Abstract
Retinol binding protein (RBP) and an engineered lipocalin, DigA16, have been studied using molecular dynamics simulations. Special emphasis has been placed on explaining the ligand–receptor interaction in RBP–retinol and DigA16–digoxigenin complexes, and steered molecular dynamics simulations of 10–20 ns have been carried out for the ligand expulsion process. Digoxigenin is bound deep inside the cavity of DigA16 and forms several stable hydrogen bonds in addition to the hydrophobic van der Waals interaction with the aromatic side-chains. Four crystalline water molecules inside the ligand-binding cavity remain trapped during the simulations. The strongly hydrophobic receptor site of RBP differs considerably from DigA16, and the main source of ligand attraction comes from the phenyl side-chains. The hydrogen bonds between digoxigenin and DigA16 cause the rupture forces on ligand removal in DigA16 and RBP to differ. The mutated DigA16 residues contribute approximately one-half of the digoxigenin interaction energy with DigA16 and, of these, the energetically most important are residues His35, Arg58, Ser87, Tyr88, and Phe114. Potential “sensor loops” were found for both receptors. These are the outlier loops between residues 114–121 and 63–67 for DigA16 and RBP, respectively, and they are located near the entrance of the ligand-binding cavity. Especially, the residues Glu119 (DigA16) and Leu64 (RBP) are critical for sensing. The ligand binding energies have been estimated based on the linear response approximation of binding affinity by using a previous parametrization for retinoids and RBP.
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References
Åqvist J, Marelius J (2001) The linear interaction energy method for predicting ligand binding free energies. Comb Chem High Throughput Screen 4:613–626
Åqvist J, Medina C, Samuelsson J-E (1994) New method for predicting binding-affinity in computer-aided drug design. Protein Eng 7:385–391
Åqvist J, Luzhkov VB, Brandsdal BO (2002) Ligand binding affinities from MD simulations. Acc Chem Res 35:358–365. doi:10.1021/ar010014p
Beaufays J et al (2008) Ir-LBP, an Ixodes ricinus tick salivary LTB4-binding lipocalin, interferes with host neutrophil function. PLoS ONE. doi:10.1371/journal.pone.0003987
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The Protein Data Bank. Nucleic Acids Research 28:235–242. (http://www.pdb.org)
Besler BH, Merz KM Jr, Kollman PA (1990) Atomic charges derived from semiempirical methods. J Comp Chem 11:431–439
Breustedt DA, Schönfeld DL, Skerra A (2006) Comparative ligand-binding analysis of ten human lipocalins. Biochim Biophys Acta 1764:161–173. doi:10.1016/j.bbapap.2005.12.006
Calderone V, Berni R, Zanotti G (2003) High-resolution structures of retinol-binding protein in complex with retinol: pH-induced protein structural changes in the crystal state. J Mol Biol 329:841–850. doi:10.1016/S0022-2836(03)00468-6
Chau P-L (2004) Water movement during ligand unbinding from receptor site. Biophys J 87:121–128. doi:10.1529/biophysj.103.036467
Cogan U, Kopelman M, Mokady S, Shinitzky M (1976) Binding affinities of retinol and related compounds to retinol binding proteins. Eur J Biochem 65:71–78
Cowan SW, Newcomer ME, Jones TA (1990) Crystallographic refinement of human serum retinol binding protein at 2 Å resolution. Proteins Struct Funct Genet 8:44–61. doi:10.1002/prot.340080108
Duan Y et al (2003) A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J Comput Chem 24:1999–2012. doi:10.1002/jcc.10349
Flower DR (1994) The lipocalin protein family: a role in cell regulation. FEBS Lett 354:7–11
Flower DR (1996) The lipocalin protein family: structure and function. Biochem J 318:1–14
Frisch MJ et al (2004) Gaussian03, Revision D. 02. Gaussian Inc., Wallingford CT
Gunnerson KN, Pereverzev YV, Prezhdo OV (2009) Atomistic simulation combined with analytic theory to study the response of the P-selectin/PSGL-1 complex to an external force. J Phys Chem B 113:2090–2100. doi:10.1021/jp803955u
Hansson T, Marelius J, Åqvist J (1998) Ligand binding affinity prediction by linear interaction energy methods. J Comput Aided Mol Design 12:27–35
Humphrey W, Dalke A, Schulten K (1996) VMD—Visual Molecular Dynamics. J Mol Graphics 14:33–38
Hytönen VP, Vogel V (2008) How force might activate talin’s vinculin binding sites: SMD reveals a structural mechanism. PLoS Comput Biol. doi:10.1371/journal.pcbi.0040024
Inoue K, Yagi N, Urade Y, Inui T (2009) Compact Packing of Lipocalin-type Prostaglandin D Synthase Induced by Binding of Lipophilic Ligands. J Biochem 145:169–175
Isralewitz B, Baudry J, Gullingsrud J, Kosztin D, Schulten K (2001) Steered molecular dynamics investigations of protein function. J Mol Graphics Modell 19:13–25
Isralewitz B, Gao M, Schulten K (2001) Steered molecular dynamics and mechanical functions of proteins. Curr Opin Struc Biol 11:224–230
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Phys Rev Lett 78:2690–2693
Jarzynski C (1997) Equilibrium free-energy differences from nonequilibrium measurements: A master-equation approach. Phys Rev E 56:5018–5035
Jeffrey PD, Strong RK, Sieker LC, Chang CY, Campbell RL, Petsko GA, Haber E, Margolies MN, Sheriff S (1993) 26-10 Fab-digoxin complex: affinity and specificity due to surface complementarity. Proc Natl Acad Sci USA 90:10310–10314
Jeffrey PD, Schildbach JF, Chang CY, Kussie PH, Margolies MN, Sheriff S (1995) Structure and specificity of the anti-digoxin antibody 40–50. J Mol Biol 248:344–360
Korndörfer IP, Schlehuber S, Skerra A (2003) Structural mechanism of specific ligand recognition by a lipocalin tailored for the complexation of digoxigenin. J Mol Biol 330:385–396. doi:10.1016/S0022-2836(03)00573-4
Meijer EJ, Sprik M (1998) Ab initio molecular dynamics study of the reaction of water with formaldehyde in sulfuric acid solution. J Am Chem Soc 120:6345–6355
Mills JL, Liu G, Skerra A, Szyperski T (2009) NMR Structure and Dynamics of the Engineered Fluorescein-Binding Lipocalin FluA Reveal Rigidification of β-Barrel and Variable Loops upon Enthalpy-Driven Ligand Binding. Biochemistry 48:7411–7419. doi:10.1021/bi900535j
Murshudov GN, Vagin AA, Dodson EJ (1997) Refinement of Macromolecular Structures by the Maximum-Likelihood Method. Acta Cryst D 53:240–255
Newcomer ME, Jones TA, Åqvist J, Sundelin J, Eriksson U, Rask L, Peterson PA (1984) The three-dimensional structure of retinol-binding protein. EMBO J 3:1451–1454
Niu C et al (2009) Dynamic mechanism of E2020 binding to acetylcholinesterase: a steered molecular dynamics simulation. J Phys Chem B 109:23730–23738. doi:10.1021/jp0552877
Park S, Schulten K (2004) Calculating potentials of mean force from steered molecular dynamics simulations. J Chem Phys 120:5946–5961. doi:10.1063/1.1651473
Peräkylä M (2009) Ligand unbinding pathways from the vitamin D receptor studied by molecular dynamics simulations. Eur Biophys J 38:185–198. doi:10.1007/s00249-008-0369-x
Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kalé L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comp Chem 26:1781–1802. doi:10.1002/jcc.20289
Schlehuber S, Skerra A (2005) Lipocalins in drug discovery: from natural ligand-binding proteins to ‘anticalins’. Drug Discovery Today 10:23–33
Schlehuber S, Beste B, Skerra A (2000) A novel type of receptor protein, based on the lipocalin scaffold, with specificity for digoxigenin. J Mol Biol 297:1105–1120
Schlehuber S, Skerra A (2002) Tuning ligand affinity, specificity, and folding stability of an engineered lipocalin variant—a so-called ‘anticalin’—using a molecular random approach. Biophys Chem 96:213–228
Schönfeld D et al (2009) An engineered lipocalin specific for CTLA-4 reveals a combining site with structural and conformational features similar to antibodies. Proc Natl Acad Sci USA 106:8198–8203
Singh RP, Brooks BR, Klauda JB (2008) Binding and release of cholesterol in the Osh4 protein of yeast. Proteins 75:468–477. doi:10.1002/prot.22263
Singh UC, Kollman PA (1984) An approach to computing electrostatic charges for molecules. J Comp Chem 5:129–145
Skerra A (2007) Alternative non-antibody scaffolds for molecular recognition. Curr Opin Biotechnol 18:295–304. doi:10.1016/j.copbio.2007.04.010
Skerra A (2008) Alternative binding proteins: Anticalins—harnessing the structural plasticity of the lipocalin pocket to engineer novel binding activities. FEBS J 275:2677–2683. doi:10.1111/j.1742-4658.2008.06439.x
Sprik M, Ciccotti G (1998) Free energy from constrained molecular dynamics. J Chem Phys 109:7737–7744
van Gunsteren WF, Berendsen HJC (1987) Groningen molecular simulation (GROMOS) library manual. Biomos, Groningen
Wang W, Wang J, Kollman PA (1999) What determines the van der Waals coefficient b in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations? Proteins Struct Funct Genet 34:395–402
Zanotti G, Berni R, Monaco HL (1993) Crystal structure of liganded and unliganded forms of bovine plasma retinol-binding protein. J Biol Chem 268:10728–10738
Zanotti G, Panzalorto M, Marcato A, Malpeli G, Folli C, Berni R (1998) Structure of pig plasma retinol-binding protein at 1.65 Å resolution. Acta Crystallog D 54:1049–1052
Zanotti G, Calderone V, Beda M, Malpeli G, Folli C, Berni R (2001) Structure of chicken plasma retinol-binding protein. Biochim Biophys Acta 1550:64–69
Zwanzig RW (1954) High-temperature equation of state by a perturbation method. 1. nonpolar gases. J Chem Phys 22:1420–1426
Acknowledgments
The parallel simulations were performed on the SGI/Altix platform at the Nanoscience Center of the University of Jyväskylä. The charge calculations with Gaussian03 were performed on the HP CP4000 BL platform at CSC in Espoo, Finland. All molecular visualizations were done with Visual Molecular Dynamics (Humphrey et al. 1996). We thank A. Skerra for discussions and providing the DigA16 structure (1LKE) with an added middle loop (residues 118–122), O. Pentikäinen for instructions with the simulation setups, and R.O. Jones for critical reading of the manuscript.
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Kalikka, J., Akola, J. Steered molecular dynamics simulations of ligand–receptor interaction in lipocalins. Eur Biophys J 40, 181–194 (2011). https://doi.org/10.1007/s00249-010-0638-3
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DOI: https://doi.org/10.1007/s00249-010-0638-3