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Characterization of PDZ domain–peptide interactions using an integrated protocol of QM/MM, PB/SA, and CFEA analyses

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Abstract

Protein–protein interactions, particularly weak and transient ones, are often mediated by peptide recognition domains. Characterizing the interaction interface of domain–peptide complexes and analyzing binding specificity for modular domains are critical for deciphering protein–protein interaction networks. In this article, we report the successful use of an integrated computational protocol to dissect the energetic profile and structural basis of peptide binding to third PDZ domain (PDZ3) from the PSD-95 protein. This protocol employs rigorous quantum mechanics/molecular mechanics (QM/MM), semi-empirical Poisson–Boltzmann/surface area (PB/SA), and empirical conformational free energy analysis (CFEA) to quantitatively describe and decompose systematic energy changes arising from, respectively, noncovalent interaction, desolvation effect, and conformational entropy loss associated with the formation of 30 affinity-known PDZ3–peptide complexes. We show that the QM/MM-, PB/SA-, and CFEA-derived energy components can work together fairly well in reproducing experimentally measured affinity after a linearly weighting treatment, albeit they are not compatible with each other directly. We also demonstrate that: (1) noncovalent interaction and desolvation effect donate, respectively, stability and specificity to complex architecture, while entropy loss contributes modestly to binding; (2) P0 and P−2 of peptide ligand are the most important positions for determining both the stability and specificity of the PDZ3–peptide complex, P−1 and P−3 can confer substantial stability (but not specificity) for the complex, and N-terminal P−4 and P−5 have only a very limited effect on binding.

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References

  1. Neduva V, Linding R, Su Angrand I, Stark A, de Masi F, Gibson TJ, Lewis J, Serrano L, Russell RB (2005) Systematic discovery of new recognition peptides mediating protein interaction networks. PLoS Biol 3:e405

    Article  Google Scholar 

  2. Petsalaki E, Russell RB (2008) Peptide mediated interactions in biological systems: new discoveries and applications. Curr Opin Biotechnol 19:344–350

    Article  CAS  Google Scholar 

  3. Vanhee P, Stricher F, Baeten L, Verschueren E, Lenaerts T, Serrano L, Rousseau F, Schymkowitz J (2009) Protein–peptide interactions adopt the same structural motifs as monomeric protein folds. Structure 17:1128–1136

    Article  CAS  Google Scholar 

  4. Hou T, Zhang W, Case DA, Wang W (2008) Characterization of domain–peptide interaction interface: a case study on the amphiphysin-1 SH3 domain. J Mol Biol 376:1201–1214

    Article  CAS  Google Scholar 

  5. Hung AY, Sheng M (2002) PDZ domains: structural modules for protein complex assembly. J Biol Chem 277:5699–5702

    Article  CAS  Google Scholar 

  6. Kennedy MB (1995) Origin of PDZ (DHR, GLGF) domains. Trends Biochem Sci 20:350

    Article  CAS  Google Scholar 

  7. Ponting CP (1997) Evidence for PDZ domains in bacteria, yeast, and plants. Protein Sci 6:46–468

    Google Scholar 

  8. Nourry C, Grant SGN, Borg JP (2003) PDZ domain proteins: plug and play! Sci STKE 2003(179):RE7

  9. Tonikian R, Zhang Y, Sazinsky SL, Currell B, Yeh JH, Reva B, Held HA, Appleton BA, Evangelista M, Wu Y, Xin X, Chan AC, Seshagiri S, Lasky LA, Sander C, Boone C, Bader GD, Sidhu SS (2008) A specificity map for the PDZ domain family. PLoS Biol 6:e239

    Article  Google Scholar 

  10. Dev KK (2004) Making protein interactions druggable: targeting PDZ domains. Nat Rev Drug Discov 3:1047–1056

    Article  CAS  Google Scholar 

  11. Giallourakis C, Cao Z, Green T, Wachtel H, Xie X, Lopez-Illasaca M, Daly M, Rioux J, Xavier R (2006) A molecular-properties-based approach to understanding PDZ domain proteins and PDZ ligands. Genome Res 16:1056–1072

    Article  CAS  Google Scholar 

  12. Wiedemann U, Boisguerin P, Leben R, Leitner D, Krause G, Moelling K, Volkmer-Engert R, Oschkinat H (2004) Quantification of PDZ domain specificity, prediction of ligand affinity and rational design of super-binding peptides. J Mol Biol 343:703–718

    Article  CAS  Google Scholar 

  13. Doyle DA, Lee A, Lewis J, Kim E, Sheng M, MacKinnon R (1996) Crystal structures of a complexed and peptide-free membrane protein–binding domain: molecular basis of peptide recognition by PDZ. Cell 85:1067–1076

    Article  CAS  Google Scholar 

  14. Stiffler MA, Chen JR, Grantcharova VP, Lei Y, Fuchs D, Allen JE, Zaslavskaia LA, MacBeath G (2007) PDZ domain binding selectivity is optimized across the mouse proteome. Science 317:364–369

    Article  CAS  Google Scholar 

  15. Chen JR, Chang BH, Allen JE, Stiffler MA, MacBeath G (2008) Predicting PDZ domain–peptide interactions from primary sequences. Nat Biotechnol 26:1041–1045

    Article  CAS  Google Scholar 

  16. Kaufmann K, Shen N, Mizoue L, Meiler J (2011) A physical model for PDZ-domain/peptide interactions. J Mol Model 17:315–324

    Article  CAS  Google Scholar 

  17. Saro D, Klosi E, Paredes A, Spaller MR (2004) Thermodynamic analysis of a hydrophobic binding site: probing the PDZ domain with nonproteinogenic peptide ligands. Org Lett 6:3429–3432

    Article  CAS  Google Scholar 

  18. Saro D, Li T, Rupasinghe C, Paredes A, Caspers N, Spaller MR (2007) A thermodynamic ligand binding study of the third PDZ domain (PDZ3) from the mammalian neuronal protein PSD-95. Biochemistry 46:6340–6352

    Article  CAS  Google Scholar 

  19. Krivov GG, Shapovalov MV, Dunbrack RL Jr (2009) Improved prediction of protein side-chain conformations with SCWRL4. Proteins 77:778–795

    Article  CAS  Google Scholar 

  20. Word JM, Lovell SC, Richardson JS, Richardson DC (1999) Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. J Mol Biol 285:1735–1747

    Article  CAS  Google Scholar 

  21. Knapp B, Omasits U, Schreiner W (2008) Side chain substitution benchmark for peptide/MHC interaction. Protein Sci 17:977–982

    Article  CAS  Google Scholar 

  22. Zhou P, Tian F, Lv F, Shang Z (2009) Geometric characteristics of hydrogen bonds involving sulfur atoms in proteins. Proteins 76:151–163

    Article  CAS  Google Scholar 

  23. Duan Y, Wu C, Chowdhury S, Lee MC, Xiong G, Zhang W, Yang R, Cieplak P, Luo R, Lee T, Caldwell J, Wang J, Kollman P (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

    Article  CAS  Google Scholar 

  24. Tian F, Yang L, Lv F, Luo X, Pan P (2011) Why OppA protein can bind sequence-independent peptides? A combination of QM/MM, PB/SA, and structure-based QSAR Analyses. Amino Acids 40:493–503

    Article  CAS  Google Scholar 

  25. Svensson M, Humbel S, Froese RDJ, Matsubara T, Sieber S, Morokuma K (1996) ONIOM: a multilayered integrated MO + MM method for geometry optimizations and single point energy predictions. A test for Diels-Alder reactions and Pt(P(t-Bu)(3))(2) + H-2 oxidative addition. J Phys Chem 100:19357–19363

    Article  CAS  Google Scholar 

  26. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Zakrzewski VG, Montgomery JA Jr, Stratmann RE, Burant JC, Dapprich S, Millam JM, Daniels AD, Kudin KN, Strain MC, Farkas O, Tomasi J, Barone V, Cossi M, Cammi R, Mennucci B, Pomelli C, Adamo C, Clifford S, Ochterski J, Petersson GA, Ayala PY, Cui Q, Morokuma K, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Cioslowski J, Ortiz JV, Stefanov BB, Liu G, Liashenko A, Piskorz P, Komaromi I, Gomperts R, Martin RL, Fox DJ, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Gonzalez C, Challacombe M, Gill PMW, Johnson BG, Chen W, Wong MW, Andres JL, Head-Gordon M, Replogle ES, Pople JA (2003) Gaussian 03. Gaussian Inc., Wallingford

    Google Scholar 

  27. Dewar MJS, Zoebisch EG, Healy EF, Stewart JJP (1985) AM1: a new general purpose quantum mechanical molecular model. J Am Chem Soc 107:3902–3909

    Article  CAS  Google Scholar 

  28. Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz KM Jr, Ferguson DM, Spellmeyer DC, Fox T, Caldwell JW, Kollman PA (1995) A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J Am Chem Soc 117:5179–5197

    Article  CAS  Google Scholar 

  29. Li Y, Yang Y, He P, Yang Q (2009) QM/MM study of epitope peptides binding to HLA-A*0201: the roles of anchor residues and water. Chem Biol Drug Des 74:611–618

    Article  CAS  Google Scholar 

  30. Zhou P, Zou J, Tian F, Shang Z (2009) Fluorine bonding—how does it work in protein–ligand interactions? J Chem Inf Model 49:2344–2355

    Article  CAS  Google Scholar 

  31. Eisenberg D, McLachlan AD (1986) Solvation energy in protein folding and binding. Nature 319:199–203

    Article  CAS  Google Scholar 

  32. Kollman PA, Massova I, Reyes C, Kuhn B, Huo SH, Chong L, Lee M, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33:889–897

    Article  CAS  Google Scholar 

  33. Retegan M, Milet A, Jamet H (2009) Exploring the binding of inhibitors derived from tetrabromobenzimidazole to the CK2 protein using a QM/MM-PB/SA approach. J Chem Inf Model 49:963–971

    Article  CAS  Google Scholar 

  34. Dubey K, Ojha R (2011) Binding free energy calculation with QM/MM hybrid methods for Abl-Kinase inhibitor. J Biol Phys 37:69–78

    Article  CAS  Google Scholar 

  35. Rocchia W, Alexov E, Honig B (2001) Extending the applicability of the nonlinear. Poisson–Boltzmann equation: multiple dielectric constants and multivalent ions. J Phys Chem 105:6507–6514

    Article  CAS  Google Scholar 

  36. Sanner MF, Olson AJ, Spehner JC (1996) Reduced surface: an efficient way to compute molecular surfaces. Biopolymers 38:305–320

    Article  CAS  Google Scholar 

  37. Lovell SC, Word JM, Richardson JS, Richardson DC (2000) The penultimate rotamer library. Proteins 40:389–408

    Article  CAS  Google Scholar 

  38. Zhou P, Tian F, Shang Z (2009) 2D depiction of nonbonding interactions for protein complexes. J Comput Chem 30:940–951

    Article  CAS  Google Scholar 

  39. Creamer TP (2000) Side-chain conformational entropy in protein unfolded states. Proteins 40:443–450

    Article  CAS  Google Scholar 

  40. Bader RFW (1990) Atoms in molecules: a quantum theory. UK, Oxford University Press

    Google Scholar 

  41. Wang W, Tian A, Wong NB (2005) Theoretical study on the bromomethane–water 1:2 complexes. J Phys Chem A 109:8035–8040

    Article  CAS  Google Scholar 

  42. Reed AE, CuritssLA WeinholdF (1988) Intermolecular interactions from a natural bond orbital, donor-acceptor viewpoint. Chem Rev 88:889–926

    Article  Google Scholar 

  43. Møller C, Plesset MS (1934) Note on an approximation treatment for many-electron systems. Phys Rev 46:618–622

    Article  Google Scholar 

  44. Biegler-Konig F, Schoenbohm J (2002) AIM2000, 2.0 ed. Buro fur Innovative Software, Bielefeld, Germany

    Google Scholar 

  45. Glendening ED, Badenhoop JK, Reed AE, Carpente JE, Bohmann JA, Morales CM, Weinhold F (2001) NBO 5.0. Theoretical Chemistry Institute, University of Wisconsin, Madison, WI

    Google Scholar 

  46. Cortes C, Vapnik V (1995) Support vector networks. Mach Learn 20:273–293

    Google Scholar 

  47. Zhou P, Tian F, Chen X, Shang Z (2008) Modeling and prediction of binding affinities between the human amphiphysin SH3 domain and its peptide ligands using genetic algorithm-Gaussian processes. Biopolymers (Pept Sci) 90:792–802

    Article  CAS  Google Scholar 

  48. Zhou P, Chen X, Wu Y, Shang Z (2010) Gaussian process: an alternative approach for QSAM modeling of peptides. Amino Acids 38:199–212

    Article  CAS  Google Scholar 

  49. Zhou P, Tian F, Lv F, Shang Z (2009) Comprehensive comparison of eight statistical modelling methods used in quantitative structure–retention relationship studies for liquid chromatographic retention times of peptides generated by protease digestion of the Escherichia coli proteome. J Chromatogr A 1216:3107–3116

    Article  CAS  Google Scholar 

  50. Matta CF, Castillo N, Boyd RJ (2005) Characterization of a closed-shell fluorine–fluorine bonding Interaction in aromatic compounds on the basis of the electron density. J Phys Chem A 109:3669–3681

    Article  CAS  Google Scholar 

  51. Nakanishi W, Hayashi S, Narahara K (2008) Atoms-in-molecules dual parameter analysis of weak to strong interactions: behaviors of electronic energy densities versus Laplacian of electron densities at bond critical points. J Phys Chem A 112:13593–13599

    Article  CAS  Google Scholar 

  52. Petsalaki E, Stark A, Garcia-Urdiales E, Russell RB (2009) Accurate prediction of peptide binding sites on protein surfaces. 5:e1000335

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Acknowledgments

The authors would like to express their gratitude to the anonymous reviewers and the editors for their professional, intensive, and useful comments. This work was supported in part by grants from the National Natural Science Foundation of China (11032012 and 30870608), the Key Science and Technology Program of CQ CSTC (2009AA5045), and the sharing fund of Chongqing university’s large-scale equipment and the Visiting Scholar Foundation of Key Lab. of Biorheological Science and Technology Under Ministry of Education in Chongqing University.

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Authors and Affiliations

  1. Key Laboratory of Biorheological Science and Technology Under Ministry of Education, ‘111’ Project Laboratory of Biomechanics and Tissue Repair, and Bioengineering College, Chongqing University, Chongqing, 400044, China

    Feifei Tian, Yonggang Lv & Li Yang

  2. School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, 610031, China

    Feifei Tian

  3. Center of Bioinformatics (COBI), School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Peng Zhou

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  1. Feifei Tian
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Correspondence to Li Yang.

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F. Tian and Y. Lv contributed equally to this work.

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Tian, F., Lv, Y., Zhou, P. et al. Characterization of PDZ domain–peptide interactions using an integrated protocol of QM/MM, PB/SA, and CFEA analyses. J Comput Aided Mol Des 25, 947–958 (2011). https://doi.org/10.1007/s10822-011-9474-5

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