UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands

Abstract

Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein-Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glycoscience. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin.eu/unilectin3D.

130 years of Plant Lectin Research

“…Furthermore, a comparative analysis between lectins from the different kingdoms is challenging since the three-dimensional structure of some lectin motifs has not yet been resolved. In recent years most structural information for lectins and lectin domains from different kingdoms obtained mainly by X-ray crystallography has been collected in the UniLectin3D Curated Database (https://unilectin.eu/unilectin3D/) [36,158]. Although some lectin folds/motifs are unique, a comparison of lectin domains at the structural level reveals the presence of several common lectin folds ( Table 2).…”

Advances in Tools to Determine the Glycan-Binding Specificities of Lectins and Antibodies

“…Sood et al used molecular-dynamics simulations to quantify the contributions made by the functional groups of monosaccharides and to identify the minimum features required for lectin-glycan binding (83). A tool that could facilitate these types of analyses is a curated database called Unilectin3D, which lists the structures in the Protein Database (PDB) of lectins in complex with a glycan (84). The in-silico methods could provide valuable context to the experimental results and produce accurate predictions of binding to glycans that are not represented on the arrays.…”

Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome

“…Software and Algorithms PyMOL Schrödinger, LLC https://pymol.org LiteMol (Sehnal et al, 2017) https://www.litemol.org/ UniLectin3D (Bonnardel et al, 2019) https://unilectin.eu/unilectin3D/ CATH (Dawson et al, 2017) http://www.cathdb.info/ SCOPe (Andreeva et al, 2020) https://scop.berkeley.edu/ Muscle (Edgar, 2004) https://www.ebi.ac.uk/Tools/msa/muscle/ HMMER (Potter et al, 2018) http://hmmer.org/ UniProtKB (UniProt, 2019) https://www.uniprot.org/ BLOSUM62 (Eddy, 2004) NCBI NR/RefSeq (Kitts et al, 2016) https://www.ncbi.nlm.nih.gov/refseq/ BlastP (Sayers et al, 2019) https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAG E=Proteins dbCAN2 (Zhang et al, 2018) http://bcb.unl.edu/dbCAN2/ CAZy CBM (Lombard et al, 2014) http://www.cazy.org/Carbohydrate-Binding-Modules.html d3heatmap R package https://www.rdocumentation.org/packages/d 3heatmap/versions/0.6.1.2/topics/d3heatmap…”

“…In recent years, this has begun to be addressed through the development of databases for structural and functional glycobiology (Mariethoz et al, 2018;Mariethoz et al, 2016). Among these, UniLectin3D provides 3D structures of more than 2500 lectins and their complexes with carbohydrates (Bonnardel et al, 2019) and sites within UniLectin, a platform dedicated to the curation and collection of lectin knowledge. In this study we describe how manual selection of lectin domains in 3D structures permits the identification of lectin classes characterised by fold similarity and minimum thresholds of sequence identity.…”