1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Biochemistry
  4. Volume 91, 2022
  5. Article

Annual Review of Biochemistry

Volume 91, 2022

Influence of Nonspecific Interactions on Protein Associations: Implications for Biochemistry In Vivo

Abstract

The cellular interior is composed of a variety of microenvironments defined by distinct local compositions and composition-dependent intermolecular interactions. We review the various types of nonspecific interactions between proteins and between proteins and other macromolecules and supramolecular structures that influence the state of association and functional properties of a given protein existing within a particular microenvironment at a particular point in time. The present state of knowledge is summarized, and suggestions for fruitful directions of research are offered.

Keyword(s): intracellular organization, macromolecular crowding, phase transitions, protein–protein interactions, surface adsorption
Loading

Article metrics loading...

/content/journals/10.1146/annurev-biochem-040320-104151
2022-06-21
2025-04-19
Loading full text...

Full text loading...

/deliver/fulltext/biochem/91/1/annurev-biochem-040320-104151.html?itemId=/content/journals/10.1146/annurev-biochem-040320-104151&mimeType=html&fmt=ahah

Literature Cited

  1. 1.
    Khatun MS, Shoombuatong W, Hasan MM, Kurata H. 2020. Evolution of sequence-based bioinformatics tools for protein-protein interaction. Curr. Genom. 21:454–63
     [Google Scholar]
  2. 2.
    Aslam B, Basit M, Nisar MA, Khurshid M, Rasool MH. 2017. Proteomics: technologies and their applications. J. Chrom. Sci. 55:182–96
     [Google Scholar]
  3. 3.
    Luby-Phelps K. 2013. The physical chemistry of cytoplasm and its influence on cell function: an update. Mol. Biol. Cell 24:2593–96
     [Google Scholar]
  4. 4.
    Kapanidis AN, Uphoff S, Stracey M. 2018. Understanding protein mobility in bacteria by tracking single molecules. J. Mol. Biol. 430:4443–55
     [Google Scholar]
  5. 5.
    Johnston KP, Maynard JA, Truskett TM, Borwankar AU, Miller MA et al. 2012. Concentrated dispersions of equilibrium protein nanoclusters that reversibly dissociate into active monomers. ACS Nano 6:1357–69
     [Google Scholar]
  6. 6.
    Lilyestrom WG, Yadav S, Shire SJ, Scherer TM. 2013. Monoclonal antibody self-association, cluster formation, and rheology at high concentrations. J. Phys. Chem. B 117:6373–84
     [Google Scholar]
  7. 7.
    Stradner A, Sedgwick H, Cardinaux F, Poon WCK, Egelhaaf SU, Schurtenberger P. 2004. Equilibrium cluster formation in concentrated protein solutions and colloids. Nature 432:492–95
     [Google Scholar]
  8. 8.
    Guin D, Gruebele M. 2019. Weak chemical interactions that drive protein evolution: crowding, sticking, and quinary structure in folding and function. Chem. Rev. 119:10691–717
     [Google Scholar]
  9. 9.
    Israelachvili JN. 1989. Intermolecular and Surface Forces with Applications to Colloidal and Biological Systems London: Academic
     [Google Scholar]
  10. 10.
    Wirth AJ, Gruebele M. 2013. Quinary protein structure and the consequences of crowding in living cells: leaving the test-tube behind. BioEssays 35:904–93
     [Google Scholar]
  11. 11.
    Huggins DJ, Marsh M, Payne MC. 2011. Thermodynamic properties of water molecules at a protein–protein interface. J. Chem. Theory Comput. 7:3514–22
     [Google Scholar]
  12. 12.
    Tsai C-J, Lin SL, Wolfson HJ, Nussinov R. 1997. Studies of protein–protein interfaces: a statistical analysis of the hydrophobic effect. Protein Sci 6:53–64
     [Google Scholar]
  13. 13.
    Xu D, Lin SL, Nussinov R. 1997. Protein binding versus protein folding: the role of hydrophilic bridges in protein associations. J. Mol. Biol. 265:68–84
     [Google Scholar]
  14. 14.
    Luby-Phelps K. 2000. Cytoarchitecture and physical properties of cytoplasm: volume, viscosity, diffusion, intracellular surface area. Int. Rev. Cytol. 192:189–221
     [Google Scholar]
  15. 15.
    Minton AP 1990. Holobiochemistry: an integrated approach to the understanding of biochemical mechanisms that emerges from the study of proteins and protein associations in volume-occupied solutions. Structural and Organizational Aspects of Metabolic Regulation PA Srere, ME Jones, CK Mathews 291–306 New York: Wiley-Liss
     [Google Scholar]
  16. 16.
    Minton AP. 1981. Excluded volume as a determinant of macromolecular structure and reactivity. Biopolymers 20:2093–120
     [Google Scholar]
  17. 17.
    Berg O. 1990. The influence of macromolecular crowding on thermodynamic activity: solubility and dimerization constants for spherical and dumbbell-shaped molecules in a hard-sphere mixture. Biopolymers 30:1027–37
     [Google Scholar]
  18. 18.
    Bhattacharya A, Kim YC, Mittal J. 2013. Protein–protein interactions in a crowded environment. Biophys. Rev. 5:99–108
     [Google Scholar]
  19. 19.
    Hoppe T, Minton AP. 2019. Non-specific interactions between macromolecular solutes in concentrated solution: physico-chemical manifestations and biochemical consequences. Front. Mol. Biosci. 6:10
     [Google Scholar]
  20. 20.
    Jiao M, Li H-T, Chen J, Minton AP, Liang Y. 2010. Attractive protein-polymer interactions markedly alter the effect of macromolecular crowding on protein association equilibria. Biophys. J. 99:914–23
     [Google Scholar]
  21. 21.
    Kim YC, Mittal J. 2013. Crowding-induced entropy-enthalpy compensation in protein association equilibria. Phys. Rev. Lett. 110:208102
     [Google Scholar]
  22. 22.
    Minton AP. 1983. The effect of volume occupancy upon the thermodynamic activity of proteins: some biochemical consequences. Mol. Cell. Biochem. 55:119–40
     [Google Scholar]
  23. 23.
    Minton AP. 1998. Molecular crowding: analysis of effects of high concentrations of inert cosolutes on biochemical equilibria and rates in terms of volume exclusion. Methods Enzymol 295:127–49
     [Google Scholar]
  24. 24.
    Minton AP. 2013. Quantitative assessment of the relative contributions of steric repulsion and chemical interactions to macromolecular crowding. Biopolymers 99:239–44
     [Google Scholar]
  25. 25.
    Nguemaha V, Qin S, Zhou H-X. 2019. Transfer free energies of test proteins into crowded protein solutions have simple dependence on crowder concentration. Front. Mol. Biosci. 6:39
     [Google Scholar]
  26. 26.
    Sapir L, Harries D. 2015. Macromolecular stabilization by excluded cosolutes: mean field theory of crowded solutions. J. Chem. Theory Comput. 11:3478–90
     [Google Scholar]
  27. 27.
    Sharp K. 2015. Analysis of the size dependence of macromolecular crowding shows that smaller is better. PNAS 112:7990–95
     [Google Scholar]
  28. 28.
    Hu Z, Jiang J, Rajagopalan R. 2007. Effects of macromolecular crowding on biochemical reaction equilibria: a molecular thermodynamic perspective. Biophys. J. 93:1464–73
     [Google Scholar]
  29. 29.
    Kinjo AR, Takada S. 2002. Effects of macromolecular crowding on protein folding and aggregation studied by density functional theory: dynamics. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 66:051902
     [Google Scholar]
  30. 30.
    Shkel IA, Knowles DB, Record MT Jr. 2015. Separating chemical and excluded volume interactions of polyethylene glycols with native proteins: comparison with PEG effects on DNA helix formation. Biopolymers 103:517–27
     [Google Scholar]
  31. 31.
    Fernández C, Minton AP. 2009. Static light scattering from concentrated protein solutions II. Experimental test of theory for protein mixtures and weakly self-associating proteins. Biophys. J. 96:1992–98
     [Google Scholar]
  32. 32.
    Fodeke AA, Minton AP. 2010. Quantitative characterization of polymer–polymer, protein–protein, and polymer–protein interaction via tracer sedimentation equilibrium. J. Phys. Chem. B 114:10876–80
     [Google Scholar]
  33. 33.
    Fodeke AA, Minton AP. 2011. Quantitative characterization of temperature-independent and temperature-dependent protein–protein interactions in highly nonideal solutions. J. Phys. Chem. B 115:11261–68
     [Google Scholar]
  34. 34.
    Hatters DM, Minton AP, Howlett GJ. 2002. Macromolecular crowding accelerates amyloid formation by human apolipoprotein C-II. J. Biol. Chem. 277:7824–30
     [Google Scholar]
  35. 35.
    Minton AP. 1995. A molecular model for the dependence of the osmotic pressure of bovine serum albumin upon concentration and pH. Biophys. Chem. 57:65–70
     [Google Scholar]
  36. 36.
    Minton AP. 2005. Influence of macromolecular crowding upon the stability and state of association of proteins: predictions and observations. J. Pharm. Sci. 94:1668–75
     [Google Scholar]
  37. 37.
    Minton AP. 2008. Effective hard particle model for the osmotic pressure of highly concentrated binary protein solutions. Biophys. J. 93:L57–59
     [Google Scholar]
  38. 38.
    Nagarajan S, Grupi A, Goldenberg DP, Minton AP, Haas E. 2011. Modulation of functionally significant conformational equilibria in adenylate cyclase by high concentrations of trimethylamine oxide attributed to volume exclusion. Biophys. J. 100:2991–99
     [Google Scholar]
  39. 39.
    Qin S, Zhou H-X. 2019. Calculation of second virial coefficients of atomistic proteins using Fast Fourier Transform. J. Phys. Chem. B 123:8203–15
     [Google Scholar]
  40. 40.
    Ross PD, Briehl RW, Minton AP. 1978. Temperature dependence of nonideality in concentrated solutions of hemoglobin. Biopolymers 17:2285–88
     [Google Scholar]
  41. 41.
    Ross PD, Minton AP. 1977. Analysis of nonideal behavior in concentrated hemoglobin solutions. J. Mol. Biol. 112:437–52
     [Google Scholar]
  42. 42.
    Sasahara K, McPhie P, Minton AP. 2003. Effect of dextran on protein stability and conformation attributed to macromolecular crowding. J. Mol. Biol. 326:1227–37
     [Google Scholar]
  43. 43.
    Scherer TM, Liu J, Shire SJ, Minton AP. 2010. Characterization of intermolecular interactions of monoclonal IgG1 antibodies in high concentration solutions via light scattering. J. Phys. Chem. B 114:12948–57
     [Google Scholar]
  44. 44.
    Wu D, Minton AP. 2015. Quantitative characterization of nonspecific self- and hetero-interactions of proteins in nonideal solutions via static light scattering. J. Phys. Chem. B 119:1891–98
     [Google Scholar]
  45. 45.
    Hoppe T, Minton AP. 2016. Incorporation of hard and soft protein–protein interactions into models for crowding effects in binary and ternary protein mixtures. Comparison of approximate analytical solutions with numerical simulation. J. Phys. Chem. B 120:11866–72
     [Google Scholar]
  46. 46.
    Rosen J, Kim YC, Mittal J. 2011. Modest protein–crowder attractive interactions can counteract enhancement of protein association by intermolecular excluded volume interactions. J. Phys. Chem. B 115:2683–89
     [Google Scholar]
  47. 47.
    McMillan WG Jr., Mayer JE. 1945. The statistical thermodynamics of multicomponent systems. J. Chem. Phys. 13:276–305
     [Google Scholar]
  48. 48.
    Douglas JF, Dudowicz J, Freed KF. 2009. Crowding induced self-assembly and enthalpy-entropy compensation. Phys. Rev. Lett. 103:135701
     [Google Scholar]
  49. 49.
    Minton AP. 2017. Explicit incorporation of hard and soft protein–protein interactions into models for crowding effects in protein mixtures. II. Effects of varying hard and soft interactions upon prototypical chemical equilibria. J. Phys. Chem. B 121:5515–22
     [Google Scholar]
  50. 50.
    Tanford C. 1961. Physical Chemistry of Macromolecules New York: Wiley & Sons
     [Google Scholar]
  51. 51.
    Minton AP. 1977. Non-ideality and the thermodynamics of sickle-cell hemoglobin gelation. J. Mol. Biol. 110:89–103
     [Google Scholar]
  52. 52.
    Flory PJ. 1953. Principles of Polymer Chemistry Ithaca, NY: Cornell Univ. Press
     [Google Scholar]
  53. 53.
    Nakashima K, Vibhute MA, Spruijt E. 2019. Biomolecular chemistry in liquid phase separated compartments. Front. Mol. Biosci. 6:21
     [Google Scholar]
  54. 54.
    Peeples W, Rosen MK. 2021. Mechanistic dissection of increased enzymatic rate in a phase-separated compartment. Nat. Chem. Biol. 17:693–702
     [Google Scholar]
  55. 55.
    Minton AP. 2001. Effects of excluded surface area and adsorbate clustering on surface adsorption of proteins II. Kinetic models. Biophys. J. 80:1641–48
     [Google Scholar]
  56. 56.
    Zimmerman SB, Minton AP. 1993. Macromolecular crowding: biochemical, biophysical, and physiological consequences. Annu. Rev. Biophys. Biomol. Struct. 22:27–65
     [Google Scholar]
  57. 57.
    Muramatsu N, Minton AP. 1988. Tracer diffusion of globular proteins in concentrated protein solutions. PNAS 85:2984–88
     [Google Scholar]
  58. 58.
    Zhou H-X, Rivas G, Minton AP. 2008. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Annu. Rev. Biophys. 37:375–97
     [Google Scholar]
  59. 59.
    Berezhkovskii AM, Szabo A. 2016. Theory of crowding effects on bimolecular reaction rates. J. Phys. Chem. B 120:5998–6002
     [Google Scholar]
  60. 60.
    Zosel F, Soranno A, Buholzer KJ, Nettels D, Schuler B. 2020. Depletion interactions modulate the binding between disordered proteins in crowded environments. PNAS 117:13480–89
     [Google Scholar]
  61. 61.
    Gray JJ. 2004. The interaction of proteins with solid surfaces. Curr. Opin. Struct. Biol. 14:110–15
     [Google Scholar]
  62. 62.
    Giddings JC, Kucera E, Russell CP, Myers MN. 1968. Statistical theory for the equilibrium distribution of rigid molecules in inert porous networks: exclusion chromatography. J. Phys. Chem. 72:4397–408
     [Google Scholar]
  63. 63.
    Minton AP. 1992. Confinement as a determinant of macromolecular structure and reactivity. Biophys. J. 63:1090–100
     [Google Scholar]
  64. 64.
    Klimov DK, Newfield D, Thirumalai D. 2002. Simulations of β-hairpin folding confined to spherical pores using distributed computing. PNAS 99:8019–24
     [Google Scholar]
  65. 65.
    Simpson LW, Good TA, Leach JB. 2020. Protein folding and assembly in confined environments: implications for protein aggregation in hydrogels and tissues. Biotechnol. Adv. 42:107573
     [Google Scholar]
  66. 66.
    Zhou H-X. 2008. Protein folding in confined and crowded environments. Arch. Biochem. Biophys. 469:76–82
     [Google Scholar]
  67. 67.
    Minton AP. 2007. The effective hard particle model provides a simple, robust and broadly applicable description of nonideal behavior in concentrated solutions of bovine serum albumin and other non-associating proteins. J. Pharm. Sci. 96:3466–69
     [Google Scholar]
  68. 68.
    Hoppe T, Minton AP. 2015. An equilibrium model for the combined effect of macromolecular crowding and surface adsorption on the formation of linear protein fibrils. Biophys. J. 108:957–66
     [Google Scholar]
  69. 69.
    Minton AP. 2019. The cumulative effect of surface adsorption and excluded volume in 2D and 3D on protein fibrillation. Biophys. J. 117:1666–73
     [Google Scholar]
  70. 70.
    Minton AP. 2000. Effects of excluded surface area and adsorbate clustering on surface adsorption of proteins. I. Equilibrium models. Biophys. Chem. 86:239–47
     [Google Scholar]
  71. 71.
    Rabe M, Verdes D, Rankl M, Artus GRJ, Seeger S. 2007. A comprehensive study of concepts and phenomena of the nonspecific adsorption of β-lactoglobulin. ChemPhysChem 8:862–72
     [Google Scholar]
  72. 72.
    Rabe M, Verdes D, Seeger S. 2010. Understanding cooperative protein adsorption events at the microscopic scale: a comparison between experimental data and Monte Carlo simulations. J. Phys. Chem. B 114:5862–69
     [Google Scholar]
  73. 73.
    Canchi DR, Garcia AE. 2013. Cosolvent effects on protein stability. Annu. Rev. Phys. Chem. 64:273–93
     [Google Scholar]
  74. 74.
    Cheung MS, Gasic AG. 2018. Toward developing principles of protein folding and dynamics in the cell. Phys. Biol. 15:063001
     [Google Scholar]
  75. 75.
    Gruebele M, Dave K, Sukenik S 2016. Globular protein folding in vitro and in vivo. Annu. Rev. Biophys. 45:233–51
     [Google Scholar]
  76. 76.
    Zimmerman SB, Trach SO. 1988. Effects of macromolecular crowding on the association of E. coli ribosomal particles. Nucleic Acids Res 16:6309–26
     [Google Scholar]
  77. 77.
    Guseman AJ, Speer SL, Perez Goncalves GM, Pielak GJ 2018. Surface charge modulates protein–protein interactions in physiologically relevant environments. Biochemistry 57:1681–84
     [Google Scholar]
  78. 78.
    Ferrone FA, Rotter MA. 2004. Crowding and the polymerization of sickle hemoglobin. J. Mol. Recognit. 17:497–504
     [Google Scholar]
  79. 79.
    Bookchin RM, Balasz T, Wang Z, Josephs R, Lew VL. 1999. Polymer structure and solubility of deoxyhemoglobin S in the presence of high concentrations of volume-excluding 70-kDa dextran. J. Biol. Chem. 274:6689–97
     [Google Scholar]
  80. 80.
    Lindner RA, Ralston GB. 1997. Macromolecular crowding: effects on actin polymerisation. Biophys. Chem. 66:57–66
     [Google Scholar]
  81. 81.
    Herzog W, Weber K. 1978. Microtubule formation by pure brain tubulin in vitro. The influence of dextran and poly(ethylene glycol). Eur. J. Biochem. 91:249–54
     [Google Scholar]
  82. 82.
    Rivas G, Fernández JA, Minton AP. 1999. Direct observation of the self-association of dilute proteins in the presence of inert macromolecules at high concentration via tracer sedimentation equilibrium: theory, experiment, and biological significance. Biochemistry 38:9379–88
     [Google Scholar]
  83. 83.
    Rivas G, Fernandez JA, Minton AP. 2001. Direct observation of the enhancement of noncooperative protein self-assembly by macromolecular crowding: indefinite linear self-association of bacterial cell division protein FtsZ. PNAS 98:3150–55
     [Google Scholar]
  84. 84.
    Reija B, Monterroso B, Jimenez M, Vicente M, Rivas G, Zorrilla S. 2011. Development of a homogeneous fluorescence anisotropy assay to monitor and measure FtsZ assembly in solution. Anal. Biochem. 418:89–96
     [Google Scholar]
  85. 85.
    Ferrone FA. 2004. Polymerization and sickle cell disease: a molecular view. Microcirculation 11:115–28
     [Google Scholar]
  86. 86.
    Drenckhahn D, Pollard TD. 1986. Elongation of actin filaments is a diffusion-limited reaction at the barbed end and is accelerated by inert macromolecules. J. Biol. Chem. 261:12754–58
     [Google Scholar]
  87. 87.
    Gao M, Winter R 2015. Kinetic insights into the elongation reaction of actin filaments as a function of temperature, pressure, and macromolecular crowding. ChemPhysChem 16:3681–86
     [Google Scholar]
  88. 88.
    Wilf J, Gladner JA, Minton AP. 1985. Acceleration of fibrin gel formation by unrelated proteins. Thromb. Res. 37:681–88
     [Google Scholar]
  89. 89.
    Gonzalez JM, Jimenez M, Velez M, Mingorance J, Andreu JM et al. 2003. Essential cell division protein FtsZ assembles into one monomer-thick ribbons under conditions resembling the crowded intracellular environment. J. Biol. Chem. 278:37664–71
     [Google Scholar]
  90. 90.
    Groen J, Foschepoth D, te Brinke E, Boersma AJ, Imamura H et al. 2015. Associative interactions in crowded solutions of biopolymers counteract depletion effects. J. Am. Chem. Soc. 137:13041–48
     [Google Scholar]
  91. 91.
    Park J, Lee M, Lee B, Castaneda N, Tetard L, Kang EH. 2021. Crowding tunes the organization and mechanics of actin bundles formed by crosslinking proteins. FEBS Lett 595:26–40
     [Google Scholar]
  92. 92.
    Hernandez-Vega A, Braun M, Scharrel L, Jahnel M, Wegmann S et al. 2017. Local nucleation of microtubule bundles through tubulin concentration into a condensed tau phase. Cell Rep 20:2304–12
     [Google Scholar]
  93. 93.
    Shahid S, Hassan MI, Islam A, Ahmad F 2017. Size-dependent studies of macromolecular crowding on the thermodynamic stability, structure, and functional activity of proteins: in vitro and in silico approaches. Biochim. Biophys. Acta Gen. Subj. 1861:178–97
     [Google Scholar]
  94. 94.
    Menon S, Sengupta N. 2019. Influence of crowding and surfaces on protein amyloidogenesis: a thermo-kinetic perspective. Biochim. Biophys. Acta Proteins Proteom. 1867:941–53
     [Google Scholar]
  95. 95.
    Uversky VN, Cooper EM, Bower KS, Li J, Fink AL. 2002. Accelerated α-synuclein fibrillation in crowded milieu. FEBS Lett 515:99–103
     [Google Scholar]
  96. 96.
    Shtilerman MD, Ding TT, Lansbury PT Jr. 2002. Molecular crowding accelerates fibrillization of α-synuclein: Could an increase in the cytoplasmic protein concentration induce Parkinson's disease?. Biochemistry 41:3855–60
     [Google Scholar]
  97. 97.
    Ma B, Xie J, Wei L, Li W 2013. Macromolecular crowding modulates the kinetics and morphology of amyloid self-assembly by β-lactoglobulin. Int. J. Biol. Macromol. 53:82–87
     [Google Scholar]
  98. 98.
    Ma Q, Fan JB, Zhou Z, Zhou BR, Meng SR et al. 2012. The contrasting effect of macromolecular crowding on amyloid fibril formation. PLOS ONE 7:e36288
     [Google Scholar]
  99. 99.
    Munishkina LA, Fink AL, Uversky VN. 2008. Concerted action of metals and macromolecular crowding on the fibrillation of α-synuclein. Protein Pept. Lett. 15:1079–85
     [Google Scholar]
  100. 100.
    Gao M, Estel K, Seeliger J, Friedrich RP, Dogan S et al. 2015. Modulation of human IAPP fibrillation: cosolutes, crowders and chaperones. Phys. Chem. Chem. Phys. 17:8338–48
     [Google Scholar]
  101. 101.
    Ellis RJ, Minton AP. 2006. Protein aggregation in crowded environments. Biol. Chem. 387:485–97
     [Google Scholar]
  102. 102.
    Laurent TC. 1963. The interaction between polysaccharides and other macromolecules. The solubility of proteins in the presence of dextran. Biochem. J. 89:253–57
     [Google Scholar]
  103. 103.
    Atha DH, Ingham KC. 1981. Mechanism of precipitation of proteins by polyethylene glycols. Analysis in terms of excluded volume. J. Biol. Chem. 256:12108–17
     [Google Scholar]
  104. 104.
    Ogston AG. 1970. On the interaction of solute molecules with porous networks. J. Phys. Chem. 74:668–69
     [Google Scholar]
  105. 105.
    Oosawa F, Higashi S. 1967. Statistical thermodynamics of polymerization and polymorphism of protein. Progress in Theoretical Biology FM Snell 79–164 New York: Academic
     [Google Scholar]
  106. 106.
    Monterroso B, Reija B, Jimenez M, Zorrilla S, Rivas G. 2016. Charged molecules modulate the volume exclusion effects exerted by crowders on FtsZ polymerization. PLOS ONE 11:e0149060
     [Google Scholar]
  107. 107.
    André AAM, Spruijt E. 2020. Liquid–liquid phase separation in crowded environments. Int. J. Mol. Sci. 21:5908
     [Google Scholar]
  108. 108.
    Taratuta VG, Holschbach A, Thurston GM, Blankschtein D, Benedek GB. 1990. Liquid–liquid phase separation of aqueous lysozyme solutions: effects of pH and salt identity. J. Phys. Chem. 94:2140–44
     [Google Scholar]
  109. 109.
    Thomson JA, Schurtenberger P, Thurston GM, Benedek GB. 1987. Binary liquid phase separation and critical phenomena in a protein/water solution. PNAS 84:7079–83
     [Google Scholar]
  110. 110.
    Annunziata O, Asherie N, Lomakin A, Pande J, Ogun O, Benedek GB. 2002. Effect of polyethylene glycol on the liquid–liquid phase transition in aqueous protein solutions. PNAS 99:14165–70
     [Google Scholar]
  111. 111.
    Cohan MC, Pappu RV. 2020. Making the case for disorded proteins and biomolecular condensates in bacteria. Trends Biochem. Sci. 45:668–80
     [Google Scholar]
  112. 112.
    Alberti S, Gladfelter AS, Mittag T. 2019. Considerations and challenges in studying liquid-liquid phase separation and biomolecular condensates. Cell 176:419–34
     [Google Scholar]
  113. 113.
    Banani SF, Lee HO, Hyman AA, Rosen MK. 2017. Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18:285–98
     [Google Scholar]
  114. 114.
    Crowe CD, Keating CD. 2018. Liquid–liquid phase separation in artificial cells. Interface Focus 8:20180032
     [Google Scholar]
  115. 115.
    Marianelli AM, Miller BM, Keating CD. 2018. Impact of macromolecular crowding on RNA/spermine complex coacervation and oligonucleotide compartmentalization. Soft Matter 14:368–78
     [Google Scholar]
  116. 116.
    Ghosh A, Mazarakos K, Zhou HX. 2019. Three archetypical classes of macromolecular regulators of protein liquid–liquid phase separation. PNAS 116:19474–83
     [Google Scholar]
  117. 117.
    Lemetti L, Hirvonen S-P, Fedorov D, Batys P, Sammalkorpi M et al. 2019. Molecular crowding facilitates assembly of spidroin-like proteins through phase separation. Eur. Polym. J. 112:539–46
     [Google Scholar]
  118. 118.
    Schuster BS, Reed EH, Parthasarathy R, Jahnke CN, Caldwell RM et al. 2018. Controllable protein phase separation and modular recruitment to form responsive membraneless organelles. Nat. Commun. 9:2985
     [Google Scholar]
  119. 119.
    McLaurin J, Charkrabartty A. 1996. Membrane disruption by Alzheimer β-amyloid peptides mediated through specific binding to either phospholipids or gangliosides. Implications for neurotoxicity. J. Biol. Chem. 271:26482–89
     [Google Scholar]
  120. 120.
    Zardeneta G, Horowitz PM. 1992. Analysis of the perturbation of phospholipid model membranes by rhodanese and its presequence. J. Biol. Chem. 267:24193–98
     [Google Scholar]
  121. 121.
    Herrig A, Janke M, Austermann J, Gerke V, Janshoff A, Steinem C. 2006. Cooperative adsorption of ezrin on PIP2-containing membranes. Biochemistry 45:13025–34
     [Google Scholar]
  122. 122.
    Haggerty L, Lenhoff AM. 1993. Analysis of ordered arrays of adsorbed lysozyme by scanning tunneling microscopy. Biophys. J. 64:886–95
     [Google Scholar]
  123. 123.
    Rabe M, Verdes D, Zimmerman J, Seeger S. 2008. Surface organization and cooperativity during nonspecific protein adsorption events. J. Phys. Chem. B 112:13971–80
     [Google Scholar]
  124. 124.
    Pandey AP, Haque F, Rochet J-C, Hovis JS. 2009. Clustering of α-synuclein on supported lipid bilayers: role of anionic lipid, protein, and divalent ion concentration. Biophys. J. 96:540–51
     [Google Scholar]
  125. 125.
    Nygren H. 1993. Nonlinear kinetics of ferritin adsorption. Biophys. J. 65:1508–12
     [Google Scholar]
  126. 126.
    Perevozchilova T, Nanda H, Nesta DP, Roberts CJ. 2015. Protein adsorption, desorption, and aggregation mediated by solid-liquid interfaces. J. Pharm. Sci. 104:1946–59
     [Google Scholar]
  127. 127.
    Calonder C, Tie Y, Van Tassel PR. 2001. History dependence of protein adsorption kinetics. PNAS 98:10664–69
     [Google Scholar]
  128. 128.
    Gorbenko GP, Ioffe VM, Kinnunen PKJ. 2007. Binding of lysozyme to phospholipid bilayers: evidence for protein aggregation upon membrane association. Biophys. J. 93:140–53
     [Google Scholar]
  129. 129.
    Melo AM, Fedorov A, Prieto M, Coutinho A. 2014. Exploring homo-FRET to quantify the oligomer stoichiometry of membrane-bound proteins involved in a cooperative partition equilibrium. Phys. Chem. Chem. Phys. 16:18105–17
     [Google Scholar]
  130. 130.
    Fernández A, Berry RS. 2003. Proteins with H-bond packing defects are highly interactive with lipid bilayers: implications for amyloidogenesis. PNAS 100:2391–96
     [Google Scholar]
  131. 131.
    Ditlev JA. 2021. Membrane-associated phase separation: organization and function emerge from a two-dimensional milieu. J. Mol. Cell Biol. 13:319–24
     [Google Scholar]
  132. 132.
    Mitchison TJ. 2020. Beyond Langmuir: surface-bound macromolecule condensates. Mol. Biol. Cell 31:2502–8
     [Google Scholar]
  133. 133.
    Snead WT, Gladfelter AS. 2019. The control centers of biomolecular phase separation: how membrane surfaces, PTMs, and active processes regulate condensation. Mol. Cell 76:295–305
     [Google Scholar]
  134. 134.
    Alberti S, Hyman AA. 2021. Biomolecular condensates at the nexus of cellular stress, protein aggregation disease and ageing. Nat. Rev. Mol. Cell Biol. 22:196–213
     [Google Scholar]
  135. 135.
    Lyon AS, Peeples WB, Rosen MK. 2021. A framework for understanding the functions of biomolecular condensates across scales. Nat. Rev. Mol. Cell Biol. 22:215–35
     [Google Scholar]
  136. 136.
    Aprelev A, Rotter M, Etzion Z, Bookchin RM, Briehl RW, Ferrone FA. 2005. The effects of erythrocyte membranes on the nucleation of sickle hemoglobin. Biophys. J. 88:2815–22
     [Google Scholar]
  137. 137.
    Ferrone FA, Hofrichter J, Eaton WA. 1985. Kinetics of sickle hemoglobin polymerization II. A double nucleation mechanism. J. Mol. Biol. 183:611–31
     [Google Scholar]
  138. 138.
    Zhu M, Souillac PO, Ionescu-Zanetti C, Carter SA, Fink AL. 2002. Surface-catalyzed amyloid fibril formation. J. Biol. Chem. 277:50914–22
     [Google Scholar]
  139. 139.
    Byström R, Aisenbrey C, Borowik T, Bokvist M, Lindström F et al. 2008. Disordered proteins: biological membranes as two-dimensional aggregation matrices. Cell Biochem. Biophys. 52:175–89
     [Google Scholar]
  140. 140.
    Ando T, Skolnick J. 2010. Crowding and hydrodynamic interactions likely dominate in vivo macromolecular motion. PNAS 107:18457–62
     [Google Scholar]
  141. 141.
    Kim YC, Best RB, Mittal J. 2010. Macromolecular crowding effects on protein–protein binding affinity and specificity. J. Chem. Phys. 133:205101
     [Google Scholar]
  142. 142.
    Wang Q, Cheung MS. 2012. A physics-based approach of coarse-graining the cytoplasm of Escherichia coli. Biophys. J. 102:2353–61
     [Google Scholar]
  143. 143.
    McGuffee SR, Elcock AH. 2010. Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. PLOS Comput. Biol. 6:e1000694
     [Google Scholar]
  144. 144.
    Bortot LO, Bashardanesh Z, van der Spoel D. 2020. Making soup: preparing and validating models of the bacterial cytoplasm for molecular simulation. J. Chem. Inf. Model. 60:322–31
     [Google Scholar]
  145. 145.
    Feig M, Yu I, Wang P, Nawrocki G, Sugita Y. 2017. Crowding in cellular environments at an atomistic level from computer simulations. J. Phys. Chem. B 121:8009–25
     [Google Scholar]
  146. 146.
    Yu I, Mori T, Ando T, Harada Y, Jung J et al. 2016. Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm. eLife 5:e19274
     [Google Scholar]
  147. 147.
    Feig M, Sugita Y. 2013. Reaching new levels of realism in modeling biological macromolecules in cellular environments. J. Mol. Graph. Model. 45:144–56
     [Google Scholar]
  148. 148.
    Andrews CT, Elcock AH. 2013. Molecular dynamics simulations of highly crowded amino acid solutions: comparisons of eight different force field combinations with experiment and with each other. J. Chem. Theory Comput. 9:4585–602
     [Google Scholar]
  149. 149.
    Ploetz EA, Karunaweera S, Bentenitis N, Chen G, Dai S et al. 2021. Kirkwood–Buff-derived force field for peptides and proteins: philosophy and development of KBFF20. J. Chem. Theory Comput. 17:2964–90
     [Google Scholar]
  150. 150.
    Yoo J, Aksimentiev A. 2018. New tricks for old dogs: improving the accuracy of biomolecular force fields by pair-specific corrections to non-bonded interactions. Phys. Chem. Chem. Phys. 20:8342–449
     [Google Scholar]
  151. 151.
    Minton AP. 2020. Simple calculation of phase diagrams for liquid–liquid phase separation in solutions of two macromolecular solute species. J. Phys. Chem. B 124:2363–70
     [Google Scholar]
  152. 152.
    Davis CM, Gruebele M. 2021. Cellular sticking can strongly reduce complex binding by speeding dissociation. J. Phys. Chem. B 125:3815–23
     [Google Scholar]
  153. 153.
    Komatsubara AT, Goto Y, Kondo Y, Matsuda M, Aoki K. 2019. Single-cell quantification of the concentrations and dissociation constants of endogenous proteins. J. Biol. Chem. 294:6062–72
     [Google Scholar]
  154. 154.
    Phillip Y, Kiss V, Schreiber G. 2012. Protein binding dynamics imaged in a living cell. PNAS 109:1461–66
     [Google Scholar]
  155. 155.
    Phillip Y, Schreiber G. 2013. Formation of protein complexes in crowded environments – from in vitro to in vivo. FEBS Lett 587:1046–52
     [Google Scholar]
  156. 156.
    Sadaie W, Harada Y, Matsuda M, Aoki K. 2014. Quantitative in vivo fluorescence cross-correlation analyses highlight the importance of competitive effects in the regulation of protein-protein interactions. Mol. Cell. Biol. 34:3272–90
     [Google Scholar]
  157. 157.
    Shi X, Foo YH, Sudhahran T, Chong S-W, Korzh V et al. 2009. Determination of dissociation constants in living zebrafish embryos with single wavelength cross-correlation spectroscopy. Biophys. J. 97:678–86
     [Google Scholar]
  158. 158.
    Speer SL, Zheng W, Jiang X, Chu I-T, Guseman AJ et al. 2021. The intracellular environment affects protein–protein interactions. PNAS 118:e2019918118
     [Google Scholar]
  159. 159.
    Stadmiller SS, Pielak GJ. 2021. Protein-complex stability in cells and in vitro under crowded conditions. Curr. Opin. Struct. Biol. 66:183–92
     [Google Scholar]
  160. 160.
    Sudhahran T, Liu P, Foo YH, Bu W, Lim KB, Wohland T. 2009. Determination of in vivo dissociation constant, KD, of Cdc42-effector complexes in live mammalian cells using single wavelength fluorescence cross-correlation spectroscopy. J. Biol. Chem. 284:13602–9. Erratum. J. Biol. Chem. 284:21100
     [Google Scholar]
  161. 161.
    Sukenik S, Ren P, Gruebele M. 2017. Weak protein–protein interactions in live cells are quantified by cell-volume modulation. PNAS 114:6776–81
     [Google Scholar]
  162. 162.
    Rivas G, Minton AP. 2018. Toward an understanding of biochemical equilibria within living cells. Biophys. Rev. 10:241–53
     [Google Scholar]
  163. 163.
    Ross JL. 2016. The dark matter of biology. Biophys. J. 111:909–16
     [Google Scholar]
  164. 164.
    Rivas G, Minton AP. 2016. Macromolecular crowding in vitro, in vivo, and in between. Trends Biochem. Sci. 41:970–81
     [Google Scholar]
  165. 165.
    Minton AP. 1995. Confinement as a determinant of macromolecular structure and reactivity. II. Effects of weakly attractive interactions between confined macrosolutes and confining structures. Biophys. J. 68:1311–22
     [Google Scholar]
  166. 166.
    Liu B, Åberg C, van Eerden FJ, Marrink SJ, Poolman B, Boersma AJ. 2017. Design and properties of genetically encoded probes for sensing macromolecular crowding. Biophys. J. 112:1929–39
     [Google Scholar]
  167. 167.
    Davis CM, Deutsch J, Gruebele M. 2020. An in vitro mimic of in-cell solvation for protein folding studies. Protein Sci 29:1060–68
     [Google Scholar]
  168. 168.
    Hou L, Lanni F, Luby-Phelps K. 1990. Tracer diffusion in F-actin and Ficoll mixtures. Toward a model for cytoplasm. Biophys. J. 58:31–43
     [Google Scholar]
  169. 169.
    Sarkar M, Smith AE, Pielak GJ. 2013. Impact of reconstituted cytosol on protein stability. PNAS 110:19342–47
     [Google Scholar]
  170. 170.
    Bermudez JG, Chen H, Einstein LC, Good MC. 2017. Probing the biology of cell boundary conditions through confinement of Xenopus cell-free cytoplasmic extracts. Genesis 55:e23013
     [Google Scholar]
  171. 171.
    Hall D, Minton AP. 2004. Effects of inert volume-excluding macromolecules on protein fiber formation. II. Kinetic models for nucleated fiber growth. Biophys. Chem. 107:299–316
     [Google Scholar]
  172. 172.
    Knowles TPJ, Waudby CA, Devlin GL, Cohen SIA, Aguzzi A et al. 2009. An analytical solution to the kinetics of breakable filament assembly. Science 326:1533–37
     [Google Scholar]
  173. 173.
    Schimmel PH, Gao M, Winter R. 2016. Modulation of the polymerization kinetics of α/β-tubulin by osmolytes and macromolecular crowding. ChemPhysChem 18:189–97
     [Google Scholar]
  174. 174.
    Hall D, Minton AP. 2005. Turbidity as a probe of tubulin polymerization kinetics: a theoretical and experimental re-examination. Anal. Biochem. 345:198–213
     [Google Scholar]
  175. 175.
    Aprelev A, Liu Z, Ferrone FA. 2011. The growth of sickle hemoglobin polymers. Biophys. J. 101:885–91
     [Google Scholar]
  176. 176.
    Kim YE, Hipp MS, Bracher A, Hayer-Hartl M, Hartl FU. 2013. Molecular chaperones in protein folding and proteostasis. Annu. Rev. Biochem. 82:323–55
     [Google Scholar]
  177. 177.
    von Bülow S, Siggel M, Linke M, Hummer G. 2019. Dynamic cluster formation determines viscosity and diffusion in dense protein solutions. PNAS 116:9843–52
     [Google Scholar]
  178. 178.
    Wright MA, Aprile FA, Bellaiche MMJ, Michaels TCT, Müller T et al. 2018. Cooperative assembly of Hsp70 subdomain clusters. Biochemistry 57:3641–49
     [Google Scholar]
  179. 179.
    Kempner ES, Miller JH. 1968. The molecular biology of Euglena gracilis: IV. Cellular stratification by centrifuging. Exp. Cell Res. 51:141–49
     [Google Scholar]
  180. 180.
    Kempner ES, Miller JH. 1968. The molecular biology of Euglena gracilis: V. Enzyme localization. Exp. Cell Res. 51:150–56
     [Google Scholar]
  181. 181.
    Knull H, Minton AP. 1996. Structure within eukaryotic cytoplasm and its relationship to glycolytic metabolism. Cell Biochem. Funct. 14:237–48
     [Google Scholar]
  182. 182.
    Kurganov BI 1985. Control of enzyme activity in reversibly adsorptive enzyme systems. Organized Multienzyme Systems GR Welch 241–70 Orlando, FL: Academic
     [Google Scholar]
  183. 183.
    Srere PA, Jones ME, Mathews CK, eds. 1989. Structural and Organizational Aspects of Metabolic Regulation New York: Wiley-Liss
     [Google Scholar]
  184. 184.
    Chapanian R, Kwan DH, Constantinescu I, Shaikh FA, Rossi NAA et al. 2014. Enhancement of biological reactions on cell surfaces via macromolecular crowding. Nat. Commun. 5:4683
     [Google Scholar]
  185. 185.
    Hoppe T, Minton AP. 2019. An equilibrium model for the combined effect of macromolecular crowding and surface adsorption on the formation of linear protein fibrils. Biophys. J. 108:957–66. Erratum. Biophys. J. 116:2234
     [Google Scholar]
  186. 186.
    Vecchi G, Sormanni P, Mannini B, Vandelli A, Tartaglia GG et al. 2020. Proteome-wide observation of the phenomenon of life on the edge of solubility. PNAS 117:1015–20
     [Google Scholar]
  187. 187.
    Hirokawa N. 1982. Cross-linker system between neurofilaments, microtubules, and membranous organelles in frog axons revealed by the quick-freeze deep-etching method. J. Cell Biol. 94:129–42
     [Google Scholar]
  188. 188.
    Medalia O, Weber I, Frangakis AS, Nicastro D, Gerisch G, Baumeister W. 2002. Macromolecular architecture in eukaryotic cells visualized by cryoelectron tomography. Science 298:1209–13
     [Google Scholar]
  189. 189.
    Stadmiller SS, Aguilar JS, Parnham S, Pielak GJ. 2020. Protein–peptide binding energetics under crowded conditions. J. Phys. Chem. B 124:9297–309
     [Google Scholar]
  190. 190.
    Batra J, Xu K, Qin S, Zhou H-X. 2009. Effect of macromolecular crowding on protein binding stability: modest stabilization and significant biological consequences. Biophys. J. 97:906–11
     [Google Scholar]
  191. 191.
    Guseman AJ, Pielak GJ. 2017. Cosolute and crowding effects on a side-by-side protein dimer. Biochemistry 56:971–76
     [Google Scholar]
  192. 192.
    Phillip Y, Sherman E, Haran G, Schreiber G. 2009. Common crowding agents have only a small effect on protein–protein interactions. Biophys. J. 97:875–85
     [Google Scholar]
  193. 193.
    Zhou YL, Liao JM, Chen J, Liang Y 2006. Macromolecular crowding enhances the binding of superoxide dismutase to xanthine oxidase: implications for protein–protein interactions in intracellular environments. Int. J. Biochem. Cell Biol. 38:1986–94
     [Google Scholar]
  194. 194.
    Alfonso C, del Castillo U, Martín I, Muga A, Rivas G. 2015. Sedimentation equilibrium analysis of ClpB self-association in diluted and crowded solutions. Adv. Enzymol. 562:135–60
     [Google Scholar]
  195. 195.
    Aguilar X, Weise CF, Sparrman T, Wolf-Watz M, Wittung-Stafshede P. 2011. Macromolecular crowding extended to a heptameric system: the co-chaperonin protein 10. Biochemistry 50:3034–44
     [Google Scholar]
  196. 196.
    Snoussi K, Halle B. 2005. Protein self-association induced by macromolecular crowding: a quantitative analysis by magnetic relaxation dispersion. Biophys. J. 88:2855–66
     [Google Scholar]
/content/journals/10.1146/annurev-biochem-040320-104151
Loading
Influence of Nonspecific Interactions on Protein Associations: Implications for Biochemistry In Vivo
Annual Review of Biochemistry 91, 321 (2022); https://doi.org/10.1146/annurev-biochem-040320-104151
/content/journals/10.1146/annurev-biochem-040320-104151
/content/journals/10.1146/annurev-biochem-040320-104151
Loading

Data & Media loading...

Supplementary Data

  • Download the Supplemental Material (PDF). Includes Supplemental Equations 1-4 and Supplemental Figures 1-5.

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error