Journal of Computer-Aided Molecular Design

, Volume 26, Issue 3, pp 301–309 | Cite as

Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions



Membrane proteins are of particular biological and pharmaceutical importance, and computational modeling and structure prediction approaches play an important role in studies of membrane proteins. Developing an accurate model quality assessment program is of significance to the structure prediction of membrane proteins. Few such programs are proposed that can be applied to a broad range of membrane protein classes and perform with high accuracy. We developed a new model scoring function Interaction-based Quality assessment (IQ), based on the analysis of four types of inter-residue interactions within the transmembrane domains of helical membrane proteins. This function was tested using three high-quality model sets: all 206 models of GPCR Dock 2008, all 284 models of GPCR Dock 2010, and all 92 helical membrane protein models of the HOMEP set. For all three sets, the scoring function can select the native structures among all of the models with the success rates of 93, 85, and 100% respectively. For comparison, these three model sets were also adopted for a recently published model assessment program for membrane protein structures, ProQM, which gave the success rates of 85, 79, and 92% separately. These results suggested that IQ outperforms ProQM when only the transmembrane regions of the models are considered. This scoring function should be useful for the computational modeling of membrane proteins.


Membrane proteins Structure quality Inter-residue interactions Frequency score Average number of interactions 

Supplementary material

10822_2012_9556_MOESM1_ESM.doc (38.4 mb)
Supplementary material 1 (DOC 39298 kb)


  1. 1.
    Visiers I, Ballesteros JA, Weinstein H (2002) Three-dimensional representations of G protein-coupled receptor structures and mechanisms. Methods Enzymol 343:329–371CrossRefGoogle Scholar
  2. 2.
    Oliveira L, Hulsen T, Lutje Hulsik D, Paiva AC, Vriend G (2004) Heavier-than-air flying machines are impossible. FEBS Lett 564:269–273CrossRefGoogle Scholar
  3. 3.
    Fanelli F, De Benedetti PG (2005) Computational modeling approaches to structure-function analysis of G protein-coupled receptors. Chem Rev 105:3297–3351CrossRefGoogle Scholar
  4. 4.
    Kontoyianni M, DeWeese C, Penzotti JE, Lybrand TP (1996) Three-dimensional models for agonist and antagonist complexes with beta 2 adrenergic receptor. J Med Chem 39:4406–4420CrossRefGoogle Scholar
  5. 5.
    Wallin E, von Heijne G (1998) Genome-wide analysis of integral membrane proteins from eubacterial, archaean, and eukaryotic organisms. Protein Sci 7:1029–1038CrossRefGoogle Scholar
  6. 6.
    Liu Y, Engelman DM, Gerstein M (2002) Genomic analysis of membrane protein families: abundance and conserved motifs. Genome Biol 3, research0054Google Scholar
  7. 7.
    Fleming KG (2000) Riding the wave: structural and energetic principles of helical membrane proteins. Curr Opin Biotechnol 11:67–71CrossRefGoogle Scholar
  8. 8.
    Overington JP, Al-Lazikani B, Hopkins AL (2006) How many drug targets are there? Nat Rev Drug Discov 5:993–996CrossRefGoogle Scholar
  9. 9.
    Xu F, Wu H, Katritch V, Han GW, Jacobson KA, Gao ZG, Cherezov V, Stevens RC (2011) Structure of an agonist-bound human A2A adenosine receptor. Science 332:322–327CrossRefGoogle Scholar
  10. 10.
    Karnik SS, Gogonea C, Patil S, Saad Y, Takezako T (2003) Activation of G-protein-coupled receptors: a common molecular mechanism. Trends Endocrinol Metab 14:431–437CrossRefGoogle Scholar
  11. 11.
    Ray A, Lindahl E, Wallner B (2010) Model quality assessment for membrane proteins. Bioinformatics 26:3067–3074CrossRefGoogle Scholar
  12. 12.
    Gao C, Stern HA (2007) Scoring function accuracy for membrane protein structure prediction. Proteins 68:67–75CrossRefGoogle Scholar
  13. 13.
    Chamberlain AK, Bowie JU (2004) Analysis of side-chain rotamers in transmembrane proteins. Biophys J 87:3460–3469CrossRefGoogle Scholar
  14. 14.
    Adamian L, Liang J (2001) Helix–helix packing and interfacial pairwise interactions of residues in membrane proteins. J Mol Biol 311:891–907CrossRefGoogle Scholar
  15. 15.
    Eilers M, Patel AB, Liu W, Smith SO (2002) Comparison of helix interactions in membrane and soluble alpha-bundle proteins. Biophys J 82:2720–2736CrossRefGoogle Scholar
  16. 16.
    Eilers M, Shekar SC, Shieh T, Smith SO, Fleming PJ (2000) Internal packing of helical membrane proteins. Proc Natl Acad Sci USA 97:5796–5801CrossRefGoogle Scholar
  17. 17.
    Fleishman SJ, Ben-Tal N (2002) A novel scoring function for predicting the conformations of tightly packed pairs of transmembrane alpha-helices. J Mol Biol 321:363–378CrossRefGoogle Scholar
  18. 18.
    Park Y, Helms V (2006) Assembly of transmembrane helices of simple polytopic membrane proteins from sequence conservation patterns. Proteins 64:895–905CrossRefGoogle Scholar
  19. 19.
    Pabuwal V, Li Z (2008) Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction. Protein Eng Des Sel 21:55–64CrossRefGoogle Scholar
  20. 20.
    Gao J, Li Z (2009) Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins. Biopolymers 91:547–556CrossRefGoogle Scholar
  21. 21.
    Gao J, Li Z (2009) Conserved network properties of helical membrane protein structures and its implication for improving membrane protein homology modeling at the twilight zone. J Comput Aided Mol Des 23:755–763CrossRefGoogle Scholar
  22. 22.
    Gromiha MM, Selvaraj S (2001) Role of medium- and long-range interactions in discriminating globular and membrane proteins. Int J Biol Macromol 29:25–34CrossRefGoogle Scholar
  23. 23.
    Michino M, Abola E, GPCR Dock 2008 participants, Brooks CL III, Dixon JS, Moult J, Stevens RC (2009) Community-wide assessment of GPCR structure modelling and ligand docking: GPCR dock 2008. Nat Rev Drug Discov 8:455–463Google Scholar
  24. 24.
    Kufareva I, Rueda M, Katritch V, GPCR Dock 2010 participants, Stevens RC, Abagyan R (2011) Status of GPCR modeling and docking as reflected by community wide GPCR dock 2010 assessment. Structure 19:1108–1126Google Scholar
  25. 25.
    Forrest LR, Tang CL, Honig B (2006) On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins. Biophys J 91:508–517CrossRefGoogle Scholar
  26. 26.
    Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG (2007) Clustal W and clustal X version 2.0. Bioinformatics 23:2947–2948CrossRefGoogle Scholar
  27. 27.
    Pearl FM, Bennett CF, Bray JE, Harrison AP, Martin N, Shepherd A, Sillitoe I, Thornton J, Orengo CA (2003) The CATH database: an extended protein family resource for structural and functional genomics. Nucleic Acids Res 31:452–455CrossRefGoogle Scholar
  28. 28.
    Tusnady GE, Dosztanyi Z, Simon I (2005) PDB_TM: selection and membrane localization of transmembrane proteins in the protein data bank. Nucleic Acids Res 33:D275–D278CrossRefGoogle Scholar
  29. 29.
    Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815CrossRefGoogle Scholar
  30. 30.
    Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28:235–242CrossRefGoogle Scholar
  31. 31.
    Stickle DF, Presta LG, Dill KA, Rose GD (1992) Hydrogen bonding in globular proteins. J Mol Biol 226:1143–1159CrossRefGoogle Scholar
  32. 32.
    Muppirala UK, Li Z (2006) A simple approach for protein structure discrimination based on the network pattern of conserved hydrophobic residues. Protein Eng Des Sel 19:265–275CrossRefGoogle Scholar
  33. 33.
    Wallner B, Elofsson A (2003) Can correct protein models be identified? Protein Sci 12:1073–1086CrossRefGoogle Scholar
  34. 34.
    Gromiha MM, Selvaraj S (2004) Inter-residue interactions in protein folding and stability. Prog Biophys Mol Biol 86:235–277CrossRefGoogle Scholar
  35. 35.
    Handl J, Knowles J, Lovell SC (2009) Artefacts and biases affecting the evaluation of scoring functions on decoy sets for protein structure prediction. Bioinformatics 25:1271–1279CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Chemistry and BiochemistryUniversity of the Sciences in PhiladelphiaPhiladelphiaUSA
  2. 2.Institute for Translational Medicine and TherapeuticsUniversity of the PennsylvaniaPhiladelphiaUSA

Personalised recommendations