New developments. Exciting developments in the field of protein-lipid interactions.

History

The fluid mosaic model is one of the most powerful models depicting a biomembrane and the way how lipids are organized in a bilayer and the way proteins are inserted in or bound to such a bilayer of lipids [1]. Recent developments in this area are nicely reviewed elsewhere [2].

The notion that lipids serve more functions than simple creating a barrier in cells is nicely described in a classic but still relevant review by Dowhan [3]. Basically, the title: “Molecular basis for membrane phospholipid diversity: why are there so many lipids?” says it all.

Protein-lipid interactions

Numerous processes in biology have been recognized where protein-lipid interactions play a role [4-6]. Please be aware that this only serves as a small impression since this rapidly evolving field produces interesting new papers constantly.

Tools to investigate protein-lipid interactions

An interesting prediction method has been published that could serve as a tool to create so-called Eisenberg plots [7]. In figure 1 you see an example depicted.

Figure 1: Example of an Eisenberg plot. Indicated are the three domains: globular, surface seeking and Transmembrane. Taken from [7].

Though the math behind the Eisenberg plot approach is quite complicated [8] its use is not. Rather straightforward it can be predicted that once one or more regions (of let’s say 20 amino acid residues long) are located in the transmembrane region you are presumably dealing with a membrane protein. The same is true for surface seeking results. The regions located in the globular region appear to be more complicated to interpreted (see [7], [9] for discussions on this). 

One way to distinguish between a soluble and a membrane bound protein is the use of the Heliquest software [10]. 

That can serve as a potential useful tool in protein-lipid research is the so-called Helical wheel plot. Using the Heliquest program it is possible to generate such a plot easily (see figure 2).

Figure 2: Helical wheel plot example.

In this example the sequence of Bombolitin is used, which is a known bee venom. In this particular case it is clear that the sequence corresponds to an amphiphilic helix and is a typical surface seeking helix. One side is predominantly hydrophobic and the other side is hydrophilic and charged. This a clear feature of a sequence corresponding to a surface seeking one.

Indeed, using the Heliquest program it is clear that the lipid binding discrimination factor (0.944×0.430 + 0.33×3 = 1.40) predicts that this region is clearly a potential lipid binding region.

This software can be used to create a Eisenberg plot [8] and in combination Heliquest [10] and Heliquest based Eisenberg approach [7] it can be used as the ultimate lipid binding region predictor. 

The Heliquest generated Eisenberg Plot approach identified lipid binding regions in protein translocation motor proteins  [11], in cytoplasmic/periplasmic loops of membrane proteins [12] and specific features of amphitropic proteins [13].

The method is used in various different fields, such as:

Antimicrobial peptides [14]

Viruses [15]

Cell penetrating peptides [16]

Membrane anchoring of proteins [17]

Cereal proteins and peptides [18]

Food proteins and peptides [19]

Experimentally a variety of methods have been developed that allows you to study protein-lipid interactions, such as:

(Trp) Fluorescence [20, 21]

FRET [22]

ESR [23, 24]

Circular Dichroism [25]

NMR [26]

Monolayer/Langmuir technique [27]

General biochemical approaches [28]

An interesting recent example in the area of protein-lipid interactions demonstrates how bioinformatics can be the 'missing link' between model system studies and in vitro/in vivo experiment [29]. That substantiates new models, see Figure 3.

Figure 3: Model for the initial steps of protein translocation. Taken from [29].

References:

[1] Singer SJ, Nicolson GL. The fluid mosaic model of the structure of cell membranes. Science. 1972 Feb 18;175(4023):720-31.

[2] Vereb G, Szöllosi J, Matkó J, Nagy P, Farkas T, Vigh L, Mátyus L, Waldmann TA, Damjanovich S. Dynamic, yet structured: The cell membrane three decades after the Singer-Nicolson model. Proc Natl Acad Sci U S A. 2003 Jul 8;100(14):8053-8.

[3] Dowhan W. Molecular basis for membrane phospholipid diversity: why are there so many lipids? Annu Rev Biochem. 1997;66:199-232.

[4] Hicks DA, Nalivaeva NN, Turner AJ. Lipid rafts and Alzheimer’s disease: protein-lipid interactions and perturbation of signaling. Front Physiol. 2012;3:189.

[5] van Klompenburg W, de Kruijff B. The role of anionic lipids in protein insertion and translocation in bacterial membranes. J Membr Biol. 1998 Mar 1;162(1):1-7.

[6] Bandorowicz-Piku?a J. Lipid-binding proteins as stabilizers of membrane microdomains–possible physiological significance. Acta Biochim Pol. 2000;47(3):553-64.

[7] Keller RCA. New user-friendly approach to obtain an eisenberg plot and its use as a practical tool in protein sequence analysis. Int J Mol Sci. 2011;12(9):5577-91.

[8] Eisenberg D, Schwarz E, Komaromy M, Wall R. Analysis of membrane and surface protein sequences with the hydrophobic moment plot. J Mol Biol. 1984 Oct 15;179(1):125-42.

[9] Phoenix DA, Stanworth A, Harris F. The hydrophobic moment plot and its efficacy in the prediction and classification of membrane interactive proteins and peptides. Membr Cell Biol. 1998;12(1):101-10.

[10] Gautier R, Douguet D, Antonny B, Drin G. HELIQUEST: a web server to screen sequences with specific alpha-helical properties. Bioinformatics. 2008 Sep 15;24(18):2101-2.

[11] Keller RCA. The prediction of novel multiple lipid-binding regions in protein translocation motor proteins: a possible general feature. Cell Mol Biol Lett. 2011 Mar;16(1):40-54.

[12] Keller RCA. Prediction of Lipid-Binding Regions in Cytoplasmic and Extracellular Loops of Membrane Proteins as Exemplified by Protein Translocation Membrane Proteins. J Membr Biol. 2012 Sep 9. [Epub ahead of print]

[13] Keller RCA Identification and in silico analysis of helical lipid binding regions in proteins belonging to the amphitropic protein family. J. Biosci. 2014;39:1–13] DOI 10.1007/s12038-014-9479-z 

[14] Torres, M. D., Sothiselvam, S., Lu, T. K., & de la Fuente-Nunez, C. (2019). Peptide design principles for antimicrobial applications. Journal of molecular biology, 431(18), 3547-3567

[15] Heldt, C. L., Zahid, A., Vijayaragavan, K. S., & Mi, X. (2017). Experimental and computational surface hydrophobicity analysis of a non-enveloped virus and proteins. Colloids and Surfaces B: Biointerfaces, 153, 77-84.

 

[16] Hemmati, S., Behzadipour, Y., & Haddad, M. (2020). Decoding the proteome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for cell-penetrating peptides involved in pathogenesis or applicable as drug delivery vectors. Infection, Genetics and Evolution, 85, 104474.

 

[17] Lhor, M., Bernier, S. C., Horchani, H., Bussières, S., Cantin, L., Desbat, B., & Salesse, C. (2014). Comparison between the behavior of different hydrophobic peptides allowing membrane anchoring of proteins. Advances in colloid and interface science, 207, 223-239.

 

[18] Keller, R. C. (2018). Identification of potential lipid binding regions in cereal proteins and peptides with the use of bioinformatics. Journal of Cereal Science, 80, 128-134.

 

[19] Keller, R. C. (2018). Identification of Possible Lipid Binding Regions in Food Proteins and Peptides and Additional In Silico Analysis. Food Biophysics, 13(2), 139-146.

 

[20] Killian, JA, Keller, RCA, Struyve, M., De Kroon, AIP.M, Tommassen, J., De Kruijff, B. Tryptophan fluorescence study on the interaction of the signal peptide of the Escherichia coli outer membrane protein PhoE with model membranes. Biochemistry. 1990;29(35):8131-8137.https://doi.org/10.1021/bi00487a021

[21] Brown MP, Royer C. Fluorescence spectroscopy as a tool to investigate protein interactions. Curr Opin Biotechnol. 1997 Feb 1;8(1):45-9.

[22] Keller, RCA, Ten Berge, D, Nouwen, N, Snel, MME, Tommassen, J, Marsh, D, & De Kruijff, B. Mode of insertion of the signal sequence of a bacterial precursor protein into phospholipid bilayers as revealed by cysteine-based site-directed spectroscopy. Biochemistry. 1996;35(9):3063-3071. https://doi.org/10.1021/bi951870+

[23] Marsh D. Electron spin resonance in membrane research: protein-lipid interactions. Methods. 2008 Oct;46(2):83-96.

[24] Keller, RCA, Snel, MM, de Kruijff, B., Marsh, D. SecA restricts, in a nucleotide-dependent manner, acyl chain mobility up to the center of a phospholipid bilayer. FEBS lett. 1995;358(3):251-254. https://doi.org/10.1016/0014-5793(94)01439-8

[25] Keller, RCA, Killian, JA, De Kruijff, B. Anionic phospholipids are essential for. alpha.-helix formation of the signal peptide of prePhoE upon interaction with phospholipid vesicles. Biochemistry. 1992;31(6):1672-1677. https://doi.org/10.1021/bi00121a014

[26] Killian, JA, De Jong, AM, Bijvelt, J, Verkleij, AJ, De Kruijff, B. Induction of non‐bilayer lipid structures by functional signal peptides. EMBO J. 1990;9(3):815-819. https://doi.org/10.1002/j.1460-2075.1990.tb08178.x 

[27] Breukink, E, Keller, RCA, de Kruijff, B. Nucleotide and negatively charged lipid‐dependent vesicle aggregation caused by SecA. FEBS Lett. 1993;331(1-2):19-24. https://doi.org/10.1016/0014-5793(93)80289-7 

[28] Zhao H, Lappalainen P. A simple guide to biochemical approaches for analyzing protein-lipid interactions. Mol Biol Cell. 2012 Aug;23(15):2823-30.

[29] Keller, RCA. Comparison of In Silico Signal Sequence-Phospholipid Results with Described In Vitro and In Vivo Protein Translocation Studies Seems to Underscore the Significance of Phospholipids. Lipidology 2024;1(1):3-17. https://doi.org/10.3390/lipidology1010002