Glycan–protein interaction

Glycan–protein interactions represent a class of biomolecular interactions that occur between free or protein-bound glycans and their cognate binding partners. Intramolecular glycan–protein (protein–glycan) interactions occur between glycans and proteins that they are covalently attached to. Together with protein–protein interactions, they form a mechanistic basis for many essential cell processes, especially for cell–cell interactions and host–cell interactions. For instance, SARS-CoV-2, the causative agent of COVID-19, employs its extensively glycosylated spike (S) protein to bind to the ACE2 receptor, allowing it to enter host cells. The spike protein is a trimeric structure, with each subunit containing 22 N-glycosylation sites, making it an attractive target for vaccine search. Glycosylation, i.e., the addition of glycans (a generic name for monosaccharides and oligosaccharides) to a protein, is one of the major post-translational modification of proteins contributing to the enormous biological complexity of life. Indeed, three different hexoses could theoretically produce from 1056 to 27,648 unique trisaccharides in contrast to only 6 peptides or oligonucleotides formed from 3 amino acids or 3 nucleotides respectively. In contrast to template-driven protein biosynthesis, the "language" of glycosylation is still unknown, making glycobiology a hot topic of current research given its prevalence in living organisms. The study of glycan–protein interactions provides insight into the mechanisms of cell-signaling and allows to create better-diagnosing tools for many diseases, including cancer. Indeed, there are no known types of cancer that do not involve erratic patterns of protein glycosylation.

Thermodynamics of binding

The binding of glycan-binding proteins (GBPs) to glycans could be modeled with simple equilibrium. Denoting glycans as G {\displaystyle G} and proteins as P {\displaystyle P} :

P r o t e i n ( P ) + G l y c a n ( G ) ⇌ P G {\displaystyle Protein(P)+Glycan(G)\rightleftharpoons PG}

With an associated equilibrium constant of

K a = [ P G ] [ P ] [ G ] {\displaystyle K_{a}={\frac {[PG]}{[P][G]}}}

Which is rearranged to give dissociation constant K d {\displaystyle K_{d}} following biochemical conventions:

K d = [ P ] [ G ] [ P G ] {\displaystyle K_{d}={\frac {[P][G]}{[PG]}}}

Given that many GBPs exhibit multivalency, this model may be expanded to account for multiple equilibria:

P + G ⇌ P G {\displaystyle P+G\rightleftharpoons PG}

P G + G ⇌ P G 2 {\displaystyle PG+G\rightleftharpoons PG_{2}}

… {\displaystyle \dots }

P G n − 1 + G ⇌ P G n {\displaystyle PG_{n-1}+G\rightleftharpoons PG_{n}}

Denoting cumulative equilibrium of binding with i {\displaystyle i} ligands as

P + i G ⇌ P G i {\displaystyle P+iG\rightleftharpoons PG_{i}}

With corresponding equilibrium constant:

β i = [ P G i ] [ P ] [ G ] i {\displaystyle \beta _{i}={\frac {[PG_{i}]}{[P][G]^{i}}}}

And writing material balance for protein ( c P {\displaystyle c_{P}} denotes the total concentration of protein):

c P = [ P ] + [ P G ] + ⋯ + [ P G n ] {\displaystyle c_{P}=[P]+[PG]+\dots +[PG_{n}]}

Expressing the terms through an equilibrium constant, a final result is found:

c P = [ P ] ( 1 + β 1 [ G ] + ⋯ + β n [ G ] n {\displaystyle c_{P}=[P](1+\beta _{1}[G]+\dots +\beta _{n}[G]^{n}}

The concentration of free protein is, thus:

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