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

Abstract Lectins are non-covalent glycan-binding proteins mediating cellular interactions but their annotation in newly sequenced organisms is lacking. The limited size of functional domains and the low level of sequence similarity challenge usual bioinformatics tools. The identification of lectin domains in proteomes requires the manual curation of sequence alignments based on structural folds. A new lectin classification is proposed. It is built on three levels: (i) 35 lectin domain folds, (ii) 109 classes of lectins sharing at least 20% sequence similarity and (iii) 350 families of lectins sharing at least 70% sequence similarity. This information is compiled in the UniLectin platform that includes the previously described UniLectin3D database of curated lectin 3D structures. Since its first release, UniLectin3D has been updated with 485 additional 3D structures. The database is now complemented by two additional modules: PropLec containing predicted β-propeller lectins and LectomeXplore including predicted lectins from sequences of the NBCI-nr and UniProt for every curated lectin class. UniLectin is accessible at https://www.unilectin.eu/

[1]  F. Lisacek,et al.  Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome , 2020, bioRxiv.

[2]  Hisashi Narimatsu,et al.  The GlyCosmos Portal: a unified and comprehensive web resource for the glycosciences , 2020, Nature Methods.

[3]  Peng-Yuan Yang,et al.  Novel methods in glycomics: a 2019 update , 2020, Expert review of proteomics.

[4]  Radka Svobodová Vareková,et al.  PDBe: improved findability of macromolecular structure data in the PDB , 2019, Nucleic Acids Res..

[5]  T. Blundell,et al.  ProCarbDB: a database of carbohydrate-binding proteins , 2019, Nucleic Acids Res..

[6]  Frédérique Lisacek,et al.  Structural Database for Lectins and the UniLectin Web Platform. , 2020, Methods in molecular biology.

[7]  Yaoqi Zhou,et al.  Recent advances in glycoinformatic platforms for glycomics and glycoproteomics. , 2019, Current opinion in structural biology.

[8]  B. Haab,et al.  Advances in Tools to Determine the Glycan-Binding Specificities of Lectins and Antibodies* , 2019, Molecular & Cellular Proteomics.

[9]  T. Kunej.  Rise of Systems Glycobiology and Personalized Glycomedicine: Why and How to Integrate Glycomics with Multiomics Science? , 2019, Omics : a journal of integrative biology.

[10]  Frederique Lisacek,et al.  The GlySpace Alliance: towards a collaborative global glycoinformatics community. , 2019, Glycobiology.

[11]  Herbert Kaltner,et al.  The sugar code: letters and vocabulary, writers, editors and readers and biosignificance of functional glycan-lectin pairing. , 2019, The Biochemical journal.

[12]  A. Ardá,et al.  Glycans in drug discovery , 2019, MedChemComm.

[13]  Frédérique Lisacek,et al.  Architecture and Evolution of Blade Assembly in β-propeller Lectins. , 2019, Structure.

[14]  J. Hirabayashi,et al.  Lectin engineering: the possible and the actual , 2019, Journal of the Royal Society Interface Focus.

[15]  Frédérique Lisacek,et al.  GlyConnect: Glycoproteomics Goes Visual, Interactive, and Analytical. , 2019, Journal of proteome research.

[16]  Jean-Philippe F Gourdine,et al.  Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery , 2019, Database J. Biol. Databases Curation.

[17]  Ian Sillitoe,et al.  CATH: expanding the horizons of structure-based functional annotations for genome sequences , 2018, Nucleic Acids Res..

[18]  The UniProt Consortium,et al.  UniProt: a worldwide hub of protein knowledge , 2018, Nucleic Acids Res..

[19]  Silvio C. E. Tosatto,et al.  The Pfam protein families database in 2019 , 2018, Nucleic Acids Res..

[20]  Michael Schroeder,et al.  UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands , 2018, Nucleic Acids Res..

[21]  M. L. Silva.  Lectin biosensors in cancer glycan biomarker detection. , 2019, Advances in clinical chemistry.

[22]  S. Goda,et al.  Identification, Characterization, and X-ray Crystallographic Analysis of a Novel Type of Lectin AJLec from the Sea Anemone Anthopleura japonica , 2018, Scientific Reports.

[23]  Robert D. Finn,et al.  HMMER web server: 2018 update , 2018, Nucleic Acids Res..

[24]  L. Amzel,et al.  F-Type Lectins: A Highly Diversified Family of Fucose-Binding Proteins with a Unique Sequence Motif and Structural Fold, Involved in Self/Non-Self-Recognition , 2017, Front. Immunol..

[25]  E. Warkentin,et al.  DM9 Domain Containing Protein Functions As a Pattern Recognition Receptor with Broad Microbial Recognition Spectrum , 2017, Front. Immunol..

[26]  Steven E Brenner,et al.  SCOPe: Manual Curation and Artifact Removal in the Structural Classification of Proteins - extended Database. , 2017, Journal of molecular biology.

[27]  Fernando Gutierrez.  Semantic Technologies and Bio-Ontologies. , 2017, Methods in molecular biology.

[28]  J. Hirabayashi,et al.  Identification, Characterization, and X-ray Crystallographic Analysis of a Novel Type of Mannose-Specific Lectin CGL1 from the Pacific Oyster Crassostrea gigas , 2016, Scientific Reports.

[29]  J. Gildersleeve,et al.  Perspectives on Anti-Glycan Antibodies Gleaned from Development of a Community Resource Database , 2016, ACS chemical biology.

[30]  Niclas G. Karlsson,et al.  SugarBindDB, a resource of glycan-mediated host–pathogen interactions , 2015, Nucleic Acids Res..

[31]  Wen J. Li,et al.  Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation , 2015, Nucleic Acids Res..

[32]  Kiyoko F. Aoki-Kinoshita,et al.  The Lectin Frontier Database (LfDB), and Data Generation Based on Frontal Affinity Chromatography , 2015, Molecules.

[33]  Pedro M. Coutinho,et al.  The carbohydrate-active enzymes database (CAZy) in 2013 , 2013, Nucleic Acids Res..

[34]  Hiroaki Tateno,et al.  Lectin structures: classification based on the 3-D structures. , 2014, Methods in molecular biology.

[35]  Sean R. Eddy,et al.  Accelerated Profile HMM Searches , 2011, PLoS Comput. Biol..

[36]  David F. Smith,et al.  Carbohydrate Recognition Properties of Human Ficolins , 2009, The Journal of Biological Chemistry.

[37]  Brandi L. Cantarel,et al.  The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics , 2008, Nucleic Acids Res..

[38]  Hafiz Ahmed,et al.  Structural and functional diversity of lectin repertoires in invertebrates, protochordates and ectothermic vertebrates. , 2004, Current opinion in structural biology.

[39]  Robert C. Edgar,et al.  MUSCLE: multiple sequence alignment with high accuracy and high throughput. , 2004, Nucleic acids research.

[40]  N. Sharon,et al.  Lectins as cell recognition molecules. , 1989, Science.