Abstract
Lectin-glycan interactions facilitate inter- and intracellular communication in many processes including protein trafficking, host-pathogen recognition, and tumorigenesis promotion. Specific recognition of glycans by lectins is also the basis for a wide range of applications in areas including glycobiology research, cancer screening, and antiviral therapeutics. To provide a better understanding of the determinants of lectin-glycan interaction specificity and support such applications, this study comprehensively investigates specificity-conferring features of all available lectin-glycan complex structures. Systematic characterization, comparison, and predictive modeling of a set of 221 complementary physicochemical and geometric features representing these interactions highlighted specificity-conferring features with potential mechanistic insight. Univariable comparative analyses with weighted Wilcoxon-Mann-Whitney tests revealed strong statistical associations between binding site features and specificity that are conserved across unrelated lectin binding sites. Multivariable modeling with random forests demonstrated the utility of these features for predicting the identity of bound glycans based on generalized patterns learned from non-homologous lectins. These analyses revealed global determinants of lectin specificity, such as sialic acid glycan recognition in deep, concave binding sites enriched for positively charged residues, in contrast to high mannose glycan recognition in fairly shallow but well-defined pockets enriched for non-polar residues. Focused fine specificity analysis of hemagglutinin interactions with human-like and avian-like glycans uncovered features representing both known and novel mutations related to shifts in influenza tropism from avian to human tissues. As the approach presented here relies on co-crystallized lectin-glycan pairs for studying specificity, it is limited in its inferences by the quantity, quality, and diversity of the structural data available. Regardless, the systematic characterization of lectin binding sites presented here provides a novel approach to studying lectin specificity and is a step towards confidently predicting new lectin-glycan interactions.
Highlights
Lectins, non-enzymatic, non-immunoglobulin, sugar-binding proteins, selectively interact with small subsets of the vast set of possible glycoforms and thereby facilitate diverse biological processes
Multivariable modeling with random forests demonstrated the utility of these features for predicting the identity of bound glycans based on generalized patterns learned from non-homologous lectins. These analyses revealed global determinants of lectin specificity, such as sialic acid glycan recognition in deep, concave binding sites enriched for positively charged residues, in contrast to high mannose glycan recognition in fairly shallow but well-defined pockets enriched for non-polar residues
Understanding what makes a particular lectin recognize a particular glycan over the vast set of other glycans can help us better understand these processes and how to monitor and control them
Summary
Non-enzymatic, non-immunoglobulin, sugar-binding proteins, selectively interact with small subsets of the vast set of possible glycoforms and thereby facilitate diverse biological processes. Specific interactions between lectins and their cognate glycans play critical roles in many other host-pathogen interactions [3] as well as an increasing number of known intracellular and extracellular biological processes with altered glycosylation in cancer cells contributing toward tumor cell growth, proliferation, migration, and invasion [4, 5]. Specific lectin-glycan interactions enable fundamental glycobiology research by tracking and investigating glycans on cells or viruses, in tissues, or in biological samples ranging from blood to human milk, through the use of lectins in mass spectrometry capture strategies, lectin arrays to assess whole cell glycosylation patterns, and labelled lectin probes [13,14,15,16,17]
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