Multivalent Lectin Ligands
Dissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.)
vorgelegt von Rohse, Philipp
an der
Mathematisch-Naturwissenschaftliche Sektion Fachbereich Chemie
Tag der mündlichen Prüfung: 21.07.2017 1. Referent: Prof. Dr. Valentin Wittmann 2. Referent: Prof. Dr. Malte Drescher 3. Referentin: Prof. Dr. Tanja Gaich
Diese Arbeit entstand im Zeitraum von November 2012 bis Februar 2017 an der Universität Konstanz im Fachbereich Chemie in der Arbeitsgruppe von Prof. Dr. Valentin Wittmann.
Das Projekt wurde durch ein Stipendium der Graduiertenschule Chemische Biologie der Universität Konstanz gefördert.
Zunächst gilt mein Dank Prof. Dr. Valentin Wittmann für das Überlassen des interessanten Themas und die große Freiheit, die ich bei der Umsetzung des Projekts genießen durfte. Insbesondere danke ich ihm für die angenehme Arbeitsatmosphäre und das Vertrauen mich als „Externen“ in die Gruppe aufzunehmen.
Prof. Dr. Malte Drescher und Prof. Dr. Tanja Gaich danke ich für die Übernahme des Zweitgutachtens und des Prüfungsvorsitzes.
Sabrina Weickert von der Arbeitsgruppe Drescher danke ich für die kurze aber erfolgreiche und unkomplizierte Zusammenarbeit und die Durchführung der EPR Experimente.
Rose Rosenberg von der Arbeitsgruppe Cölfen danke ich für die Durchführung der AUC Experimente.
Mein Dank geht auch an Dr. David Witte und Prof. Dr. Alexander Titz für die Beratung am ITC.
Ein besonderer Dank geht an die gesamte AG Wittmann für ein sehr angenehmes Arbeitsklima und viel Spaß auf den zahlreichen AG Retreats, Ausflügen, Weihnachtsfeiern, etc. Oliver Baudendistel danke ich für die Freundschaft und den Humor, was half manche Widrigkeiten nicht allzu ernst zu nehmen.
Meinen Laborpartnern Daniel Matzner, Christine Lasogga, Olga Grotz und besonders Jeremias „JEGA“
Dold danke ich für ein stets angenehmes und stressfreies Miteinander in L817. Daniel Wieland danke ich für sein musikalisches Engagement in meiner Band. Ivan Zemskov möchte ich für seine Begeisterung dafür doch die schwierigere Bergtour zu machen (Hohe Aiffner Spitz ruft!) und die vielen trink- und essbaren Spezialitäten danken. Torben Seitz danke ich für die Überlassung seines Labors damit ich als „Neuer“ nicht direkt in den Exilgang verbannt wurde und die Flower Power Challenge.
Ein besonderer Dank geht an „AG-Mama“ Monica Boldt die immer ein offenes Ohr für Probleme und Sorgen hatte. Anne-Katrin Späte danke ich für die kritische Durchsicht dieser Arbeit. Rebecca Faißt danke ich für die hervorragende Umsetzung meines Proposals und drücke die Daumen, dass es ein Erfolg wird!
Dank gilt auch meinen Mitarbeiterpraktikanten Yannic Altrichter, Judith Schwaderer, Oliver Rudolphi und Eva Schiebel sowie meinen Bachelorstudenten Philipp Lohner, Caroline Benz und Cora Dieterich für ihre tatkräftige Unterstützung.
Der Uni Big-Band, Tim Strohmeier, Benedikt Auer, Simon Schleinitz, Markus Schilling, Lukas Götz und Sarah Frommknecht danke ich ganz besonders für das gemeinsame Musikmachen.
Meinen Schwiegereltern danke ich für die verlässliche Unterstützung in Form von Kinderbetreuung, Krisenberatung und die vielen gemeinsamen Urlaube in den Bergen.
Table of Contents
1 Introduction ... 1
2 State of the Art ... 3
2.1 Lectins ... 3
2.1.1 General Considerations ... 3
2.1.2 Wheat Germ Agglutinin ... 4
2.2 Multivalency ... 6
2.3 Multivalent Lectin Ligands ... 9
2.3.1 Polymeric Ligands... 9
2.3.2 Dendritic Ligands ... 9
2.3.3 Other Glycoclusters ... 10
2.3.4 Ligands Based on Nanomaterials ... 11
2.3.5 Ligands Based on Self-Assembly or Combinatorial Chemistry ... 12
2.3.6 Multivalent Ligands for WGA ... 15
2.4 Methods for the Investigation of Multivalent Interactions. ... 18
2.4.1 Isothermal Titration Calorimetry ... 18
2.4.2 Enzyme-Linked Lectin Assay ... 21
2.4.3 Dynamic Light Scattering ... 22
2.4.4 Electron Paramagnetic Resonance Spectroscopy ... 23
3 Assignment of Task ... 25
3.1 Mechanistic Investigation of High Affinity Glycopeptides Binding to WGA ... 25
3.2 New Concept for Scaffolds – Linear Lectin Ligands ... 27
4 Results and Discussion ... 29
4.1 Mechanistic Investigation of High Affinity Glycopeptides Binding to WGA ... 29
4.1.1 Design of Compounds ... 29
4.1.2 Synthesis of Neoglycopeptides ... 31
4.1.3 Influence of Conformational Preorganization of Tetravalent Ligands on Binding Affinity ... 33
4.1.4 Relevance of the Sugars at Positions D-Dab2 and D-Dab7 ... 35
4.1.5 Dynamic Light Scattering ... 36
4.1.6 Precipitation Studies ... 38
4.1.7 Analytical Ultracentrifugation ... 39
4.1.8 Discussion of Possible Binding Modes ... 40
4.1.9 Trivalent Ligands ... 42
4.2.3 Synthesis of Linear Lectin Ligands ... 56
4.2.4 Binding Assays ... 58
4.2.5 Precipitation Studies ... 60
4.2.6 Dynamic Light Scattering ... 61
4.2.7 Synthesis of Spin-Labeled Linear Lectin Ligands ... 62
4.2.8 EPR Measurements ... 65
4.2.9 Discussion of Binding Modes ... 67
4.3 Competitive ITC Experiments ... 71
4.3.1 Obstacles of High Affinity Binding and ITC ... 71
4.3.2 Competitive ITC with Tetravalent Ligands ... 72
4.3.3 Competitive ITC with a Multivalent Competitor ... 76
4.3.4 Deconvolution of High Binding Affinities Using Temperature ... 80
5 Summary and Outlook ... 83
6 Zusammenfassung ... 87
7 Experimental Section ... 91
7.1 General Methods ... 91
7.2 Synthesis of Glycopeptides ... 92
7.2.1 General Procedures ... 92
7.2.2 Carbohydrate Synthesis ... 94
7.2.3 Amino Acids ... 95
7.2.4 Peptide Synthesis... 97
7.3 Linear Lectin Ligands ... 104
7.3.1 General Procedures ... 104
7.3.2 Carbohydrates ... 104
7.3.3 Divalent Ligands ... 105
7.3.4 Synthesis of Oligoethylene Glycols and Derivatives ... 108
7.3.5 Synthesis of Oligoethylene Glycol Carbonates ... 112
7.3.6 Synthesis of Linear Lectin Ligands ... 114
7.3.7 Synthesis of Spin Labeled Linear Lectin Ligands ... 121
7.3.8 Divalent Galactose Ligand ... 129
7.4 Isothermal Titration Calorimetry ... 131
7.4.1 Buffer solution ... 131
7.4.2 Preparation of Samples ... 131
7.4.3 Thermograms of Glycopeptides ... 132
7.4.4 Thermograms of Divalent Ligands ... 135
7.4.5 Thermograms of Linear Lectin Ligands ... 136
7.5 Dynamic Light Scattering ... 139
7.6 Precipitation Assay ... 139
7.7 Enzyme-Linked Lectin Assay... 139
7.7.1 Solutions ... 139
7.7.2 Assay for Determination of IC50 Values ... 140
7.7.3 Evaluation of Data ... 140
7.8 Selected NMR spectra ... 142
7.9 Selected HPLC Chromatograms ... 158
8 References ... 163
Abbreviations
ABTS 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)
Ala L-alanine
All allyl
Aloc allyloxycarbonyl
anal analytical
AUC analytical ultracentrifugation
Boc tert-butyloxycarbonyl
BSA bovine serum albumin
calcd calculated
Con A Concanavalin A
D-Dab D-diaminobutyric acid
DEER double electron electron resonance DGL Dioclea grandiflora lectin
DLS dynamic light scattering
DMF N,N-dimethylformamide
DMSO Dimethyl sulfoxide
EHEC enterohemorrhagic E. coli
ELISA enzyme-linked immunosorbent assay ELLA enzyme-linked lectin assay
EPR electron paramagnetic resonance ESI electron spray ionization
FA formic acid
FC flash column chromatography
Fmoc fluorenylmethyloxycarbonyl
Gal D-galactose
GalNAc N-acetyl- D-galactosamine GlcNAc N-acetyl- D-glucosamine
Glu L-glutamic acid
HBTU 2-(1H-benzotriazol-1-yl)-1,1,3,3-tetramethyluronium hexafluorophosphate
HOBt 1-hydroxybenzotriazole
HPLC high performance liquid chromatography
HRP horseradish peroxidase
ITC isothermal titration calorimetry
LC liquid chromatography
Lys L-lysine
Man D-mannose
MHz megahertz
MPLC medium pressure liquid chromatography
MS mass spectrometry
MTBE methyl tert-butylether NeuNAc N-acetylneuraminic acid NMP N-methyl-2-pyrrolidone
NMR nuclear magnetic resonance
OEG oligo(ethylene) glycol
PBS phosphate buffered saline
PDITC phenylene diisothiocyanat
PSM porcine stomach mucin
QCM quartz crystal microbalance
Rf retention factor
RP HPLC reversed phase high performance liquid chromatography
rpm revolutions per minute
RT room temperature
sat saturated
SPPS solid phase peptide synthesis
SPR surface plasmon resonance
TFA trifluoroacetic acid
TFE 2,2,2-trifluoroethanol
THF tetrahydrofuran
TIS triisopropylsilane
TLC thin layer chromatography
Val L-valine
WGA wheat germ agglutinin
Xaa any amino acid
Carbohydrates are the most abundant biomolecules on earth. They are present in all organisms functioning as energy storage, providing stability to cells, are part of the backbone of nucleic acids, and can be found as conjugates of many proteins and lipids. The basic building blocks of all bigger carbohydrate structures are monosaccharides. There are many different monosaccharides of which the most commonly known is glucose. Both, starch and cellulose, the main energy and stability providing molecules, consist of glucose. The only difference between the two structures is the configuration at one carbon atom but it leads to very different properties.[1] In addition to starch and cellulose many other polysaccharides exist, for example hyaluronate which is part of cartilage, joints and tendons or chitin which is part of the insect’s skeletons.[2]
DNA and proteins only form linear polymers and in the case of DNA the number of possible sequences is also limited by the small number of possible monomers. In case of carbohydrates the monosaccharides can be interconnected via several hydroxyl groups. Thus, even for small oligosaccharides the number of possible isomers is very high. For a pentapeptide from a set of 20 amino acids 6.4 · 107 possible isomers exist, whereas for a pentasaccharide from a set of 20 hexoses including linear and branched isomers the number of possible isomers is 2.7 · 1011.[3] This makes carbohydrates ideal molecules to store information. Taking a closer look on the cell membrane, for example, it does not only consist of a lipid bilayer but the lipids are decorated with oligosaccharides and many glycoproteins are embedded in the lipid layer extending their carbohydrate structures into the extracellular matrix. This carbohydrate layer on the cell surface is called the glycocalyx.[4] It provides the cell with the ability to communicate with other cells. For the readout of the information a class of proteins called lectins is responsible. Lectins have binding sites which are specific for certain mono- and oligosaccharides and they are also present on cell surfaces allowing cell-cell adhesion and communication mediated by the carbohydrate-lectin interactions.
These interactions between carbohydrates and lectins are important and take part in many cell recognition processes. For example, the first step of a virus to infect a cell is the attachment to the cell surface. In the case of the influenza virus this is mediated by hemagglutinin, a lectin which binds specifically to terminal sialic acid residues that are often part of glycoproteins and glycolipids in the membrane.[5] Another medically important example is the binding of toxins to cells. The cholera toxin possesses a lectin functionality that can bind to the oligosaccharide unit of GM1 which is a ganglioside present in the cell membrane.[6] In animals, selectins enable leukocytes to attach to the endothelial cells of the blood vessels.[7]
Since the oligosaccharides on cell surfaces are usually present in more than one copy and lectins often
binding modes, such as chelating, rebinding, and crosslinking, can be in action. In order to understand and study carbohydrate lectin interactions, artificial multivalent ligands are necessary. Among many other examples, glycopeptides have been successfully employed to create multivalent ligands with high affinities.[11-12] In this work the effect of different structural features of a certain type of glycopeptides on the binding to the plant lectin wheat germ agglutinin (WGA) has been studied. This is important when thinking of creating multivalent, high-affinity ligands that should inhibit the binding of pathogens to cells. The binding mode in action needs to be known to circumvent undesired side effects.
The scaffold which bears the individual carbohydrates plays an important role for the creation of multivalent ligands.[13] A central scaffold to which the carbohydrates are attached to with a linker has proven to be very useful and versatile. Many examples of different chemical nature have been employed reaching from peptides,[11-12, 14-20] calixarenes,[21-24] dendrimers,[14, 16, 18-19, 25-27] silsesquioxanes[28-29] to quantum dots,[30] and nanoparticles[31-35]. Based on earlier studies[11] a new concept for a multivalent scaffold has been developed in this work. The carbohydrates are not attached to the scaffold but they are integrated into the scaffold. This is advantageous as it reduces the overall size of the ligands to a minimum and the embedded carbohydrates have less possibilities to dissociate once bound to the lectin.
For the design of new ligands that are suitable for an application in a specific context it is important to know how the structure of multivalent ligands affects the binding mechanisms to the target lectins. In this work the binding of various ligands to WGA has been analyzed using different techniques such as isothermal titration calorimetry (ITC), enzyme linked lectin assays (ELLA), dynamic light scattering (DLS), precipitation studies, and electron paramagnetic resonance (EPR) spectroscopy. The combination of these methods allowed conclusions on the binding mode of the different ligands. In addition to a suitable binding mode, new ligands have to fulfil other characteristics. Aiming at a medical application these would be selectivity, high affinity, and water solubility, all of which have to be considered in the scaffold design. Knowledge about the interplay of structure, binding mechanisms and binding characteristics paves way for the targeted design of new, efficient ligands
2.1 Lectins
2.1.1 General Considerations
Carbohydrates are part of important biological molecules like nucleic acids, glycoproteins or glycolipids where they are covalently bound. Yet there are also many non-covalent interactions that are mediated by carbohydrates. The binding partners for the saccharides are usually anti-carbohydrate antibodies, carbohydrate processing enzymes or another class of proteins called lectins.[36] A lectin has been defined as “a carbohydrate binding protein of nonimmune origin that agglutinates cells or precipitates polysaccharides or glycoconjugates”[37]. Lectins bind specifically to certain carbohydrates and are characterized according to which monosaccharide they exhibit the highest affinity. The five monosaccharides that act as main binding partners are: N-acetylglucosamine (GlcNAc), N- acetylneuraminic acid (NeuNAc), fucose, galactose (Gal)/N-acetylgalacosamine (GalNAc), or mannose (Man). Based on their structural features, lectins can be further categorized in simple lectins which are rather small structures, mosaic lectins in which the lectin is part of a bigger assembly of protein domains, and macromolecular examples where many copies of proteins form macromolecular structures like bacterial fimbriae.[36] Many lectins exist as oligomers of homologous domains. This leads to more than one carbohydrate binding site, making the lectin multivalent. The binding affinity of monosaccharides to the corresponding lectins is usually low. However, if the monosaccharides are displayed in a multivalent fashion, several lectin-monosaccharide interactions can be in action simultaneously. This may result in a considerably stronger binding. Lectins participate in a plethora of processes. Many can be termed cell recognition events. A lot of lectins and carbohydrate structures are situated at the outside of the cell membrane which makes them easily accessible to each other. As already indicated they take part in many different pathologic events. Not only viral surface lectins mediate the infection of cells but also many bacteria take advantage of lectin carbohydrate interactions to interact with their host cells.
Adhesion of Pseudomonas aeruginosa, a pathogen that can lead to acute and chronic infections especially in the respiratory tract, to the host epithelial cells is mediated by the lectins LecA and LecB.[38]
E. coli possess fimbriae with affinity for carbohydrate structures that allows the adhesion on host surfaces.[39] Galectins which are binding specifically to galactosides are associated with cancer[40], galectin-3 for example can promote metastasis[41-42]. Also various toxins carry a lectin subunit that enables the toxin to bind to the membrane of its target, followed by endocytosis and the toxic effect of the toxin subunit. Examples are cholera toxin[43-44], shiga toxin[6, 45], or ricin[46]. Being involved in many diseases, lectins could be a potent medical target to interfere or inhibit the above mentioned processes.
Lectins
phagocytosis.[47] Selectins, C-type lectins that need Ca2+ for the carbohydrate binding, are found on leukocytes and allow the adhesion of the latter to endothelial cells of the blood vessels. That enables the direction of leukocytes to cites of inflammation.[7] P-type lectins participate in transport of lysosomal enzymes to their destination.[48]. The manifold functions of lectins offer many opportunities for research in this field.
2.1.2 Wheat Germ Agglutinin
One example of a multivalent lectin is wheat germ agglutinin. It was first discovered when tumor cells were treated with wheat germ lipase which lead to an aggregation of the tumor cells.[49] This could be traced back to the presence of an impurity in the lipase samples. The impurity was identified as a lectin that was termed wheat germ agglutinin (WGA)[50] and could be isolated in pure form[51]. Subsequent studies established the affinity of the lectin for N-acetylglucosamine (GlcNAc)[52] 1, its oligomers, for example N,N-diacetylchitobiose[51, 53] 2, and N-acetylneuraminic acid (NeuNAc)[54] 3 (Figure 1). Soon after, the first crystal structure of WGA could be obtained[55-56] and paved way for many following studies describing the binding of the saccharides to the lectin[54, 57-59].
Figure 1 GlcNAc 1, N,N-diacetylchitobiose 2, and NeuNAc 3 that can bind to wheat germ agglutinin.
At neutral pH, WGA exists as a homodimer with a mass of 34 kDa (Figure 2).[60] The monomers are built of four domains (A, B, C, and D) each containing four disulfide bridges. The dimer is very stable in solution and can be dissociated only at low or high pH.[56] It contains eight binding sites for carbohydrates which are located at the interface of the two monomers and are formed by contribution of two domains each. The binding sites are grouped in primary and secondary binding sites. The primary binding sites, which are termed B1C2, B2C1, C1B2 and C2B1 after the domains that are involved, exhibit higher affinities for the ligands. On the contrary the secondary binding sites A1, A2, D1A2 and D2A1 often remained unoccupied in crystal structures of the protein with its ligands.[57, 59] Each domain contributes by aromatic or polar residues to the binding with the exception of binding sites A1 and A2 where the polar contributions of domains D1 and D2 are lacking.[61]
Figure 2 Crystal structure of WGA. The protein is shown as surface representation with domains of monomer 1 colored red to yellow and domains of monomer 2 colored cyan to dark blue, with the binding sites marked as yellow ellipses. Picture created using USCF Chimera 1.10.1[62] based on PDB ID: 2X52.[11]
The binding affinity of WGA for GlcNAc has first been determined by an fluorescence assay.[63] The obtained Kd was 1.4 mM which is comparable to the later assessed Kd of 2.6 mM derived from isothermal titration calorimetry.[64] For the oligomers of GlcNAc the affinity rises with each monomer up to a Kd of 81 µM for the trisaccharide.[64]
The role of WGA in wheat has been in discussion for a long time. Early studies showed evidence for the inhibition of the growth of certain fungi by WGA.[65-66] Others reported increased WGA levels in cells under stress conditions and proposed a role as radical scavenger due to the high cystine content.[67]
It has also been suggested that WGA plays a beneficial role in the interaction of wheat with nitrogen fixing bacteria.[68] A more recent study revealed increased bacterial adhesion to wheat roots treated with WGA.[69] In summary, the role of WGA in wheat remains still vague and cannot be clearly defined. Yet its eight binding sites make it a very useful and often used model to study multivalent carbohydrate- lectin interactions.
Multivalency
2.2 Multivalency
Multivalency in biological systems has attracted a lot of interest in the last decades.[9] Multivalent interactions take place “between an m-valent receptor and an n-valent ligand (m, n > 1)”[70]. This can lead to strongly enhanced binding affinities compared to a corresponding monovalent interaction.
Binding of viruses,[71] bacteria[72-76], or toxins[77] to target cells strongly depends on multivalent interactions mediated by lectins. The creation of ligands capable of binding strongly to the pathogenic receptors and thus prevent the pathogen from binding to its target has great potential. In case of multivalent carbohydrate-lectin interactions the binding enhancement has been termed the “Cluster Glycoside Effect”.[78-79] Three general mechanisms which lead to the cluster glycoside effect are in discussion: statistical rebinding, chelating and crosslinking (Figure 3).
Figure 3 Multivalent binding mechanisms: (A) Statistical rebinding, (B) chelating, (C) crosslinking.
Statistical rebinding can occur in all multivalent systems (Figure 3 A).[80] A multivalent ligand is bound to its receptor with on epitope. The binding is enhanced since additional binding epitopes are in close proximity to the binding site and can easily rebind when a bound epitope is released. In chelating binding modes, one ligand is capable to bridge several binding sites on one receptor simultaneously (Figure 3 B). The prerequisites are linkages of sufficient length between the individual epitopes of the ligand. The third binding mechanism involves crosslinking of receptors. A ligand binds to more than one receptor and bigger networks are formed (Figure 3 C).[79]
The binding affinity of a ligand to its receptor is quantified in terms of the association (or equilibrium) constant Ka. For the binding of a ligand (L) to a receptor (R) it is defined as 𝐾𝑎=[𝐿][𝑅][𝐿𝑅].
The dissociation constant Kd, which is often used instead of the association constant in biological contexts, is the reciprocal of the affinity constant: 𝐾𝑑=𝐾1
𝑎. The Ka value is linked to the free enthalpy
G via
∆𝐺 = −𝑅𝑇 ln 𝐾𝑎
The free enthalpy is composed of the enthalpic contribution H and the entropic term TS in the Gibbs- Helmholtz equation:
∆𝐺 = ∆𝐻 − 𝑇∆𝑆
The following explanations are for an exothermic binding event, i.e. the binding enthalpy H is negative.
Considering a multivalent interaction, the binding enthalpy of an n-valent ligand in an ideal case is nHmono of the corresponding monovalent ligand. However, interactions from the linker with the receptor for example may contribute to a more negative Hmulti of the multivalent ligand than it would be expected from nHmono. But the more frequent case, at least for multivalent carbohydrate ligands, is a higher (less negative) value for Hmulti because the individual carbohydrate moieties are restricted by the linker and cannot always adopt the optimal orientation in the binding pockets.[9, 79] The entropic term
S is composed of the individual contribution of translational, rotational, conformational and solvatational entropy.
∆𝑆 = ∆𝑆𝑡𝑟𝑎𝑛𝑠+ ∆𝑆𝑟𝑜𝑡+ ∆𝑆𝑐𝑜𝑛𝑓+ ∆𝑆𝑠𝑜𝑙𝑣
In the case of perfectly matched, rigid ligands (with no conformational flexibility) and neglecting the solvatational entropy the binding is maximal entropically enhanced. As soon as a single epitope of the ligand binds, all further epitopes are shifted automatically into their binding position without further entropic loss. Disregarding the influence of molecular weight on the translational and rotational entropy, the entropic cost for such a multivalent system is S. For a corresponding monovalent system consisting of n ligands and n receptors the binding entropy is nS. The entropic gain of the multivalent system compared to the monovalent is (n–1)S. However, usually the ligands do not fulfil such ideal conditions.
If the conformational loss of entropy is smaller than the gain (n–1)S from translational and rotational entropy, the multivalent binding is still favored. If the loss due to conformational entropy is bigger, the binding of more than one ligand to the same receptor becomes favorable over a chelating binding mode.[9]
These considerations are for systems that involve only intramolecular binding.[81] Crosslinking of receptors is not considered and there is no convenient model that treats aggregation effects yet. Still aggregative mechanisms often play a role in multivalent systems. Many lectins are able to agglutinate
Multivalency
crosslinking becomes likely[82] and contributes strongly to the enhanced binding affinities.[79, 81]
Entropically the formation of aggregates should be disfavored compared to intramolecular binding since more particles are bound together in the crosslinked case and more translational and rotational entropy is lost. On the other hand the ligands might retain more conformational entropy when crosslinks are formed that are more flexible than an intramolecular chelating binding.[83] Often high affinities are measured together with the observation of precipitation. Irreversible precipitates affect the equilibrium and kinetics of the binding process. This makes it difficult to understand the thermodynamics in such a case but aggregation seems to have a strong impact on affinities which are then usually reported as apparent affinities .[79]
2.3 Multivalent Lectin Ligands
To address multivalent lectins, many kinds of ligands have been developed. They differ in scaffolds, size, valency, flexibility, and lectin specificity. Usually they are created by choosing a central scaffold which has several attachment points that allow the conjugation of carbohydrate residues. This can be done by classical glycosylation reactions or by using modified carbohydrates that bear functional groups which allow convenient reactions with suitable groups on the scaffold. The different ligands can be classified into different groups, depending on the chemical nature of their scaffolds[79].
2.3.1 Polymeric Ligands
An early example for a multivalent lectin ligand was a polymerized glycoprotein binding to influenza virus hemagglutinin.[84] Later these glycoproteins were mimicked by employing polyacrylamide based polymers bearing sialic acid residues (Figure 4, 4).[85] They proved to be efficient inhibitors of hemagglutination by influenza virus.[86-87] Other reports show ligands for Concanavalin A (Con A) based on ring-opening-metathesis-polymerization (ROMP)[88] (Figure 4, 5). Varying the degree of polymerization and thus the number of carbohydrate residues, the affinity increased up to polymer chain lengths of 50 after which no more affinity increase was observed. Combinations of poly(amidoamine) dendrimers on a chitosan polymer[89-90] or mannosylated serum albumin served as ligands for macrophages[91]. More recent studies employ self-assembly[92] to create supramolecular ligands or polymers that serve as scaffold for dynamic combinatorial libraries[93].
Figure 4 Polyacrylamide based ligand 4 and ligand 5 created using ROMP.
2.3.2 Dendritic Ligands
Dendrimers are highly branched structures spreading from a central core structure to many end points which can bear functional groups suitable for further derivatization.[94-95] This makes them ideal scaffolds to create very symmetric and high valent lectin ligands when decorating them with carbohydrates. They were also used to create ligands for the inhibition of influenza virus hemagglutinin.[96] André et al. synthesized a series of dendrimers based on poly(amidoamine) with up to 128 branches and tested their affinity to various lectins.[97] The affinities were strongly dependent on
Multivalent Lectin Ligands
later modified in the carbohydrate unit leading to affinities for the dendrimers as high as for the natural ligand[26] or higher[98]. Based on the same scaffold Pera et al. developed a glycodendrimer microarray for the screening of lectins.[27] Reymond and co-workers developed dendrimers binding to LecA[18-19]
and LecB[16] from the pathogen pseudomonas aeruginosa. An example for a glycodendrimer (6) capable of binding to the cholera toxin[98] is shown in Figure 5.
Figure 5 Dendritic cholera toxin inhibitor 6 with 380 000 fold affinity enhancement compared to the monovalent ligand.[98]
2.3.3 Other Glycoclusters
Besides big dendritic structures, many small dendrimers and ligands based on other scaffolds have been reported. Ley and coworkers prepared tetravalent dendrimers based on pentaerythritol (Figure 6, 7).[99]
Also glycans themselves have been used as scaffolds for multivalent ligands. Their cyclic structure and several free hydroxyl groups that can be used to attach linkers with additional glycans make them
attractive core structures. Dubber et al. introduced carbohydrates as scaffolds terming them “octopus glycosides”.[100] Based on this work, Kitov et al. developed the so called “STARFISH” ligand that is still one of the best binders for shiga-like toxins (Figure 6, 8).[101] It is based on a glucose core to which ten copies of Gb3, the natural oligosaccharide ligand for shiga toxin, are attached via five linkers.
Galactoclusters based on a mannose center inhibit the biofilm formation by pseudomonas aeruginosa.[102] Cyclodextrins, which are glycan-derived, offer a symmetric core structure with many possible attachment points.[103] Another cyclic core structure that has emerged as a suitable scaffold to create multivalency are calixarenes[21, 23]. Ligands based on pillar[5]arenes (Figure 6, 9) are among the best ligands for LecB. The lectin LecA from the same organism could be inhibited with high affinity by a small divalent ligand having a rigid spacer between the carbohydrates (Figure 6, 10).[104]
Figure 6 Examples for multivalent ligands: ligand 7 with pentaerythritol core[99], STARFISH ligand 8 for shiga- like toxin[101], pillar[5]arene based ligand 9[24] and divalent ligand 10 with a rigid spacer[104].
2.3.4 Ligands Based on Nanomaterials
Multivalent Lectin Ligands
that facilitate detection of molecular interactions. The nature of the material can be manifold and examples reach from metals, polymers, dendrimers to carbon and silica nanostructures.[105] An early report by Penadés and coworkers introduced gold nanoparticles which are decorated with different mono- and oligosaccharides.[106] The saccharides were tethered to oligoethylene glycol spacers with a terminal thiol that dimerizes the molecules upon oxidation to the corresponding disulfides. Treatment of these with tetrachloroauric acid under reducing conditions yielded in the corresponding nanoparticles.
They were shown to have potential as antiadhesives in tumor metastasis.[107] Carbon nanoparticles are often made of graphene derivatives as fullerenes[108] (Figure 7, 11) or carbon nanotubes[109]. A ligand for WGA was based on CdSe/ZnS quantum dots which were decorated with GlcNAc residues via a linker with a terminal thiol (Figure 7, 12).[30] Quantum dots are usually made of semi-conductive materials and their electrons can only adapt discrete energy levels. The applications of such glycosylated nanomaterials are manifold, especially for biosensing of lectins in vitro and in vivo.[105]
Figure 7 A ligand based on fullerene 11[108] and carbohydrate modified quantum dots 12[30]. 2.3.5 Ligands Based on Self-Assembly or Combinatorial Chemistry
If no structural information about a target lectin is available, it can be necessary to screen many ligands in order to find hits that fit the geometry of the lectin and bind with high affinity. Combinatorial chemistry is an ideal tool to create big, structurally diverse libraries of related compounds. One approach is the use of dynamic combinatorial chemistry.[110] Here, a library is created by reacting several different compounds with each other via a reversible reaction. All products that are formed are in equilibrium.
Then an external force is applied to the system. This can be for example a physical parameter as temperature or pressure, or a binding partner for the compounds in the library. The library adapts to the new conditions and certain library members are amplified while the content of others decreases depending on the conditions. In case of lectin binding as a selection criterion, the best binders can be amplified. Requirements that have to be met are reversible reactions for the creation of the library and the possibility to detect the amplified species, for example by “freezing” of the library at a certain state, transforming the members into stable derivatives, stopping the exchange by changing the conditions[111], or deconvolution techniques[112]. Ramström and Lehn used disulfide exchange as reversible reaction to create dimeric ligands for Con A using different monosaccharides (Scheme 1).[111]
Scheme 1 Schematic representation of a dynamic combinatorial library based on disulfide exchange. Divalent Gal species 13 and divalent Man species 14 react via disulfide exchange to the mixed compound 15.[111]
The library solution was incubated with sepharose beads conjugated to Con A. The bound species from the sepharose beads could be eluted at acidic pH which also stopped the disulfide exchange and the species containing two mannose residues 14 were identified as the most dominant which is in line with the sugar specificity of Con A.
Another way of using combinatorial chemistry is the creation of “static” libraries. They can be created by various synthetic strategies. Wittmann and Seeberger used split-mix synthesis[113] for the creation of a diverse library of cyclic peptides by solid phase peptide synthesis (SPPS). The peptides served as scaffolds for the attachment of carbohydrates.[15] The idea behind the cyclic structure of the peptides was to create a conformationally restricted and preorganized ligand, leading to a small enthalpic penalty upon binding to the protein. The optimal peptide sequence and position of the carbohydrates on the peptide should be found by exploring a big number of different ligands. For the creation of the library in each coupling step a set of different amino acids was used. The resin for the SPPS was distributed on several reaction vessels according to the number of different amino acids used. After the coupling, the resin portions were combined, mixed and split again for the next coupling cycle. That way a library of about 20 000 members could be created (Figure 8).[20] In the synthesis amino acids with protected side chain amino groups were used that were conjugated to GlcNAc residues after the peptide synthesis.
Figure 8 Design of the glycopeptide library by Wittmann and Seeberger.[20]
The resin beads were then incubated with biotin labeled WGA and after washing, the beads which bound most WGA were identified by a color reaction catalyzed by an alkaline phosphatase conjugated to an anti-biotin antibody. The glycopeptides were released from the resin beads and identified. Compound
Multivalent Lectin Ligands
(depending on the assay, see Chapter 2.4.2)[114] affinity enhancement over the monovalent ligand GlcNAc.
Figure 9 One of the most potent ligands for WGA found in the screening of a 20 000-membered library.[20]
Self-assembling systems are also a valuable tool for the creation of multivalent ligands. Monomers that interact in a noncovalent, defined way can build up large supramolecular structures of high valency comparable to ligands based on polymers. Brunsveld and co-workers developed disc-shaped building blocks 17 with an aromatic core (Figure 10 A).[92] The periphery of the disc was decorated with mannose.
The discs were able to build columnar structures by stacking mediated through -interactions (Figure 10 B).
Figure 10 (A) Monomeric building block 17 for the (B) self-assembly of columnar multivalent ligands.[92]
The binding affinities were measured by an ELLA and proved to be three times higher for the polymer formed from the mono-mannose disc compared to the -methyl mannoside.
2.3.6 Multivalent Ligands for WGA
The lectin WGA possesses eight carbohydrate binding sites making it a target often used to study multivalent carbohydrate lectin interactions. Early multivalent ligands for WGA by Zanini and Roy were based on a peptidic dendrimer with a valency of up to eight (Figure 11). Compound 18 with highest valency showed a 20-fold enhancement of binding compared to the monovalent analogue as determined by an enzyme-linked lectin assay (ELLA).[115] Calixarene 19 had a 312-fold inhibitory potency over monovalent GlcNAc, derived from a hemagglutination assay. In the study, ligands of varying linker lengths between the calixarenes and the saccharides were tested. Ligands with shorter linkers showed lower affinities.[21] As described above, Wittmann and Seeberger employed combinatorial chemistry to synthesize a library of 20 000 cyclic glycopeptides[15] and screened it for affinity to WGA.[20] One of the hits (16, Figure 9) was further optimized to give 20 (Figure 11), which had an affinity 25 500-fold higher as GlcNAc.[11] Lactotriaose dendrimers 21 were also effective binders for WGA.[28] Masaka et al.
prepared tetravalent glycoclusters with 22 being the most potent one. They also performed precipitation studies showing that their ligands were able to precipitate WGA. At high concentrations of ligand, the aggregates dissolved again.[116] Beckmann et al. used click chemistry to tether N,N-diacetylchitobiose to di- and trivalent core structures with compound 23 being among the best ligands for WGA at that time.[117] Soon after, Fiore et al. presented the first example of a WGA inhibitor with nanomolar affinity in terms of IC50 and also Kd value which was based on a cyclic peptide scaffold.[12] They also observed precipitation and attributed the high affinity partly to aggregation. The same group developed ligands on the base of octasilsesquioxanes (24, Figure 11)[118] and dendrimers with a carbohydrate number of up to 48 carbohydrate residues[29]. Currently compound 24 and the 48-valent dendrimer belong together with compound 20 to the best ligands for WGA.
Schwefel et al. performed a thorough structural study of a series of divalent ligands and cyclic tetravalent glycopeptides binding to WGA.[11] They could show that divalent ligand 25 (Figure 12 A) was able to bridge two adjacent binding sites and four ligands were able to occupy all eight binding sites in the crystal structure of 25 with WGA (Figure 12 B). Ligand 25 showed a 400 times higher affinity in an ELLA assay compared to GlcNAc. Structurally related compound 26 (Figure 12 A) bound even 2350 times better than the monosaccharide. Also cyclic peptide 20 (Figure 13 A) could be crystallized together with WGA (Figure 13 B). Here the ligand also bridges two adjacent binding sites but the structure of the ligand is only partly resolved in the crystal structure (Figure 13 A, shaded gray) and it cannot be seen if the carbohydrates at D-Dab2 (D-diamino butanoic acid) and D-Dab7 are participating in the binding.
Multivalent Lectin Ligands
Figure 11 Multivalent ligands for WGA with scaffolds based on peptides (18, 20), calixarenes (19) ethylene glycol (22), ammonia (23) and silsesquioxanes (24).
Figure 12 (A) Divalent ligands 25 and 26 for WGA. (B) WGA in complex with ligand 25 (PDB ID: 2X52). The ligand is represented by a stick model (black) and the protein is shown as surface representation (gray). Secondary binding sites are located at the back of the protein and are not shown here.
A B
Figure 13 (A) Cyclic peptide 20 and (B) crystal structure of its complex with WGA (PDB ID: 2X3T). Only the gray shaded substructure of 20 is resolved in the crystal structure and shown as stick model (black). The protein is shown as surface representation (gray). D-Dab = D-diaminobutanoic acid
A B
Methods for the Investigation of Multivalent Interactions.
2.4 Methods for the Investigation of Multivalent Interactions.
For the investigation of multivalent interactions many different methods have been applied.[70] A lot of them yield in binding affinities in terms of association constants or IC50 values (defined as the ligand concentration that reduces the initially detected signal of the binding assay to 50 %). Examples are:
enzyme-linked lectin assay (ELLA)[20, 114-115, 119], fluorescence spectroscopy[30, 120], isothermal titration calorimetry (ITC)[121], microarrays[27], microscale thermophoresis[122], quartz crystal microbalance (QCM)[123], surface plasmon resonance (SPR)[124], or total internal reflection spectroscopy[125]. Information about the structure of complexes formed by multivalent interactions can be gained from analytical ultracentrifugation[83, 120], crystallography[11, 19, 82, 126-130], dynamic light scattering (DLS)[21, 30,
131-132], transmission electron microscopy[30] or electron paramagnetic resonance (EPR) spectroscopy[133]. Often combinations of the above techniques are needed to elucidate the binding mechanisms that lead to the observed multivalent effects. In the following the methods used in this work are discussed in more detail.
2.4.1 Isothermal Titration Calorimetry
Isothermal titration calorimetry is a technique mainly used for the analysis of binding events between two binding partners (that may interact also in stoichiometries other than one to one). It allows the determination of the association constant Ka, the binding enthalpy H, and the stoichiometry n of the binding event in one single experiment. Neither of the binding partners has to be labeled and the measurement takes place in solution. This make ITC an ideal method to study interactions of biomolecules.[134-135] The instrument consists of two cells: a reference cell and the sample cell which both are heated with a constant power supply to maintain a steady, constant temperature (Figure 14 A).
The reference cell is filled with the solvent that is used for the interaction and the sample cell is filled with a solution of one binding partner. The syringe is filled with the second binding partner dissolved in the same solvent and this solution is gradually titrated into the sample cell. Upon each addition, heat is released into or absorbed from the solution depending on whether the interaction is exothermic or endothermic. The sample cell warms up or cools down and the heater has to supply more or less power to maintain the temperature of the sample cell constant to the reference cell. This power provided to the sample cell is plotted as µcal s–1 against the time (Figure 14 B). The area under the resulting peaks for each injection is plotted against the ratio of the binding partners (Figure 14 C). This plot is used for the fitting of the binding curve with Ka, H and n as adjustable parameters.
Figure 14 (A) Schematic representation of isothermal titration calorimeter. (B) Raw data, power used to heat sample cell plotted against time. (C) Integrated peaks and fitting curve.
The fitting equation can be derived as follows.[135] For an interaction between ligand (L) and receptor (R) that form a complex LR
the equilibrium constant is
𝐾𝑎= [𝐿𝑅]
[𝐿][𝑅]
and the total concentrations of ligand and receptor are
[𝐿]𝑡𝑜𝑡 = [𝐿] + [𝐿𝑅] and [𝑅]𝑡𝑜𝑡= [𝑅] + [𝐿𝑅] = [𝐿𝑅] + [𝐿𝑅]
𝐾𝑎[𝐿]. After resolving for [L] and substitution, the quadratic equation
[𝐿𝑅]2+ [𝐿𝑅] (−[𝑅]𝑡𝑜𝑡− [𝐿]𝑡𝑜𝑡− 1
𝑘𝑎) + [𝑅]𝑡𝑜𝑡[𝐿]𝑡𝑜𝑡= 0 results that can be resolved to
[𝐿𝑅] =−𝑏−(𝑏2−4𝑐)
1 2
2 with 𝑏 = −[𝑅]𝑡𝑜𝑡− [𝐿]𝑡𝑜𝑡− 1
𝐾𝑎 and 𝑐 = [𝑅]𝑡𝑜𝑡[𝐿]𝑡𝑜𝑡.
Differentiation for [L]tot gives
Reference cell
adiabatic shield
sample cell syringe
T
power supply -0,5 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0
-16 -14 -12 -10 -8 -6 -4 -2 0
Molar Ratio
kcal/moleofinjectant
-1,0 -0,8 -0,6 -0,4 -0,2 0,0 0,2
0 10 20 30 40 50 60
Time (min)
µcal/sec
A B C
Methods for the Investigation of Multivalent Interactions.
The heat change that results from the titration is proportional to the change in concentration of the complex [LR]:
𝑑𝑄 = 𝑑[𝐿𝑅] ∙ Δ𝐻𝑜∙ 𝑉𝑂
Together with the expression above, the following term is obtained:
𝑑𝑄
𝑑[𝐿]𝑡𝑜𝑡 = 𝑉0∙ Δ𝐻𝑜(1
2+ 1 −1 + 𝑟 2 −[𝐿]𝑟
2
([𝐿]𝑟2− 2[𝐿]𝑟(1 − 𝑟) + (1 + 𝑟)2)12 )
The data gained from the experiment is the differential heat 𝑑[𝐿]𝑑𝑄
𝑡𝑜𝑡 which is connected to the binding enthalpy Ho and the association constant Ka as described by the equation before. All other variables are known. These parameters are determined by least-squares fitting that means the sum of squared residuals is minimized by variation of the parameters Ka and Ho. A residual is defined as “the difference between a measured data point and its calculated counterpart”.[136]
ITC has often been used to characterize lectin carbohydrate interactions[18-19, 24, 102, 104, 121, 137-153]. Bains et al. were first to investigate the binding properties of WGA to its different ligands.[64] The monosaccharide GlcNAc had a Kd value of 2.5 mM and the affinity rose up to 50 µM for the pentasaccharide. The binding enthalpy for GlcNAc was stated as 7 kcal mol–1. In general, the investigation of monosaccharides with ITC is problematic because the binding affinities are generally low. That would either call for samples with very high concentrations of protein and ligand or, because high concentrations can be difficult to achieve, the evaluation has to be performed with binding curves that lack a sigmoidal shape. This may result in inaccurate values for H and n.[154]
Brewer and coworkers investigated the binding of multivalent ligands to Con A and Dioclea grandiflora lectin (DGL) thoroughly.[121, 151-152] They reported increased affinities compared to the monosaccharide as it is usually found for multivalent ligands and the stoichiometries showed dependency on the valency.
The binding enthalpy H was proportional to the number of carbohydrate residues on the ligand while the enthalpy TS did not behave proportionally. The values were much lower than expected for a proportional behavior leading to only moderate binding affinities. This was attributed to the big distances between the binding sites on Con A and DGL that did not allow a chelating binding mode for the ligands used in the study. Because of that behavior G and thus the affinity was low for the ligands that could not bridge adjacent binding sites. The same group reported negative cooperativity for their crosslinking ligands[151] and decreasing affinity constants for individual carbohydrate residues of the ligands upon sequential binding using reverse titrations with the macromolecule being titrated to the ligand.[152] In studies by Rao et al. with systems that allow chelating binding modes also TS was proportional to the number of individual epitopes.[155]
ITC data for multivalent ligands binding to WGA is rare. Fiore et al. investigated a series of cyclic peptides using ELLA and ITC and identified neoglycopeptide 27 (Figure 15) as the best binder with a dissociation constant of 9 nM.[12] No other examples of ITC data for multivalent WGA ligands are available until now.
Figure 15 Tetravalent cyclic peptide 27 with nanomolar affinity for WGA.[12]
2.4.2 Enzyme-Linked Lectin Assay
The enzyme-linked lectin assay is a method to determine relative affinities of carbohydrate ligands binding to lectins and was introduced by Goldstein and coworkers.[119] The principle is similar to the well-known enzyme-linked immunosorbent assay (ELISA). A microtiter plate is coated with a saccharide that binds to the lectin of interest. For the coating different methodologies exist. The first examples used glycoproteins[119, 156], others used porcine stomach mucin (PSM)[20, 115], or glycopolymers[12] that bind non-covalently to the surface of the microtiter plate. Maierhofer et al.
developed an assay which uses amino functionalized microtiter plates that are coated with monosaccharides using covalent immobilization.[114] The amino groups on the microtiter plate are coupled to 1,4-phenylene diisothiocyanate 28 to form a thiourea derivative (Scheme 2). The second isothiocyanate group is then reacted with amine 29 that is connected via a linker to the reference ligand, in this case GlcNAc.
Scheme 2 Covalent functionalization of microtiter plate for ELLA.
The lectin that is to be investigated bears a reporter group which is needed for detection. This can be an enzyme which catalyzes for example a color reaction. Here, it is a horseradish peroxidase which oxidizes 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) to a green product. The lectin-reporter
Methods for the Investigation of Multivalent Interactions.
the surface and the remaining protein is washed away. The amount of surface bound lectin is then determined by the intensity of the color produced by the reporter group (Scheme 3 C). This results in inhibition curves that yield in IC50 values. The IC50 value is the concentration of ligand at which 50 % of the binding of the lectin to the microtiter plate is inhibited by the ligand. The IC50 values are relative values and strongly depend on the assay. For example, the material of the microtiter plate, the density of carbohydrates on the surface, and the method used for immobilization influences the values.
Wittmann and coworkers determined the IC50 values for tetravalent cyclic glycopeptide 16 (Figure 9) using an ELLA with either a PSM coated surface[20] or a covalently coated surface[114]. The PSM assay gave an IC50 of 380 µM and the covalent assay yielded in 16 µM. Thus, it is difficult to compare the results derived from different ELLA assays.
Scheme 3 ELLA assay: (A) Preincubation of labeled lectin with ligand; (B) incubation of lectin-ligand mixture with saccharide coated microtiter plate; (C) visualization of protein bound to surface with enzyme catalyzed color reaction.
2.4.3 Dynamic Light Scattering
Dynamic light scattering (DLS) is used to determine the hydrodynamic radii of species in solution. These can be biologic macromolecules as DNA or proteins, polymers, nanoparticles, or other supramolecular assemblies. The sample containing the particles of interest is irradiated with laser light and the scattered light is detected at a certain angle (Figure 16 A). The light is scattered by the particles in solution which are all at different positions which leads to interference. The Brownian motion of the particles changes the positions of the particles constantly which leads to fluctuations in the intensity of the scattered light.
Figure 16 (A) Basic experimental setup for a DLS experiment, (B) correlation function, (C) intensity distribution.
ABTS ABTS∙+ ligand
reporter lectin
A B C
wash
Laser
Detec-
tor -101E-7 1E-6 1E-5 1E-4 1E-3 0,01
0 10 20 30 40 50 60 70 80
Amplitude/AU
t/ s
0,01 0,1 1 10 100 1000 10000
0 20 40 60 80 100
Intensity/AU
size / nm
A B C
The signal is analyzed using an autocorrelation function (Figure 16 B). The speed of the particles is dependent on the diffusion coefficient D. This is related to the hydrodynamic radius r via the Stokes- Einstein equation
𝐷 = 𝑘𝐵𝑇 6𝜋𝜂𝑟
with Boltzmann’s constant kB and the dynamic viscosity η.[157] The analysis of the correlation function yields in an intensity distribution of the radii of the species in solution (Figure 16 C). The particles are usually treated as spheres and the obtained radii refer to spherical particles that have the same diffusion properties as the original particles. Depending on the shape of the particle, the obtained radii may deviate from the actual size of the species. The method has often been used in the context of lectins and multivalency to detect the aggregation of multivalent ligands with lectins[25, 82-83, 130, 153, 158-159] or to study the interactions of nanomaterials with lectins[160]. The advantage of the method is, that it is non-invasive, fast, and uses only a small amount of sample.
2.4.4 Electron Paramagnetic Resonance Spectroscopy
Electron paramagnetic resonance (EPR) spectroscopy is related to nuclear magnetic resonance spectroscopy but observes unpaired electron spins instead of nuclear spins. Unpaired electrons are introduced into the system of interest in the form of spin labels, in organic molecules often as stable nitroxide radicals. The double electron-electron resonance (DEER) or pulsed electron double resonance (PELDOR) technique allows the measurement of distances between electron spins in the range of 2 to 10 nm utilizing the magnetic dipolar coupling between two unpaired electron spins.[161-162] It has been especially useful in a biological context for the structural investigation of proteins[163-168]. The currently most commonly used technique is the four-pulse DEER experiment (Figure 17).
Figure 17 Four pulse sequence of DEER measurement.[161]
The DEER technique separates the magnetic dipole-dipole interaction of pairs of electron spins from other contributions to the EPR signal. An example for a resulting EPR spectrum is shown in Figure 18
Methods for the Investigation of Multivalent Interactions.
denominated spins A and B as shown in Figure 18 B. Due to their different Larmor frequencies (corresponding to the different spectral positions), spins A and B can be addressed individually by two different microwave frequencies 1 and 2 as shown in Figure 17. The first /2 pulse at the resonance frequency 1 of A turns the magnetization into the xy-plane and evolves over 1under the influence of the magnetic dipole-dipole interaction with spin B and the resonance offset of the A spins.[169] Then a
pulse creates a spin echo (dotted) at 21. A second pulse after 21+2 refocuses the A spins. At the resonance frequency 2 of spins B a pulse between the pulses at 1 is applied that inverts the B spins (Figure 18 B). This changes the local magnetic field at the A spins and leads to an oscillation of the refocused spin echo intensity at the dipolar coupling frequency.
Figure 18 (A) EPR spectrum with the spectral positions of spin A and B. (B) Inversion of spin B by pulse at
2[161]
The dipolar coupling frequency is
𝜔𝑑𝑖𝑝 =𝜇𝐵2𝑔𝐴𝑔𝐵 ℏ
1 𝑟𝐴𝐵3
with the Bohr magneton µB while gA and gB are the g-factors of the electrons and rAB the electron- electron distance that is desired.
DEER (or PELDOR) measurements can not only be used to measure distances between spins but also the number of interacting spins (spins per nanoobject) can be determined using the modulation depth as it has been described by Bode et al.[170] To do so the modulation depth of the DEER experiment of interest has to be compared with a calibration experiment that was performed with a sample containing the biradical alone using the equation
𝑛 = 𝑙𝑛𝑉𝜆
ln(1 − 𝜆𝐵)+ 1
with Vbeing the echo intensity after the modulation decay of the deer experiment, B is the modulation depth of the calibration measurement, and n is the number of spins per nanoobject.
