François Bonnardel

Mr. François Bonnardel

Cermac, cnrs, univ Grenoble, UNIGE, pig, sib
orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 September 2018 in Nucleic Acids Research
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Journal Article
Open access
PDF file
François BonnardelFrançois Bonnardel
François Bonnardel
JMJulien Mariethoz
Julien Mariethoz
SSSebastian Salentin
Sebastian Salentin
XRXavier Robin
Xavier Robin
MSMichael Schroeder
Michael Schroeder
AIAnne Imberty
Anne Imberty
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.

11 November 2020 in Nucleic Acids Research
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Journal Article
Open access
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François BonnardelFrançois Bonnardel
François Bonnardel
JMJulien Mariethoz
Julien Mariethoz
SPSerge Pérez
Serge Pérez
AIAnne Imberty
Anne Imberty
FLFrederique Lisacek
Frederique Lisacek
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 June 2020 in Current Opinion in Structural Biology
Verified
Journal Article
Closed access
SNSimona Notova
Simona Notova
François BonnardelFrançois Bonnardel
François Bonnardel
FLFrederique Lisacek
Frederique Lisacek
AVAnnabelle Varrot
Annabelle Varrot
AIAnne Imberty
Anne Imberty

1 May 2019 in Structure
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Journal Article
Closed access
François BonnardelFrançois Bonnardel
François Bonnardel
AKAtul Kumar
Atul Kumar
MWMichaela Wimmerova
Michaela Wimmerova
MLMartina Lahmann
Martina Lahmann
SPSerge Perez
Serge Perez
AIAnne Imberty
Anne Imberty

7 June 2021 in Journal of Fungi
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Journal Article
Open access
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ALAnnie Lebreton
Annie Lebreton
François BonnardelFrançois Bonnardel
François Bonnardel
Yucheng DaiYucheng Dai
Yucheng Dai
AIAnne Imberty
Anne Imberty
FMFrancis Martin
Francis Martin
FLFrederique Lisacek
Frederique Lisacek
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.

11 December 2020 in Biomolecules
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Journal Article
Open access
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Serge PerezSerge Perez
Serge Perez
François BonnardelFrançois Bonnardel
François Bonnardel
FLFrederique Lisacek
Frederique Lisacek
AIAnne Imberty
Anne Imberty
SBSylvie Ricard Blum
Sylvie Ricard Blum
OMOlga Nikolaevna Makshakova
Olga Nikolaevna Makshakova
Glycosaminoglycans (GAGs) are complex linear polysaccharides. GAG-DB is a curated database that classifies the three-dimensional features of the six mammalian GAGs (chondroitin sulfate, dermatan sulfate, heparin, heparan sulfate, hyaluronan, and keratan sulfate) and their oligosaccharides complexed with proteins. The entries are structures of GAG and GAG-protein complexes determined by X-ray single-crystal diffraction methods, X-ray fiber diffractometry, solution NMR spectroscopy, and scattering data often associated with molecular modeling. We designed the database architecture and the navigation tools to query the database with the Protein Data Bank (PDB), UniProtKB, and GlyTouCan (universal glycan repository) identifiers. Special attention was devoted to the description of the bound glycan ligands using simple graphical representation and numerical format for cross-referencing to other databases in glycoscience and functional data. GAG-DB provides detailed information on GAGs, their bound protein ligands, and features their interactions using several open access applications. Binding covers interactions between monosaccharides and protein monosaccharide units and the evaluation of quaternary structure. GAG-DB is freely available.