed  Google Scholar 

  66. Roy A, Kucukural A, Zhang Y (2010) I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 5(4):725–738. https://doi.org/10.1038/nprot.2010.5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Zhang J, Yang J, Jang R, Zhang Y (2015) GPCR-I-TASSER: a hybrid approach to G protein-coupled receptor structure modeling and the application to the human genome. Structure 23(8):1538–1549. https://doi.org/10.1016/j.str.2015.06.007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Esguerra M, Siretskiy A, Bello X, Sallander J, Gutierrez-de-Teran H (2016) GPCR-ModSim: a comprehensive web based solution for modeling G-protein coupled receptors. Nucleic Acids Res 44(W1):W455–462. https://doi.org/10.1093/nar/gkw403

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Ballesteros JA, Weinstein H (1995) Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors. Methods Neurosci 25(19):366–428. https://doi.org/10.1016/s1043-9471(05)80049-7

    Article  CAS  Google Scholar 

  70. Pandy-Szekeres G, Munk C, Tsonkov TM, Mordalski S, Harpsoe K, Hauser AS, Bojarski AJ, Gloriam DE (2018) GPCRdb in 2018: adding GPCR structure models and ligands. Nucleic Acids Res 46(D1):D440–D446. https://doi.org/10.1093/nar/gkx1109

    Article  CAS  PubMed  Google Scholar 

  71. Vass M, Kooistra AJ, Verhoeven S, Gloriam D, de Esch IJP, de Graaf C (2018) A structural framework for GPCR chemogenomics: what's in a residue number? Methods Mol Biol 1705:73–113. https://doi.org/10.1007/978-1-4939-7465-8_4

    Article  CAS  PubMed  Google Scholar 

  72. Katritch V, Fenalti G, Abola EE, Roth BL, Cherezov V, Stevens RC (2014) Allosteric sodium in class A GPCR signaling. Trends Biochem Sci 39(5):233–244. https://doi.org/10.1016/j.tibs.2014.03.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Hishinuma S, Kosaka K, Akatsu C, Uesawa Y, Fukui H, Shoji M (2017) Asp73-dependent and -independent regulation of the affinity of ligands for human histamine H1 receptors by Na+. Biochem Pharmacol 128:46–54. https://doi.org/10.1016/j.bcp.2016.12.021

    Article  CAS  PubMed  Google Scholar 

  74. Liu W, Chun E, Thompson AA, Chubukov P, Xu F, Katritch V, Han GW, Roth CB, Heitman LH, Adriaan PIJ, Cherezov V, Stevens RC (2012) Structural basis for allosteric regulation of GPCRs by sodium ions. Science 337(6091):232–236. https://doi.org/10.1126/science.1219218

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Seeliger D, de Groot BL (2010) Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des 24(5):417–422. https://doi.org/10.1007/s10822-010-9352-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791. https://doi.org/10.1002/jcc.21256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Wu EL, Cheng X, Jo S, Rui H, Song KC, Davila-Contreras EM, Qi Y, Lee J, Monje-Galvan V, Venable RM, Klauda JB, Im W (2014) CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. J Comput Chem 35(27):1997–2004. https://doi.org/10.1002/jcc.23702

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Dickson CJ, Madej BD, Skjevik AA, Betz RM, Teigen K, Gould IR, Walker RC (2014) Lipid14: the AMBER lipid force field. J Chem Theory Comput 10(2):865–879. https://doi.org/10.1021/ct4010307

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Salomon-Ferrer R, Götz 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  PubMed  Google Scholar 

  80. 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(12):10089–10092. https://doi.org/10.1063/1.464397

    Article  CAS  Google Scholar 

  81. Brunger AT, Adams PD (2002) Molecular dynamics applied to X-ray structure refinement. Acc Chem Res 35(6):404–412

    Article  CAS  PubMed  Google Scholar 

  82. Roe DR, Cheatham TE 3rd (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  PubMed  Google Scholar 

  83. Salgado A, Tatunashvili E, Gogolashvili A, Chankvetadze B, Gago F (2017) Structural rationale for the chiral separation and migration order reversal of clenpenterol enantiomers in capillary electrophoresis using two different b-cyclodextrins. Phys Chem Chem Phys 19(41):27935–27939. https://doi.org/10.1039/c7cp04761d

    Article  CAS  PubMed  Google Scholar 

  84. Sánchez-Murcia PA, Cortés-Cabrera A, Gago F (2017) Structural rationale for the cross-resistance of tumor cells bearing the A399V variant of elongation factor eEF1A1 to the structurally unrelated didemnin B, ternatin, nannocystin A and ansatrienin B. J Comput Aided Mol Des 31(10):915–928. https://doi.org/10.1007/s10822-017-0066-x

    Article  CAS  PubMed  Google Scholar 

  85. Desiraju GR (2002) Hydrogen bridges in crystal engineering: interactions without borders. Acc Chem Res 35(7):565–573. https://doi.org/10.1021/ar010054t

    Article  CAS  PubMed  Google Scholar 

  86. Burnley BT, Afonine PV, Adams PD, Gros P (2012) Modelling dynamics in protein crystal structures by ensemble refinement. Elife 1:e00311. https://doi.org/10.7554/eLife.00311

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Castellanos MM, Colina CM (2013) Molecular dynamics simulations of human serum albumin and role of disulfide bonds. J Phys Chem B 117(40):11895–11905. https://doi.org/10.1021/jp402994r

    Article  CAS  PubMed  Google Scholar 

  88. ter Laak AM, Timmerman H, Leurs R, Nederkoorn PH, Smit MJ, Donne-Op den Kelder GM (1995) Modelling and mutation studies on the histamine H1-receptor agonist binding site reveal different binding modes for H1-agonists: Asp116 (TM3) has a constitutive role in receptor stimulation. J Comput Aided Mol Des 9(4):319–330

    Article  PubMed  Google Scholar 

  89. Wittmann HJ, Seifert R, Strasser A (2009) Contribution of binding enthalpy and entropy to affinity of antagonist and agonist binding at human and guinea pig histamine H1-receptor. Mol Pharmacol 76(1):25–37. https://doi.org/10.1124/mol.109.055384

    Article  CAS  PubMed  Google Scholar 

  90. Nguyen CN, Cruz A, Gilson MK, Kurtzman T (2014) Thermodynamics of water in an enzyme active site: grid-based hydration analysis of coagulation factor Xa. J Chem Theory Comput 10(7):2769–2780. https://doi.org/10.1021/ct401110x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Klebe G (2019) Broad-scale analysis of thermodynamic signatures in medicinal chemistry: are enthalpy-favored binders the better development option? Drug Discov Today 24(4):943–948. https://doi.org/10.1016/j.drudis.2019.01.014

    Article  CAS  PubMed  Google Scholar 

  92. Schmidtke P, Luque FJ, Murray JB, Barril X (2011) Shielded hydrogen bonds as structural determinants of binding kinetics: application in drug design. J Am Chem Soc 133(46):18903–18910. https://doi.org/10.1021/ja207494u

    Article  CAS  PubMed  Google Scholar 

  93. Ruiz-Carmona S, Schmidtke P, Luque FJ, Baker L, Matassova N, Davis B, Roughley S, Murray J, Hubbard R, Barril X (2017) Dynamic undocking and the quasi-bound state as tools for drug discovery. Nat Chem 9(3):201–206. https://doi.org/10.1038/nchem.2660

    Article  CAS  PubMed  Google Scholar 

  94. Krimmer SG, Cramer J, Betz M, Fridh V, Karlsson R, Heine A, Klebe G (2016) Rational design of thermodynamic and kinetic binding profiles by optimizing surface water networks coating protein-bound ligands. J Med Chem 59(23):10530–10548. https://doi.org/10.1021/acs.jmedchem.6b00998

    Article  CAS  PubMed  Google Scholar 

  95. Ross GA, Morris GM, Biggin PC (2012) Rapid and accurate prediction and scoring of water molecules in protein binding sites. PLoS ONE 7(3):e32036. https://doi.org/10.1371/journal.pone.0032036

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Cui G, Swails JM, Manas ES (2013) SPAM: a simple approach for profiling bound water molecules. J Chem Theory Comput 9(12):5539–5549. https://doi.org/10.1021/ct400711g

    Article  CAS  PubMed  Google Scholar 

  97. Nilsson LM, Thomas WE, Sokurenko EV, Vogel V (2008) Beyond induced-fit receptor-ligand interactions: structural changes that can significantly extend bond lifetimes. Structure 16(7):1047–1058. https://doi.org/10.1016/j.str.2008.03.012

    Article  CAS  PubMed  Google Scholar 

  98. Cramer J, Krimmer SG, Fridh V, Wulsdorf T, Karlsson R, Heine A, Klebe G (2017) Elucidating the origin of long residence time binding for inhibitors of the metalloprotease thermolysin. ACS Chem Biol 12(1):225–233. https://doi.org/10.1021/acschembio.6b00979

    Article  CAS  PubMed  Google Scholar 

  99. Yau MQ, Emtage AL, Chan NJY, Doughty SW, Loo JSE (2019) Evaluating the performance of MM/PBSA for binding affinity prediction using class A GPCR crystal structures. J Comput Aided Mol Des 33(5):487–496. https://doi.org/10.1007/s10822-019-00201-3

    Article  CAS  PubMed  Google Scholar 

  100. Cramer J, Krimmer SG, Heine A, Klebe G (2017) Paying the price of desolvation in solvent-exposed protein pockets: impact of distal solubilizing groups on affinity and binding thermodynamics in a series of thermolysin inhibitors. J Med Chem 60(13):5791–5799. https://doi.org/10.1021/acs.jmedchem.7b00490

    Article  CAS  PubMed  Google Scholar 

  101. Hantschel O, Rix U, Superti-Furga G (2008) Target spectrum of the BCR-ABL inhibitors imatinib, nilotinib and dasatinib. Leuk Lymphoma 49(4):615–619. https://doi.org/10.1080/10428190801896103

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Financial support from the Spanish Ministry of Science and Innovation through grant SAF2015-64629-C2-2-R to F.G. is gratefully acknowledged.

Author information

Author notes

  1. Almudena Perona

    Present address: Departamento de Química en Ciencias Farmacéuticas, Facultad de Farmacia, Ciudad Universitaria, Plaza de Ramón y Cajal, 28040, Madrid, Spain

Authors and Affiliations

  1. Universidad Europea de Madrid, Urbanización El Bosque, c/ Tajo s/n, 28670, Villaviciosa de Odón, Madrid, Spain

    Almudena Perona & M. Piedad Ros

  2. Area of Pharmacology, Department of Biomedical Sciences and “Unidad Asociada IQM-CSIC”, School of Medicine and Health Sciences, University of Alcalá, 28805, Alcalá de Henares, Madrid, Spain

    Alberto Mills & Federico Gago

  3. Repsol Technology Lab, c/ Agustín de Betancourt s/n, 28935, Móstoles, Madrid, Spain

    Antonio Morreale

Authors
  1. Almudena Perona
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Piedad Ros
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alberto Mills
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Antonio Morreale
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Federico Gago
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Participated in research design: AP, AM, and FG. Conducted experiments: MPR, AP, AM, AM, and FG. Performed data analysis: AP, AM, and FG. Wrote or contributed to the writing of the manuscript: MPR, AP, AM, AM, and FG.

Corresponding author

Correspondence to Federico Gago.

Additional information

This work is dedicated to Prof. Gerhard Klebe (University of Marburg, Germany), on occasion of his retirement, in recognition of his outstanding and inspiring scientific contributions.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 9488 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Perona, A., Ros, M.P., Mills, A. et al. Distinct binding of cetirizine enantiomers to human serum albumin and the human histamine receptor H1. J Comput Aided Mol Des 34, 1045–1062 (2020). https://doi.org/10.1007/s10822-020-00328-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-020-00328-8

Keywords

Search

Navigation