LectomeXplore, an update of UniLectin for the discovery of carbohydrate-binding proteins based on a new lectin classification

In silico discovery and anti-tumor bioactivities validation of an algal lectin from Kappaphycus alvarezii genome

Lectins are proteins that bind specifically and reversibly to carbohydrates, and some of them have significant anti-tumor activities. Compared to those of lectins from land plants, there are far fewer studies on algal lectins, despite of the high biodiversity of algae. However, canonical strategies based on chromatographic feature-oriented screening cannot satisfy the requirement for algal lectin discovery. In this study, prospecting for novel OAAH family lectins throughout 358 genomes of red algae and cyanobacteria was conducted. Then 35 candidate lectins and 1843 of their simulated mutated forms were virtually screened based on predicted binding specificities to characteristic carbohydrates on cancer cells inferred by a deep learning model. A new lectin, named Siye, was discovered in Kappaphycus alvarezii genome and further verified on different cancer cells. Without causing agglutination of erythrocytes, Siye showed significant cytotoxicity to four human cancer cell lines (IC50 values ranging from 0.11 to 3.95 μg/mL), including breast adenocarcinoma HCC1937, lung carcinoma A549, liver cancer HepG2 and romyelocytic leukemia HL60. And the cytotoxicity was induced through promoting apoptosis by regulating the caspase and the p53 pathway within 24 h. This study testifies the feasibility and efficiency of the genome mining guided by evolutionary theory and artificial intelligence in the discovery of algal lectins.

Boltzmann Model Predicts Glycan Structures from Lectin Binding

Glycans are complex oligosaccharides that are involved in many diseases and biological processes. Unfortunately, current methods for determining glycan composition and structure (glycan sequencing) are laborious and require a high level of expertise. Here, we assess the feasibility of sequencing glycans based on their lectin binding fingerprints. By training a Boltzmann model on lectin binding data, we predict the approximate structures of 88 ± 7% of N-glycans and 87 ± 13% of O-glycans in our test set. We show that our model generalizes well to the pharmaceutically relevant case of Chinese hamster ovary (CHO) cell glycans. We also analyze the motif specificity of a wide array of lectins and identify the most and least predictive lectins and glycan features. These results could help streamline glycoprotein research and be of use to anyone using lectins for glycobiology.

Tandem-repeat lectins: structural and functional insights

Multivalency in lectins plays a pivotal role in influencing glycan cross-linking, thereby affecting lectin functionality. This multivalency can be achieved through oligomerization, the presence of tandemly repeated carbohydrate recognition domains, or a combination of both. Unlike lectins that rely on multiple factors for the oligomerization of identical monomers, tandem-repeat lectins inherently possess multivalency, independent of this complex process. The repeat domains, although not identical, display slightly distinct specificities within a predetermined geometry, enhancing specificity, affinity, avidity and even oligomerization. Despite the recognition of this structural characteristic in recently discovered lectins by numerous studies, a unified criterion to define tandem-repeat lectins is still necessary. We suggest defining them multivalent lectins with intrachain tandem repeats corresponding to carbohydrate recognition domains, independent of oligomerization. This systematic review examines the folding and phyletic diversity of tandem-repeat lectins and refers to relevant literature. Our study categorizes all lectins with tandemly repeated carbohydrate recognition domains into nine distinct folding classes associated with specific biological functions. Our findings provide a comprehensive description and analysis of tandem-repeat lectins in terms of their functions and structural features. Our exploration of phyletic and functional diversity has revealed previously undocumented tandem-repeat lectins. We propose research directions aimed at enhancing our understanding of the origins of tandem-repeat lectin and fostering the development of medical and biotechnological applications, notably in the design of artificial sugars and neolectins.

Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries

Most membrane proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, shielding potentially large fractions of protein surface. High glycan conformational freedom hinders complete structural elucidation of glycoproteins. Computer simulations may be used to model glycosylated proteins but require hundreds of thousands of computing hours on supercomputers, thus limiting routine use. Here, we describe GlycoSHIELD, a reductionist method that can be implemented on personal computers to graft realistic ensembles of glycan conformers onto static protein structures in minutes. Using molecular dynamics simulation, small-angle X-ray scattering, cryoelectron microscopy, and mass spectrometry, we show that this open-access toolkit provides enhanced models of glycoprotein structures. Focusing on N-cadherin, human coronavirus spike proteins, and gamma-aminobutyric acid receptors, we show that GlycoSHIELD can shed light on the impact of glycans on the conformation and activity of complex glycoproteins.

Elucidating the glycan-binding specificity and structure of Cucumis melo agglutinin, a new R-type lectin

Plant lectins have garnered attention for their roles as laboratory probes and potential therapeutics. Here, we report the discovery and characterization of Cucumis melo agglutinin (CMA1), a new R-type lectin from melon. Our findings reveal CMA1's unique glycan-binding profile, mechanistically explained by its 3D structure, augmenting our understanding of R-type lectins. We expressed CMA1 recombinantly and assessed its binding specificity using multiple glycan arrays, covering 1,046 unique sequences. This resulted in a complex binding profile, strongly preferring C2-substituted, beta-linked galactose (both GalNAc and Fuca1-2Gal), which we contrasted with the established R-type lectin Ricinus communis agglutinin 1 (RCA1). We also report binding of specific glycosaminoglycan subtypes and a general enhancement of binding by sulfation. Further validation using agglutination, thermal shift assays, and surface plasmon resonance confirmed and quantified this binding specificity in solution. Finally, we solved the high-resolution structure of the CMA1 N-terminal domain using X-ray crystallography, supporting our functional findings at the molecular level. Our study provides a comprehensive understanding of CMA1, laying the groundwork for further exploration of its biological and therapeutic potential.

het-B allorecognition in Podospora anserina is determined by pseudo-allelic interaction of genes encoding a HET and lectin fold domain protein and a PII-like protein

Filamentous fungi display allorecognition genes that trigger regulated cell death (RCD) when strains of unlike genotype fuse. Podospora anserina is one of several model species for the study of this allorecognition process termed heterokaryon or vegetative incompatibility. Incompatibility restricts transmission of mycoviruses between isolates. In P. anserina, genetic analyses have identified nine incompatibility loci, termed het loci. Here we set out to clone the genes controlling het-B incompatibility. het-B displays two incompatible alleles, het-B1 and het-B2. We find that the het-B locus encompasses two adjacent genes, Bh and Bp that exist as highly divergent allelic variants (Bh1/Bh2 and Bp1/Bp2) in the incompatible haplotypes. Bh encodes a protein with an N-terminal HET domain, a cell death inducing domain bearing homology to Toll/interleukin-1 receptor (TIR) domains and a C-terminal domain with a predicted lectin fold. The Bp product is homologous to PII-like proteins, a family of small trimeric proteins acting as sensors of adenine nucleotides in bacteria. We show that although the het-B system appears genetically allelic, incompatibility is in fact determined by the non-allelic Bh1/Bp2 interaction while the reciprocal Bh2/Bp1 interaction plays no role in incompatibility. The highly divergent C-terminal lectin fold domain of BH determines recognition specificity. Population studies and genome analyses indicate that het-B is under balancing selection with trans-species polymorphism, highlighting the evolutionary significance of the two incompatible haplotypes. In addition to emphasizing anew the central role of TIR-like HET domains in fungal RCD, this study identifies novel players in fungal allorecognition and completes the characterization of the entire het gene set in that species.

Bacterial surface display of human lectins in Escherichia coli

Lectin-glycan interactions sustain fundamental biological processes involved in development and disease. Owing to their unique sugar-binding properties, lectins have great potential in glycobiology and biomedicine. However, their relatively low affinities and broad specificities pose a significant challenge when used as analytical reagents. New approaches for expression and engineering of lectins are in demand to overcome current limitations. Herein, we report the application of bacterial display for the expression of human galectin-3 and mannose-binding lectin in Escherichia coli. The analysis of the cell surface expression and binding activity of the surface-displayed lectins, including point and deletion mutants, in combination with molecular dynamics simulation, demonstrate the robustness and suitability of this approach. Furthermore, the display of functional mannose-binding lectin in the bacterial surface proved the feasibility of this method for disulfide bond-containing lectins. This work establishes for the first time bacterial display as an efficient means for the expression and engineering of human lectins, thereby increasing the available toolbox for glycobiology research.

HumanLectome, an update of UniLectin for the annotation and prediction of human lectins

The UniLectin portal (https://unilectin.unige.ch/) was designed in 2019 with the goal of centralising curated and predicted data on carbohydrate-binding proteins known as lectins. UniLectin is also intended as a support for the study of lectomes (full lectin set) of organisms or tissues. The present update describes the inclusion of several new modules and details the latest (https://unilectin.unige.ch/humanLectome/), covering our knowledge of the human lectome and comprising 215 unevenly characterised lectins, particularly in terms of structural information. Each HumanLectome entry is protein-centric and compiles evidence of carbohydrate recognition domain(s), specificity, 3D-structure, tissue-based expression and related genomic data. Other recent improvements regarding interoperability and accessibility are outlined.

Genome-wide analysis of lectins in cyanobacteria: from evolutionary mode to motif patterns

Lectins are glycoproteins that can bind to specific carbohydrates, and different lectin families exhibit different biological activities. They are also present in the cyanobacteria and many of them have shown excellent therapeutic effect, which deserve for bioprospecting. However, in comparison to those from terrestrial plants, the current knowledge on cyanobacterial lectins is very limited. To this end, genome-wide analyses were performed to find out their evolutionary mode and motif patterns in 316 genomes of representative taxa. In results, 196 putative cyanobacterial lectins were dig out and 105 of them were classified into known families. Seven lectins were found to be belonged to distinct two lectin families, and they may have the potential activities of both lectin families. Whereas no MFP-2, Chitin, and Nictaba family lectins were found. What's more, the Legume lectin-like lectin family was found to be the richest and most complex in cyanobacteria, which could be a main research direction for future cyanobacterial lectin bioprospecting and development. Our classification and prediction of cyanobacteria lectins is expected to provide assistance in the development of lectin-based medicine and provide solutions to the current thorny viral and tumor diseases in humans.

Computational modeling of protein-carbohydrate interactions: Current trends and future challenges

The article leads the reader through an up-to-date presentation of the concepts, developments, and main applications of computational modeling to study protein-carbohydrate interactions. It follows with the presentation of some current issues and perspectives arising from the expected evolution of generic methodological developments in deep learning, immersive analytics, and virtual reality for molecular visualization and data management. Such methodological developments for macromolecular interactions would greatly benefit a wide range of scientific endeavors in the field of carbohydrate chemistry and biochemistry, including the following interrelated efforts dealing with highly crowded media, with examples concerning glycoside transferases, the extracellular matrix, and the exploration of interactions between complex carbohydrates and intrinsically disordered proteins.

BiotechLec: an interactive guide of commercial lectins for glycobiology and biomedical research applications

For decades, lectins have been used as probes in glycobiology and this usage has gradually spread to other domains of Life Science. Nowadays, researchers investigate glycan recognition with lectins in diverse biotechnology and clinical applications, addressing key questions regarding binding specificity. The latter is documented in scattered and heterogeneous sources, and this situation calls for a centralized and easy-access reference. To address this need, an on-line solution called BiotechLec (https://www.unilectin.eu/biotechlec) is proposed in a new section of UniLectin, a platform dedicated to lectin molecular knowledge.

A Genomic and Transcriptomic Analysis of the C-Type Lectin Gene Family Reveals Highly Expanded and Diversified Repertoires in Bivalves

C-type lectins belong to a widely conserved family of lectins characterized in Metazoa. They show important functional diversity and immune implications, mainly as pathogen recognition receptors. In this work, C-type lectin-like proteins (CTLs) of a set of metazoan species were analyzed, revealing an important expansion in bivalve mollusks, which contrasted with the reduced repertoires of other mollusks, such as cephalopods. Orthology relationships demonstrated that these expanded repertoires consisted of CTL subfamilies conserved within Mollusca or Bivalvia and of lineage-specific subfamilies with orthology only between closely related species. Transcriptomic analyses revealed the importance of the bivalve subfamilies in mucosal immunity, as they were mainly expressed in the digestive gland and gills and modulated with specific stimuli. CTL domain-containing proteins that had additional domains (CTLDcps) were also studied, revealing interesting gene families with different conservation degrees of the CTL domain across orthologs from different taxa. Unique bivalve CTLDcps with specific domain architectures were revealed, corresponding to uncharacterized bivalve proteins with putative immune function according to their transcriptomic modulation, which could constitute interesting targets for functional characterization.

Crystal structure of an L-type lectin domain from archaea

The crystal structures of an L-type lectin domain from Methanocaldococcus jannaschii in apo and mannose-bound forms have been determined. A thorough investigation of L-type lectin domains from several organisms provides insight into the differences in these domains from different kingdoms of life. While the overall fold of the L-type lectin domain is conserved, differences in the lengths of the carbohydrate-binding loops and significant variations in the Mn²⁺ -binding site compared to the Ca²⁺ -binding site are observed. Furthermore, the sequence and phylogenetic analyses suggest that the archaeal L-type lectin domain is evolutionarily closer to the plant legume lectins than to its bacterial or animal counterparts. This is the first report of the biochemical, structural, sequence, and phylogenetic analyses of an L-type lectin domain from archaea and serves to enhance our understanding of the species-specific differences and evolution of L-type lectin domains.

Structure and interactions of the phloem lectin (phloem protein 2) Cus17 from Cucumis sativus

Phloem protein 2 (PP2) contributes crucially to phloem-based defense in plants by binding to carbohydrates displayed by pathogens. However, its three-dimensional structure and the sugar binding site remained unexplored. Here, we report the crystal structure of the dimeric PP2 Cus17 from Cucumis sativus in its apo form and complexed with nitrobenzene, N-acetyllactosamine, and chitotriose. Each protomer of Cus17 consists of two antiparallel four-stranded twisted β sheets, a β hairpin, and three short helices forming a β sandwich architectural fold. This structural fold has not been previously observed in other plant lectin families. Structure analysis of the lectin-carbohydrate complexes reveals an extended carbohydrate binding site in Cus17, composed mostly of aromatic amino acids. Our studies suggest a highly conserved tertiary structure and a versatile binding site capable of recognizing motifs common to diverse glycans on plant pathogens/pests, which makes the PP2 family suited for phloem-based plant defense.

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Glycans are critical to every facet of biology and medicine, from viral infections to embryogenesis. Tools to study glycans are rapidly evolving; however, the majority of our knowledge is deeply dependent on binding by glycan binding proteins (e.g., lectins). The specificities of lectins, which are often naturally isolated proteins, have not been well-defined, making it difficult to leverage their full potential for glycan analysis. Herein, we use a combination of machine learning algorithms and expert annotation to define lectin specificity for this important probe set. Our analysis uses comprehensive glycan microarray analysis of commercially available lectins we obtained using version 5.0 of the Consortium for Functional Glycomics glycan microarray (CFGv5). This data set was made public in 2011. We report the creation of this data set and its use in large-scale evaluation of lectin-glycan binding behaviors. Our motif analysis was performed by integrating 68 manually defined glycan features with systematic probing of computational rules for significant binding motifs using mono- and disaccharides and linkages. Combining machine learning with manual annotation, we create a detailed interpretation of glycan-binding specificity for 57 unique lectins, categorized by their major binding motifs: mannose, complex-type N-glycan, O-glycan, fucose, sialic acid and sulfate, GlcNAc and chitin, Gal and LacNAc, and GalNAc. Our work provides fresh insights into the complex binding features of commercially available lectins in current use, providing a critical guide to these important reagents.

N-glycosylation of cervicovaginal fluid reflects microbial community, immune activity, and pregnancy status

Human cervicovaginal fluid (CVF) is a complex, functionally important and glycan rich biological fluid, fundamental in mediating physiological events associated with reproductive health. Using a comprehensive glycomic strategy we reveal an extremely rich and complex N-glycome in CVF of pregnant and non-pregnant women, abundant in paucimannose and high mannose glycans, complex glycans with 2-4 N-Acetyllactosamine (LacNAc) antennae, and Poly-LacNAc glycans decorated with fucosylation and sialylation. N-glycosylation profiles were observed to differ in relation to pregnancy status, microbial composition, immune activation, and pregnancy outcome. Compared to CVF from women experiencing term birth, CVF from women who subsequently experienced preterm birth showed lower sialylation, which correlated to the presence of a diverse microbiome, and higher fucosylation, which correlated positively to pro-inflammatory cytokine concentration. This study is the first step towards better understanding the role of cervicovaginal glycans in reproductive health, their contribution to the mechanism of microbial driven preterm birth, and their potential for preventative therapy.

Hybrid emulsifier systems: Alkyl imidazolium lactoside surfactants derived from natural resources

A new series of hybrid surfactants comprising an imidazolium as a cation and a disaccharide as a non-ion were synthesized, and their aggregation behavior was also investigated. The synthetic approach used alkylation as an easily accessible route on an imidazole to attempt an economic production followed by coupling with bromoethyl lactoside to form lacto-imidazolium salts surfactants. The coupled surfactants were obtained in almost quantitative yield over several steps. The surfactant surface properties in aqueous media were investigated, including critical micelle concentration (CMC), Krafft temperature, and emulsion stability were studied. The CMC measurements of the alkyl imidazolium lactoside surfactants are significantly lower than normal imidazolium surfactants, while the emulsion investigations encourage the use of alkyl imidazolium lactoside surfactants owing to stabilized assemble behavior as good as APGs.

Structural insights into host-microbe glycointeractions

Despite their ubiquitous presence in biological systems, glycans have historically received less attention than they deserved. Investigations in recent years have featured important findings about the role of glycans in regulating the human gut microbiota. Here, we present a brief overview of current trends that shape future directions of computational and experimental research approaches and add to our understanding of host-microbe glycointeractions.

LectinOracle: A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction

Ranging from bacterial cell adhesion over viral cell entry to human innate immunity, glycan-binding proteins or lectins are abound in nature. Widely used as staining and characterization reagents in cell biology and crucial for understanding the interactions in biological systems, lectins are a focal point of study in glycobiology. Yet the sheer breadth and depth of specificity for diverse oligosaccharide motifs has made studying lectins a largely piecemeal approach, with few options to generalize. Here, LectinOracle, a model combining transformer-based representations for proteins and graph convolutional neural networks for glycans to predict their interaction, is presented. Using a curated data set of 564,647 unique protein-glycan interactions, it is shown that LectinOracle predictions agree with literature-annotated specificities for a wide range of lectins. Using a range of specialized glycan arrays, it is shown that LectinOracle predictions generalize to new glycans and lectins, with qualitative and quantitative agreement with experimental data. It is further demonstrated that LectinOracle can be used to improve lectin classification, accelerate lectin directed evolution, predict epidemiological outcomes in the context of influenza virus, and analyze whole lectomes in host-microbe interactions. It is envisioned that the herein presented platform will advance both the study of lectins and their role in (glyco)biology.

UniLectin, A One-Stop-Shop to Explore and Study Carbohydrate-Binding Proteins

All eukaryotic cells are covered with a dense layer of glycoconjugates, and the cell walls of bacteria are made of various polysaccharides, putting glycans in key locations for mediating protein-protein interactions at cell interfaces. Glycan function is therefore mainly defined as binding to other molecules, and lectins are proteins that specifically recognize and interact non-covalently with glycans. UniLectin was designed based on insight into the knowledge of lectins, their classification, and their biological role. This modular platform provides a curated and periodically updated classification of lectins along with a set of comparative and visualization tools, as well as structured results of screening comprehensive sequence datasets. UniLectin can be used to explore lectins, find precise information on glycan-protein interactions, and mine the results of predictive tools based on HMM profiles. This usage is illustrated here with two protocols. The first one highlights the fine-tuned role of the O blood group antigen in distinctive pathogen recognition, while the second compares the various bacterial lectin arsenals that clearly depend on living conditions of species even in the same genus. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Searching for the structural details of lectins binding the O blood group antigen Basic Protocol 2: Comparing the lectomes of related organisms in different environments.

Comprehensive analysis of lectin-glycan interactions reveals determinants of lectin specificity

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.

Diverse Localization Patterns of an R-Type Lectin in Marine Annelids

Lectins facilitate cell–cell contact and are critical in many cellular processes. Studying lectins may help us understand the mechanisms underlying tissue regeneration. We investigated the localization of an R-type lectin in a marine annelid (Perinereis sp.) with remarkable tissue regeneration abilities. Perinereis nuntia lectin (PnL), a galactose-binding lectin with repeating Gln-X-Trp motifs, is derived from the ricin B-chain. An antiserum was raised against PnL to specifically detect a 32-kDa lectin in the crude extracts from homogenized lugworms. The antiserum detected PnL in the epidermis, setae, oblique muscle, acicula, nerve cord, and nephridium of the annelid. Some of these tissues and organs also produced Galactose (Gal) or N-acetylgalactosamine (GalNAc), which was detected by fluorescent-labeled plant lectin. These results indicated that the PnL was produced in the tissues originating from the endoderm, mesoderm, and ectoderm. Besides, the localizing pattern of PnL partially merged with the binding pattern of a fluorescent-labeled mushroom lectin that binds to Gal and GalNAc. It suggested that PnL co-localized with galactose-containing glycans in Annelid tissue; this might be the reason PnL needed to be extracted with haptenic sugar, such as d-galactose, in the buffer. Furthermore, we found that a fluorescein isothiocyanate-labeled Gal/GalNAc-binding mushroom lectin binding pattern in the annelid tissue overlapped with the localizing pattern of PnL. These findings suggest that lectin functions by interacting with Gal-containing glycoconjugates in the tissues.

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

Bacteria use carbohydrate-binding proteins (CBPs), such as lectins and carbohydrate-binding modules (CBMs), to anchor to specific sugars on host surfaces. CBPs in the gut microbiome are well studied, but their roles in the vagina microbiome and involvement in sexually transmitted infections, cervical cancer and preterm birth are largely unknown. We established a classification system for lectins and designed Hidden Markov Model (HMM) profiles for data mining of bacterial genomes, resulting in identification of >100,000 predicted bacterial lectins available at unilectin.eu/bacteria. Genome screening of 90 isolates from 21 vaginal bacterial species shows that those associated with infection and inflammation produce a larger CBPs repertoire, thus enabling them to potentially bind a wider array of glycans in the vagina. Both the number of predicted bacterial CBPs and their specificities correlated with pathogenicity. This study provides new insights into potential mechanisms of colonisation by commensals and potential pathogens of the reproductive tract that underpin health and disease states.

A Comprehensive Phylogenetic and Bioinformatics Survey of Lectins in the Fungal Kingdom

Fungal lectins are a large family of carbohydrate-binding proteins with no enzymatic activity. They play fundamental biological roles in the interactions of fungi with their environment and are found in many different species across the fungal kingdom. In particular, their contribution to defense against feeders has been emphasized, and when secreted, lectins may be involved in the recognition of bacteria, fungal competitors and specific host plants. Carbohydrate specificities and quaternary structures vary widely, but evidence for an evolutionary relationship within the different classes of fungal lectins is supported by a high degree of amino acid sequence identity. The UniLectin3D database contains 194 fungal lectin 3D structures, of which 129 are characterized with a carbohydrate ligand. Using the UniLectin3D lectin classification system, 109 lectin sequence motifs were defined to screen 1223 species deposited in the genomic portal MycoCosm of the Joint Genome Institute. The resulting 33,485 putative lectin sequences are organized in MycoLec, a publicly available and searchable database. These results shed light on the evolution of the lectin gene families in fungi.