Journal of Biomolecular NMR

, Volume 67, Issue 1, pp 35–49 | Cite as

High quality NMR structures: a new force field with implicit water and membrane solvation for Xplor-NIH

  • Ye Tian
  • Charles D. Schwieters
  • Stanley J. Opella
  • Francesca M. Marassi
Article

Abstract

Structure determination of proteins by NMR is unique in its ability to measure restraints, very accurately, in environments and under conditions that closely mimic those encountered in vivo. For example, advances in solid-state NMR methods enable structure determination of membrane proteins in detergent-free lipid bilayers, and of large soluble proteins prepared by sedimentation, while parallel advances in solution NMR methods and optimization of detergent-free lipid nanodiscs are rapidly pushing the envelope of the size limit for both soluble and membrane proteins. These experimental advantages, however, are partially squandered during structure calculation, because the commonly used force fields are purely repulsive and neglect solvation, Van der Waals forces and electrostatic energy. Here we describe a new force field, and updated energy functions, for protein structure calculations with EEFx implicit solvation, electrostatics, and Van der Waals Lennard-Jones forces, in the widely used program Xplor-NIH. The new force field is based primarily on CHARMM22, facilitating calculations with a wider range of biomolecules. The new EEFx energy function has been rewritten to enable OpenMP parallelism, and optimized to enhance computation efficiency. It implements solvation, electrostatics, and Van der Waals energy terms together, thus ensuring more consistent and efficient computation of the complete nonbonded energy lists. Updates in the related python module allow detailed analysis of the interaction energies and associated parameters. The new force field and energy function work with both soluble proteins and membrane proteins, including those with cofactors or engineered tags, and are very effective in situations where there are sparse experimental restraints. Results obtained for NMR-restrained calculations with a set of five soluble proteins and five membrane proteins show that structures calculated with EEFx have significant improvements in accuracy, precision, and conformation, and that structure refinement can be obtained by short relaxation with EEFx to obtain improvements in these key metrics. These developments broaden the range of biomolecular structures that can be calculated with high fidelity from NMR restraints.

Keywords

Structure calculation Implicit solvent Membrane protein Eefx Force field 

References

  1. Abagyan RA, Totrov MM (1997) Contact area difference (CAD): a robust measure to evaluate accuracy of protein models. J Mol Biol 268:678–685. doi:10.1006/jmbi.1997.0994 CrossRefGoogle Scholar
  2. Baker NA (2005) Improving implicit solvent simulations: a Poisson-centric view. Curr Opin Struct Biol 15:137–143. doi:10.1016/j.sbi.2005.02.001 CrossRefGoogle Scholar
  3. Bashford D, Case DA (2000) Generalized born models of macromolecular solvation effects. Annu Rev Phys Chem 51:129–152. doi:10.1146/annurev.physchem.51.1.129 ADSCrossRefGoogle Scholar
  4. Bermejo GA, Clore GM, Schwieters CD (2012) Smooth statistical torsion angle potential derived from a large conformational database via adaptive kernel density estimation improves the quality of NMR protein structures. Protein Sci 21:1824–1836. doi:10.1002/pro.2163 CrossRefGoogle Scholar
  5. Bermejo GA, Clore GM, Schwieters CD (2016) Improving NMR Structures of RNA. Structure 24:806–815. doi:10.1016/j.str.2016.03.007 CrossRefGoogle Scholar
  6. Bertini I, Case DA, Ferella L, Giachetti A, Rosato A (2011) A Grid-enabled web portal for NMR structure refinement with AMBER. Bioinformatics 27:2384–2390. doi:10.1093/bioinformatics/btr415 CrossRefGoogle Scholar
  7. Brooks BR et al (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30:1545–1614. doi:10.1002/jcc.21287 CrossRefGoogle Scholar
  8. Brunger AT (1992) X-PLOR, Version 3.1: a system for X-ray crystallography and NMR. Yale University Press, New HavenGoogle Scholar
  9. Brunger AT et al (1998) Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Crystallogr D Biol Crystallogr 54(Pt 5):905–921CrossRefGoogle Scholar
  10. Cai M et al (1998) Solution structure of the cellular factor BAF responsible for protecting retroviral DNA from autointegration. Nat Struct Biol 5:903–909. doi:10.1038/2345 CrossRefGoogle Scholar
  11. Case DA et al (2005) The Amber biomolecular simulation programs. J Comput Chem 26:1668–1688. doi:10.1002/jcc.20290 CrossRefGoogle Scholar
  12. Chen J, Brooks CL 3rd, Khandogin J (2008) Recent advances in implicit solvent-based methods for biomolecular simulations. Curr Opin Struct Biol 18:140–148. doi:10.1016/j.sbi.2008.01.003 CrossRefGoogle Scholar
  13. Chen J, Im W, Brooks CL 3rd (2004) Refinement of NMR structures using implicit solvent and advanced sampling techniques. J Am Chem Soc 126:16038–16047. doi:10.1021/ja047624f CrossRefGoogle Scholar
  14. Chen J, Won HS, Im W, Dyson HJ, Brooks CL 3rd (2005) Generation of native-like protein structures from limited NMR data, modern force fields and advanced conformational sampling. J Biomol NMR 31:59–64. doi:10.1007/s10858-004-6056-z CrossRefGoogle Scholar
  15. Chen VB et al (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D Biol Crystallogr 66:12–21. doi:10.1107/S0907444909042073 CrossRefGoogle Scholar
  16. Cheng X, Im W (2012) NMR observable-based structure refinement of DAP12-NKG2C activating immunoreceptor complex in explicit membranes. Biophys J 102:L27–L29. doi:10.1016/j.bpj.2012.03.002 CrossRefGoogle Scholar
  17. Cheng X, Jo S, Marassi FM, Im W (2013) NMR-based simulation studies of Pf1 coat protein in explicit membranes. Biophys J 105:691–698. doi:10.1016/j.bpj.2013.06.040 CrossRefGoogle Scholar
  18. Clore GM (2015) Practical aspects of paramagnetic relaxation enhancement in biological macromolecules. Methods Enzymol 564:485–497. doi:10.1016/bs.mie.2015.06.032 CrossRefGoogle Scholar
  19. Clore GM, Garrett DS (1999) R-factor, free R, and complete cross-validation for dipolar coupling refinement of NMR structures. J Am Chem Soc 121:9008–9012CrossRefGoogle Scholar
  20. Clore GM, Gronenborn AM (1989) Determination of three-dimensional structures of proteins and nucleic acids in solution by nuclear magnetic resonance spectroscopy. Crit Rev Biochem Mol Biol 24:479–564CrossRefGoogle Scholar
  21. Clore GM, Gronenborn AM (1998) New methods of structure refinement for macromolecular structure determination by NMR. Proc Natl Acad Sci USA 95:5891–5898ADSCrossRefGoogle Scholar
  22. Cornilescu G et al (2016) Structural analysis of multi-helical RNAs by NMR-SAXS/WAXS: application to the U4/U6 di-snRNA. J Mol Biol 428:777–789. doi:10.1016/j.jmb.2015.11.026 CrossRefGoogle Scholar
  23. Cross TA, Ekanayake V, Paulino J, Wright A (2014) Solid state NMR: the essential technology for helical membrane protein structural characterization. J Magn Reson 239:100–109. doi:10.1016/j.jmr.2013.12.006 ADSCrossRefGoogle Scholar
  24. Das R, Baker D (2008) Macromolecular modeling with rosetta. Annu Rev Biochem 77:363–382. doi:10.1146/annurev.biochem.77.062906.171838 CrossRefGoogle Scholar
  25. Das N, Dai J, Hung I, Rajagopalan MR, Zhou HX, Cross TA (2015) Structure of CrgA, a cell division structural and regulatory protein from Mycobacterium tuberculosis, in lipid bilayers. Proc Natl Acad Sci USA 112:E119–E126. doi:10.1073/pnas.1415908112 ADSCrossRefGoogle Scholar
  26. Davis IW et al (2007) MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Res 35:W375–W383. doi:10.1093/nar/gkm216 ADSCrossRefGoogle Scholar
  27. DeLano WL (2005) PyMol.Google Scholar
  28. Dror RO, Dirks RM, Grossman JP, Xu H, Shaw DE (2012) Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys 41:429–452. doi:10.1146/annurev-biophys-042910-155245 CrossRefGoogle Scholar
  29. Feeney J, Birdsall B, Kovalevskaya NV, Smurnyy YD, Navarro Peran EM, Polshakov VI (2011) NMR structures of apo L. casei dihydrofolate reductase and its complexes with trimethoprim and NADPH: contributions to positive cooperative binding from ligand-induced refolding, conformational changes, and interligand hydrophobic interactions. Biochemistry 50:3609–3620. doi:10.1021/bi200067t CrossRefGoogle Scholar
  30. Feig M, Brooks CL 3rd (2004) Recent advances in the development and application of implicit solvent models in biomolecule simulations. Curr Opin Struct Biol 14:217–224. doi:10.1016/j.sbi.2004.03.009 CrossRefGoogle Scholar
  31. Garrett DS, Seok YJ, Liao DI, Peterkofsky A, Gronenborn AM, Clore GM (1997) Solution structure of the 30 kDa N-terminal domain of enzyme I of the Escherichia coli phosphoenolpyruvate: sugar phosphotransferase system by multidimensional NMR. BioChemistry 36:2517–2530. doi:10.1021/bi962924y CrossRefGoogle Scholar
  32. Garrett DS, Seok YJ, Peterkofsky A, Gronenborn AM, Clore GM (1999) Solution structure of the 40,000 Mr phosphoryl transfer complex between the N-terminal domain of enzyme I and HPr. Nat Struct Biol 6:166–173. doi:10.1038/5854 CrossRefGoogle Scholar
  33. Gronenborn AM, Clore GM (1995) Structures of protein complexes by multidimensional heteronuclear magnetic resonance spectroscopy. Crit Rev Biochem Mol Biol 30:351–385. doi:10.3109/10409239509083489 CrossRefGoogle Scholar
  34. Gronenborn AM, Filpula DR, Essig NZ, Achari A, Whitlow M, Wingfield PT, Clore GM (1991) A novel, highly stable fold of the immunoglobulin binding domain of streptococcal protein G. Science 253:657–661ADSCrossRefGoogle Scholar
  35. Guntert P (1998) Structure calculation of biological macromolecules from NMR data. Q Rev Biophys 31:145–237CrossRefGoogle Scholar
  36. Guntert P (2004) Automated NMR structure calculation with CYANA Methods Mol Biol 278:353–378. doi:10.1385/1-59259-809-9:353 Google Scholar
  37. Guntert P, Mumenthaler C, Wuthrich K (1997) Torsion angle dynamics for NMR structure calculation with the new program DYANA. J Mol Biol 273:283–298. doi:10.1006/jmbi.1997.1284 CrossRefGoogle Scholar
  38. Hagn F, Etzkorn M, Raschle T, Wagner G (2013) Optimized phospholipid bilayer nanodiscs facilitate high-resolution structure determination of membrane proteins. J Am Chem Soc 135:1919–1925. doi:10.1021/ja310901f CrossRefGoogle Scholar
  39. Im W, Brooks CL 3rd (2004) De novo folding of membrane proteins: an exploration of the structure and NMR properties of the fd coat protein. J Mol Biol 337:513–519. doi:10.1016/j.jmb.2004.01.045 CrossRefGoogle Scholar
  40. Jureka AS, Kleinpeter AB, Cornilescu G, Cornilescu CC, Petit CM (2015) Structural basis for a novel interaction between the NS1 protein derived from the 1918 influenza virus and RIG-I. Structure 23:2001–2010. doi:10.1016/j.str.2015.08.007 CrossRefGoogle Scholar
  41. Kuhlman B, Baker D (2000) Native protein sequences are close to optimal for their structures. Proc Natl Acad Sci USA 97:10383–10388ADSCrossRefGoogle Scholar
  42. Kuszewski J, Gronenborn AM, Clore GM (1999) Improving the packing and accuracy of NMR structures with a pseudopotential for the radius of gyration. J Am Chem Soc 121:2337–2338CrossRefGoogle Scholar
  43. Lazaridis T (2003) Effective energy function for proteins in lipid membranes. Proteins 52:176–192. doi:10.1002/prot.10410 CrossRefGoogle Scholar
  44. Lazaridis T, Karplus M (1999) Effective energy function for proteins in solution. Proteins 35:133–152. doi:10.1002/(SICI)1097-0134(19990501)35:2<133::AID-PROT1>3.0.CO;2-N CrossRefGoogle Scholar
  45. Lee W, Petit CM, Cornilescu G, Stark JL, Markley JL (2016) The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data. J Biomol NMR 65:51–57. doi:10.1007/s10858-016-0036-y CrossRefGoogle Scholar
  46. Linge JP, Nilges M (1999) Influence of non-bonded parameters on the quality of NMR structures: a new force field for NMR structure calculation. J Biomol NMR 13:51–59CrossRefGoogle Scholar
  47. Linge JP, Williams MA, Spronk CA, Bonvin AM, Nilges M (2003) Refinement of protein structures in explicit solvent. Proteins 50:496–506. doi:10.1002/prot.10299 CrossRefGoogle Scholar
  48. Lovell SC et al (2003) Structure validation by Calpha geometry: phi, psi and Cbeta deviation. Proteins 50:437–450CrossRefGoogle Scholar
  49. Mahalakshmi R, Marassi FM (2008) Orientation of the Escherichia coli outer membrane protein OmpX in phospholipid bilayer membranes determined by solid-state NMR. BioChemistry 47:6531–6538. doi:10.1021/bi800362b CrossRefGoogle Scholar
  50. Mao B, Tejero R, Baker D, Montelione GT (2014) Protein NMR structures refined with Rosetta have higher accuracy relative to corresponding X-ray crystal structures. J Am Chem Soc 136:1893–1906. doi:10.1021/ja409845w CrossRefGoogle Scholar
  51. Marassi FM, Opella SJ (2003) Simultaneous assignment and structure determination of a membrane protein from NMR orientational restraints. Protein Sci 12:403–411. doi:10.1110/ps.0211503 CrossRefGoogle Scholar
  52. Marassi FM, Ding Y, Schwieters CD, Tian Y, Yao Y (2015) Backbone structure of Yersinia pestis Ail determined in micelles by NMR-restrained simulated annealing with implicit membrane solvation. J Biomol NMR 63:59–65. doi:10.1007/s10858-015-9963-2 CrossRefGoogle Scholar
  53. Murray DT, Li C, Gao FP, Qin H, Cross TA (2014) Membrane protein structural validation by oriented sample solid-state NMR: diacylglycerol kinase. Biophys J 106:1559–1569. doi:10.1016/j.bpj.2014.02.026 CrossRefGoogle Scholar
  54. Nabuurs SB et al (2004) DRESS: a database of REfined solution NMR structures. Proteins 55:483–486. doi:10.1002/prot.20118 CrossRefGoogle Scholar
  55. Nabuurs SB, Krieger E, Spronk CA, Nederveen AJ, Vriend G, Vuister GW (2005) Definition of a new information-based per-residue quality parameter. J Biomol NMR 33:123–134. doi:10.1007/s10858-005-2826-5 CrossRefGoogle Scholar
  56. Nederveen AJ et al (2005) RECOORD: a recalculated coordinate database of 500+ proteins from the PDB using restraints from the BioMagResBank. Proteins 59:662–672. doi:10.1002/prot.20408 CrossRefGoogle Scholar
  57. Nilges M, Gronenborn AM, Brunger AT, Clore GM (1988) Determination of three-dimensional structures of proteins by simulated annealing with interproton distance restraints. Application to crambin, potato carboxypeptidase inhibitor and barley serine proteinase inhibitor 2. Protein Eng 2:27–38CrossRefGoogle Scholar
  58. Raman S et al (2010) NMR structure determination for larger proteins using backbone-only data. Science 327:1014–1018. doi:10.1126/science.1183649 ADSCrossRefGoogle Scholar
  59. Ramelot TA et al (2009) Improving NMR protein structure quality by Rosetta refinement: a molecular replacement study. Proteins 75:147–167. doi:10.1002/prot.22229 CrossRefGoogle Scholar
  60. Roux B, Simonson T (1999) Implicit solvent models. Biophys Chem 78:1–20CrossRefGoogle Scholar
  61. Sammalkorpi M, Lazaridis T (2007) Modeling a spin-labeled fusion peptide in a membrane: implications for the interpretation of EPR experiments. Biophys J 92:10–22. doi:10.1529/biophysj.106.092809 CrossRefGoogle Scholar
  62. Schwieters CD, Clore GM (2001) Internal coordinates for molecular dynamics and minimization in structure determination and refinement. J Magn Reson 152:288–302ADSCrossRefGoogle Scholar
  63. Schwieters CD, Kuszewski JJ, Tjandra N, Clore GM (2003) The Xplor-NIH NMR molecular structure determination package. J Magn Reson 160:65–73ADSCrossRefGoogle Scholar
  64. Schwieters CD, Kuszewski JJ, Marius Clore G (2006) Using Xplor–NIH for NMR molecular structure determination. Prog Nucl Magn Reson Spectrosc 48:47–62. doi:10.1016/j.pnmrs.2005.10.001 CrossRefGoogle Scholar
  65. Sengupta I, Nadaud PS, Jaroniec CP (2013) Protein structure determination with paramagnetic solid-state NMR spectroscopy. Acc Chem Res 46:2117–2126. doi:10.1021/ar300360q CrossRefGoogle Scholar
  66. Sharma M et al (2010) Insight into the mechanism of the influenza A proton channel from a structure in a lipid bilayer. Science 330:509–512. doi:10.1126/science.1191750 ADSCrossRefGoogle Scholar
  67. Shi L, Traaseth NJ, Verardi R, Cembran A, Gao J, Veglia G (2009) A refinement protocol to determine structure, topology, and depth of insertion of membrane proteins using hybrid solution and solid-state NMR restraints. J Biomol NMR 44:195–205. doi:10.1007/s10858-009-9328-9 CrossRefGoogle Scholar
  68. Spronk CA, Linge JP, Hilbers CW, Vuister GW (2002) Improving the quality of protein structures derived by NMR spectroscopy. J Biomol NMR 22:281–289CrossRefGoogle Scholar
  69. Teriete P, Franzin CM, Choi J, Marassi FM (2007) Structure of the Na, K-ATPase regulatory protein FXYD1 in micelles. BioChemistry 46:6774–6783. doi:10.1021/bi700391b CrossRefGoogle Scholar
  70. Teriete P, Yao Y, Kolodzik A, Yu J, Song H, Niederweis M, Marassi FM (2010) Mycobacterium tuberculosis Rv0899 adopts a mixed alpha/beta-structure and does not form a transmembrane beta-barrel. Biochemistry 49:2768–2777. doi:10.1021/bi100158s CrossRefGoogle Scholar
  71. Tian Y, Schwieters CD, Opella SJ, Marassi FM (2014) A practical implicit solvent potential for NMR structure calculation. J Magn Reson 243:54–64. doi:10.1016/j.jmr.2014.03.011 ADSCrossRefGoogle Scholar
  72. Tian Y, Schwieters CD, Opella SJ, Marassi FM (2015) A practical implicit membrane potential for NMR structure calculations of membrane proteins. Biophys J 109:574–585. doi:10.1016/j.bpj.2015.06.047 CrossRefGoogle Scholar
  73. Vanommeslaeghe K, MacKerell AD Jr (2015) CHARMM additive and polarizable force fields for biophysics and computer-aided drug design. Biochim Biophys Acta 1850:861–871. doi:10.1016/j.bbagen.2014.08.004 CrossRefGoogle Scholar
  74. Vogeley L, Sineshchekov OA, Trivedi VD, Sasaki J, Spudich JL, Luecke H (2004) Anabaena sensory rhodopsin: a photochromic color sensor at 2.0 Å. Science 306:1390–1393. doi:10.1126/science.1103943 ADSCrossRefGoogle Scholar
  75. Wang Y, Schwieters CD, Tjandra N (2012) Parameterization of solvent-protein interaction and its use on NMR protein structure determination. J Magn Reson 221:76–84. doi:10.1016/j.jmr.2012.05.020 ADSCrossRefGoogle Scholar
  76. Wang S et al (2013) Solid-state NMR spectroscopy structure determination of a lipid-embedded heptahelical membrane protein. Nat Methods 10:1007–1012. doi:10.1038/nmeth.2635 CrossRefGoogle Scholar
  77. Ward ME, Brown LS, Ladizhansky V (2015) Advanced solid-state NMR techniques for characterization of membrane protein structure and dynamics: application to Anabaena Sensory Rhodopsin. J Magn Reson 253:119–128. doi:10.1016/j.jmr.2014.11.017 ADSCrossRefGoogle Scholar
  78. Word JM et al (1999) Visualizing and quantifying molecular goodness-of-fit: small-probe contact dots with explicit hydrogen atoms. J Mol Biol 285:1711–1733. doi:10.1006/jmbi.1998.2400 CrossRefGoogle Scholar
  79. Xia B, Tsui V, Case DA, Dyson HJ, Wright PE (2002) Comparison of protein solution structures refined by molecular dynamics simulation in vacuum, with a generalized Born model, and with explicit water. J Biomol NMR 22:317–331CrossRefGoogle Scholar
  80. Xu C et al (2008) Regulation of T cell receptor activation by dynamic membrane binding of the CD3epsilon cytoplasmic tyrosine-based motif. Cell 135:702–713. doi:10.1016/j.cell.2008.09.044 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Ye Tian
    • 1
  • Charles D. Schwieters
    • 2
  • Stanley J. Opella
    • 3
  • Francesca M. Marassi
    • 1
  1. 1.Sanford-Burnham-Prebys Medical Discovery InstituteLa JollaUSA
  2. 2.Center for Information TechnologyNational Institutes of HealthBethesdaUSA
  3. 3.Department of Chemistry and BiochemistryUniversity of California San DiegoLa JollaUSA

Personalised recommendations