@article{biomedinformatics3020021,

title = {Evaluation of Transmembrane Protein Structural Models Using HPMScore},

author = {Stéphane Téletchéa and Jérémy Esque and Aurélie Urbain and Catherine Etchebest and Alexandre G. de Brevern},

url = {https://www.mdpi.com/2673-7426/3/2/21

https://hal.science/hal-03251546v1, HAL},

doi = {10.3390/biomedinformatics3020021},

issn = {2673-7426},

year  = {2023},

date = {2023-05-02},

urldate = {2023-05-02},

journal = {BioMedInformatics},

volume = {3},

number = {2},

pages = {306--326},

abstract = {Transmembrane proteins (TMPs) are a class of essential proteins for biological and therapeutic purposes. Despite an increasing number of structures, the gap with the number of available sequences remains impressive. The choice of a dedicated function to select the most probable/relevant model among hundreds is a specific problem of TMPs. Indeed, the majority of approaches are mostly focused on globular proteins. We developed an alternative methodology to evaluate the quality of TMP structural models. HPMScore took into account sequence and local structural information using the unsupervised learning approach called hybrid protein model. The methodology was extensively evaluated on very different TMP all-α proteins. Structural models with different qualities were generated, from good to bad quality. HPMScore performed better than DOPE in recognizing good comparative models over more degenerated models, with a Top 1 of 46.9% against DOPE 40.1%, both giving the same result in 13.0%. When the alignments used are higher than 35%, HPM is the best for 52%, against 36% for DOPE (12% for both). These encouraging results need further improvement particularly when the sequence identity falls below 35%. An area of enhancement would be to train on a larger training set. A dedicated web server has been implemented and provided to the scientific community. It can be used with structural models generated from comparative modeling to deep learning approaches.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Téletchéa2023,

title = {Evaluation of Transmembrane Protein Structural Models Using HPMScore },

author = {Stéphane Téletchéa and Jérémy Esque and Aurélie Urbain and Catherine Etchebest and Alexandre de Brevern},

editor = {Pentti Nieminen},

url = {https://www.mdpi.com/2673-7426/3/2/21},

doi = {10.3390/biomedinformatics3020021},

issn = {2673-7426},

year  = {2023},

date = {2023-04-06},

urldate = {2023-04-06},

journal = {BioMedInformatics},

volume = {3},

issue = {2},

pages = {306-326},

abstract = {Transmembrane proteins (TMPs) are a class of essential proteins for biological and therapeutic purposes. Despite an increasing number of structures, the gap with the number of available sequences remains impressive. The choice of a dedicated function to select the most probable/relevant model among hundreds is a specific problem of TMPs. Indeed, the majority of approaches are mostly focused on globular proteins. We developed an alternative methodology to evaluate the quality of TMP structural models. HPMScore took into account sequence and local structural information using the unsupervised learning approach called hybrid protein model. The methodology was extensively evaluated on very different TMP all-α proteins. Structural models with different qualities were generated, from good to bad quality. HPMScore performed better than DOPE in recognizing good comparative models over more degenerated models, with a Top 1 of 46.9% against DOPE 40.1%, both giving the same result in 13.0%. When the alignments used are higher than 35%, HPM is the best for 52%, against 36% for DOPE (12% for both). These encouraging results need further improvement particularly when the sequence identity falls below 35%. An area of enhancement would be to train on a larger training set. A dedicated web server has been implemented and provided to the scientific community. It can be used with structural models generated from comparative modeling to deep learning approaches.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ijms24021051,

title = {The Histone Chaperone Network Is Highly Conserved in Physarum polycephalum},

author = {Axel Poulet and Ellyn Rousselot and Stéphane Téletchéa and Céline Noirot and Yannick Jacob and Josien Wolfswinkel and Christophe Thiriet and Céline Duc},

url = {https://www.mdpi.com/1422-0067/24/2/1051},

doi = {10.3390/ijms24021051},

issn = {1422-0067},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {International Journal of Molecular Sciences},

volume = {24},

number = {2},

abstract = {The nucleosome is composed of histones and DNA. Prior to their deposition on chromatin, histones are shielded by specialized and diverse proteins known as histone chaperones. They escort histones during their entire cellular life and ensure their proper incorporation in chromatin. Physarum polycephalum is a Mycetozoan, a clade located at the crown of the eukaryotic tree. We previously found that histones, which are highly conserved between plants and animals, are also highly conserved in Physarum. However, histone chaperones differ significantly between animal and plant kingdoms, and this thus probed us to further study the conservation of histone chaperones in Physarum and their evolution relative to animal and plants. Most of the known histone chaperones and their functional domains are conserved as well as key residues required for histone and chaperone interactions. Physarum is divergent from yeast, plants and animals, but PpHIRA, PpCABIN1 and PpSPT6 are similar in structure to plant orthologues. PpFACT is closely related to the yeast complex, and the Physarum genome encodes the animal-specific APFL chaperone. Furthermore, we performed RNA sequencing to monitor chaperone expression during the cell cycle and uncovered two distinct patterns during S-phase. In summary, our study demonstrates the conserved role of histone chaperones in handling histones in an early-branching eukaryote.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FLOCH2021,

title = {A Review of the Literature Organized Into a New Database: RHeference},

author = {Aline Floch and Stéphane Téletchéa and Christophe Tournamille and Alexandre G de Brevern and France Pirenne},

url = {https://www.sciencedirect.com/science/article/pii/S0887796321000109},

doi = {https://doi.org/10.1016/j.tmrv.2021.04.002},

issn = {0887-7963},

year  = {2021},

date = {2021-01-01},

journal = {Transfusion Medicine Reviews},

abstract = {Hundreds of articles containing heterogeneous data describe D variants or add to the knowledge of known alleles. Data can be difficult to find despite existing online blood group resources and genetic and literature databases. We have developed a modern, elaborate database for D variants, thanks to an extensive literature search with meticulous curation of 387 peer-reviewed articles and 80 abstracts from major conferences and other sources. RHeference contains entries for 710 RHD alleles, 11 RHCE alleles, 30 phenotype descriptions (preventing data loss from historical sources), 35 partly characterized alleles, 3 haplotypes, and 16 miscellaneous entries. The entries include molecular, phenotypic, serological, alloimmunization, haplotype, geographical, and other data, detailed for each source. The main characteristics are summarized for each entry. The sources for all information are included and easily accessible through doi and PMID links. Overall, the database contains more than 10,000 individual pieces of data. We have set up the database architecture based on our previous expertise on database setup and biocuration for other topics, using modern technologies such as the Django framework, BioPython, Bootstrap, and Jquery. This architecture allows an easy access to data and enables simple and complex queries: combining multiple mutations, keywords, or any of the characteristics included in the database. RHeference provides a complement to existing resources and will continue to grow as our knowledge expands and new articles are published. The database url is http://www.rheference.org/.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gheyouche_structural_2021,

title = {Structural Design and Analysis of the RHOA-ARHGEF1 Binding Mode: Challenges and Applications for Protein-Protein Interface Prediction},

author = {Ennys Gheyouche and Matthias Bagueneau and Gervaise Loirand and Bernard Offmann and Stéphane Téletchéa},

doi = {10.3389/fmolb.2021.643728},

issn = {2296-889X},

year  = {2021},

date = {2021-01-01},

journal = {Frontiers in Molecular Biosciences},

volume = {8},

pages = {643728},

abstract = {The interaction between two proteins may involve local movements, such as small side-chains re-positioning or more global allosteric movements, such as domain rearrangement. We studied how one can build a precise and detailed protein-protein interface using existing protein-protein docking methods, and how it can be possible to enhance the initial structures using molecular dynamics simulations and data-driven human inspection. We present how this strategy was applied to the modeling of RHOA-ARHGEF1 interaction using similar complexes of RHOA bound to other members of the Rho guanine nucleotide exchange factor family for comparative assessment. In parallel, a more crude approach based on structural superimposition and molecular replacement was also assessed. Both models were then successfully refined using molecular dynamics simulations leading to protein structures where the major data from scientific literature could be recovered. We expect that the detailed strategy used in this work will prove useful for other protein-protein interface design. The RHOA-ARHGEF1 interface modeled here will be extremely useful for the design of inhibitors targeting this protein-protein interaction (PPI).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1093/nargab/lqab107,

title = {Identification and characterization of histones in Physarum polycephalum evidence a phylogenetic vicinity of Mycetozoans to the animal kingdom},

author = {Axel Poulet and Laxmi Narayan Mishra and Stéphane Téletchéa and Jeffrey J Hayes and Yannick Jacob and Christophe Thiriet and Céline Duc},

url = {https://doi.org/10.1093/nargab/lqab107},

doi = {10.1093/nargab/lqab107},

issn = {2631-9268},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {NAR Genomics and Bioinformatics},

volume = {3},

number = {4},

abstract = {Physarum polycephalum belongs to Mycetozoans, a phylogenetic clade apart from the animal, plant and fungus kingdoms. Histones are nuclear proteins involved in genome organization and regulation and are among the most evolutionary conserved proteins within eukaryotes. Therefore, this raises the question of their conservation in Physarum and the position of this organism within the eukaryotic phylogenic tree based on histone sequences. We carried out a comprehensive study of histones in Physarum polycephalum using genomic, transcriptomic and molecular data. Our results allowed to identify the different isoforms of the core histones H2A, H2B, H3 and H4 which exhibit strong conservation of amino acid residues previously identified as subject to post-translational modifications. Furthermore, we also identified the linker histone H1, the most divergent histone, and characterized a large number of its PTMs by mass spectrometry. We also performed an in-depth investigation of histone genes and transcript structures. Histone proteins are highly conserved in Physarum and their characterization will contribute to a better understanding of the polyphyletic Mycetozoan group. Our data reinforce that P. polycephalum is evolutionary closer to animals than plants and located at the crown of the eukaryotic tree. Our study provides new insights in the evolutionary history of Physarum and eukaryote lineages.},

note = {lqab107},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33408768,

title = {The twin cytokines interleukin-34 and CSF-1: masterful conductors of macrophage homeostasis},

author = {Javier Muñoz-Garcia and Denis Cochonneau and Stéphane Télétchéa and Emilie Moranton and Didier Lanoe and Régis Brion and Frédéric Lézot and Marie-Françoise Heymann and Dominique Heymann},

doi = {10.7150/thno.50683},

issn = {1838-7640},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Theranostics},

volume = {11},

number = {4},

pages = {1568--1593},

abstract = {Macrophages are specialized cells that control tissue homeostasis. They include non-resident and tissue-resident macrophage populations which are characterized by the expression of particular cell surface markers and the secretion of molecules with a wide range of biological functions. The differentiation and polarization of macrophages relies on specific growth factors and their receptors. Macrophage-colony stimulating factor (CSF-1) and interleukine-34 (IL-34), also known as "twin" cytokines, are part of this regluatory landscape. CSF-1 and IL-34 share a common receptor, the macrophage-colony stimulating factor receptor (CSF-1R), which is activated in a similar way by both factors and turns on identical signaling pathways. However, there is some discrete differential activation leading to specific activities. In this review, we disscuss recent progress in understanding of the role of the twin cytokines in macrophage differentiation, from their interaction with CSF-1R and the activation of signaling pathways, to their implication in macrophage polarization of non-resident and tissue-resident macrophages. A special focus on IL-34, its involvement in pathophsyiological contexts, and its potential as a theranostic target for macrophage therapy will be proposed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1093/database/baaa095,

title = {STOREFISH 2.0: a database on the reproductive strategies of teleost fishes},

author = {Stéphane Téletchéa and Fabrice Téletchéa},

url = {https://doi.org/10.1093/database/baaa095},

doi = {10.1093/database/baaa095},

issn = {1758-0463},

year  = {2020},

date = {2020-01-01},

journal = {Database},

volume = {2020},

abstract = {Teleost fishes show the most outstanding reproductive diversity of all vertebrates. Yet to date, no one has been able to decisively explain this striking variability nor to perform large-scale phylogenetic analyses of reproductive modes. Here, we describe STrategies Of REproduction in FISH (STOREFISH) 2.0, an online database easing the sharing of an original data set on reproduction published in 2007, enriched with automated data extraction and presentation to display the knowledge acquired on temperate freshwater fish species. STOREFISH 2.0 contains the information for 80 freshwater fish species and 50 traits from the analysis of 1219 references. It is anticipated that this new database could be useful for freshwater biodiversity research, conservation, assessment and management.Database URL: www.storefish.org},

note = {baaa095},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1021/acs.joc.0c01927b,

title = {Access to Galectin-3 Inhibitors from Chemoenzymatic Synthons},

author = {Christophe Dussouy and Stéphane Téletchéa and Annie Lambert and Cathy Charlier and Iuliana Botez and Frédéric De Ceuninck and Cyrille Grandjean},

url = {https://doi.org/10.1021/acs.joc.0c01927},

doi = {10.1021/acs.joc.0c01927},

year  = {2020},

date = {2020-01-01},

journal = {The Journal of Organic Chemistry},

volume = {85},

number = {24},

pages = {16099-16114},

abstract = {Chemoenzymatic strategies are useful for providing both regio- and stereoselective access to bioactive oligosaccharides. We show herein that a glycosynthase mutant of a Thermus thermophilus α-glycosidase can react with unnatural glycosides such as 6-azido-6-deoxy-d-glucose/glucosamine to lead to β-d-galactopyranosyl-(1→3)-d-glucopyranoside or β-d-galactopyranosyl-(1→3)-2-acetamido-2-deoxy-d-glucopyranoside derivatives bearing a unique azide function. Taking advantage of the orthogonality between the azide and the hydroxyl functional groups, the former was next selectively reacted to give rise to a library of galectin-3 inhibitors. Combining enzyme substrate promiscuity and bioorthogonality thus appears as a powerful strategy to rapidly access to sugar-based ligands},

note = {PMID: 33200927},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gheyouche2019,

title = {Docknmine, a web portal to assemble and analyse virtual and experimental interaction data},

author = {Ennys Gheyouche and Romain Launay and Jean Lethiec and Antoine Labeeuw and Caroline Roze and Alan Amossé and Stéphane Téletchéa},

doi = {10.3390/ijms20205062},

issn = {14220067},

year  = {2019},

date = {2019-10-01},

journal = {International Journal of Molecular Sciences},

volume = {20},

number = {20},

publisher = {MDPI AG},

abstract = {Scientists have to perform multiple experiments producing qualitative and quantitative data to determine if a compound is able to bind to a given target. Due to the large diversity of the potential ligand chemical space, the possibility of experimentally exploring a lot of compounds on a target rapidly becomes out of reach. Scientists therefore need to use virtual screening methods to determine the putative binding mode of ligands on a protein and then post-process the raw docking experiments with a dedicated scoring function in relation with experimental data. Two of the major difficulties for comparing docking predictions with experiments mostly come from the lack of transferability of experimental data and the lack of standardisation in molecule names. Although large portals like PubChem or ChEMBL are available for general purpose, there is no service allowing a formal expert annotation of both experimental data and docking studies. To address these issues, researchers build their own collection of data in flat files, often in spreadsheets, with limited possibilities of extensive annotations or standardisation of ligand descriptions allowing cross-database retrieval. We have conceived the dockNmine platform to provide a service allowing an expert and authenticated annotation of ligands and targets. First, this portal allows a scientist to incorporate controlled information in the database using reference identifiers for the protein (Uniprot ID) and the ligand (SMILES description), the data and the publication associated to it. Second, it allows the incorporation of docking experiments using forms that automatically parse useful parameters and results. Last, the web interface provides a lot of pre-computed outputs to assess the degree of correlations between docking experiments and experimental data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tripathi2019,

title = {Investigation of phospholipase Cγ1 interaction with SLP76 using molecular modeling methods for identifying novel inhibitors},

author = {Neha Tripathi and Iyanar Vetrivel and Stéphane Téletchéa and Mickaël Jean and Patrick Legembre and Adèle D Laurent},

doi = {10.3390/ijms20194721},

issn = {14220067},

year  = {2019},

date = {2019-10-01},

journal = {International Journal of Molecular Sciences},

volume = {20},

number = {19},

publisher = {MDPI AG},

abstract = {The enzyme phospholipase C gamma 1 (PLCγ1) has been identified as a potential drug target of interest for various pathological conditions such as immune disorders, systemic lupus erythematosus, and cancers. Targeting its SH3 domain has been recognized as an efficient pharmacological approach for drug discovery against PLCγ1. Therefore, for the first time, a combination of various biophysical methods has been employed to shed light on the atomistic interactions between PLCγ1 and its known binding partners. Indeed, molecular modeling of PLCγ1 with SLP76 peptide and with previously reported inhibitors (ritonavir, anethole, daunorubicin, diflunisal, and rosiglitazone) facilitated the identification of the common critical residues (Gln805, Arg806, Asp808, Glu809, Asp825, Gly827, and Trp828) as well as the quantification of their interaction through binding energies calculations. These features are in agreement with previous experimental data. Such an in depth biophysical analysis of each complex provides an opportunity to identify new inhibitors through pharmacophore mapping, molecular docking and MD simulations. From such a systematic procedure, a total of seven compounds emerged as promising inhibitors, all characterized by a strong binding with PLCγ1 and a comparable or higher binding affinity to ritonavir (ΔGbind < -25 kcal/mol), one of the most potent inhibitor reported till now.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Teletchea2019,

title = {Repository of enriched structures of proteins involved in the red blood cell environment (RESPIRE)},

author = {Stéphane Téletchéa and H Santuz and S Léonard and Catherine Etchebest},

doi = {10.1371/journal.pone.0211043},

issn = {19326203},

year  = {2019},

date = {2019-02-01},

journal = {PLoS ONE},

volume = {14},

number = {2},

publisher = {Public Library of Science},

abstract = {The Red Blood Cell (RBC) is a metabolically-driven cell vital for processes such a gas transport and homeostasis. RBC possesses at its surface exposing antigens proteins that are critical in blood transfusion. Due to their importance, numerous studies address the cell function as a whole but more and more details of RBC structure and protein content are now studied using massive state-of-the art characterisation techniques. Yet, the resulting information is frequently scattered in many scientific articles, in many databases and specialized web servers. To provide a more compendious view of erythrocytes and of their protein content, we developed a dedicated database called RESPIRE that aims at gathering a comprehensive and coherent ensemble of information and data about proteins in RBC. This cell-driven database lists proteins found in erythrocytes. For a given protein entry, initial data are processed from external portals and enriched by using state-of-the-art bioinformatics methods. As structural information is extremely useful to understand protein function and predict the impact of mutations, a strong effort has been put on the prediction of protein structures with a special treatment for membrane proteins. Browsing the database is available through text search for reference gene names or protein identifiers, through pre-defined queries or via hyperlinks. The RESPIRE database provides valuable information and unique annotations that should be useful to a wide audience of biologists, clinicians and structural biologists.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LeCaignec2019,

title = {RPL13 Variants Cause Spondyloepimetaphyseal Dysplasia with Severe Short Stature},

author = {Cédric Le Caignec and Benjamin Ory and François Lamoureux and Marie Francoise O'Donohue and Emilien Orgebin and Pierre Lindenbaum and Stéphane Téletchéa and Manon Saby and Anna Hurst and Katherine Nelson and Shawn R Gilbert and Yael Wilnai and Leonid Zeitlin and Eitan Segev and Robel Tesfaye and Mathilde Nizon and Benjamin Cogne and Stéphane Bezieau and Loic Geoffroy and Antoine Hamel and Emmanuelle Mayrargue and Beno{î}t de Courtivron and Aliette Decock-Giraudaud and Céline Charrier and Olivier Pichon and Christelle Retière and Richard Redon and Alexander Pepler and Kirsty McWalter and Lydie Da Costa and Annick Toutain and Pierre Emmanuel Gleizes and Marc Baud'huin and Bertrand Isidor},

doi = {10.1016/j.ajhg.2019.09.024},

issn = {15376605},

year  = {2019},

date = {2019-01-01},

journal = {American Journal of Human Genetics},

volume = {105},

number = {5},

pages = {1040--1047},

abstract = {Variants in genes encoding ribosomal proteins have thus far been associated with Diamond-Blackfan anemia, a rare inherited bone marrow failure, and isolated congenital asplenia. Here, we report one de novo missense variant and three de novo splice variants in RPL13, which encodes ribosomal protein RPL13 (also called eL13), in four unrelated individuals with a rare bone dysplasia causing severe short stature. The three splice variants (c.477+1GtextgreaterT, c.477+1GtextgreaterA, and c.477+2 TtextgreaterC) result in partial intron retention, which leads to an 18-amino acid insertion. In contrast to observations from Diamond-Blackfan anemia, we detected no evidence of significant pre-rRNA processing disturbance in cells derived from two affected individuals. Consistently, we showed that the insertion-containing protein is stably expressed and incorporated into 60S subunits similar to the wild-type protein. Erythroid proliferation in culture and ribosome profile on sucrose gradient are modified, suggesting a change in translation dynamics. We also provide evidence that RPL13 is present at high levels in chondrocytes and osteoblasts in mouse growth plates. Taken together, we show that the identified RPL13 variants cause a human ribosomopathy defined by a rare skeletal dysplasia, and we highlight the role of this ribosomal protein in bone development.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Richoux2019,

title = {Comparing two deep learning sequence-based models for protein-protein interaction prediction},

author = {Florian Richoux and Charlène Servantie and Cynthia Borès and Stéphane Téletchéa},

url = {http://arxiv.org/abs/1901.06268},

year  = {2019},

date = {2019-01-01},

journal = {arXiv},

volume = {1901.06268},

abstract = {Biological data are extremely diverse, complex but also quite sparse. The recent developments in deep learning methods are offering new possibilities for the analysis of complex data. However, it is easy to be get a deep learning model that seems to have good results but is in fact either overfitting the training data or the validation data. In particular, the fact to overfit the validation data, called "information leak", is almost never treated in papers proposing deep learning models to predict protein-protein interactions (PPI). In this work, we compare two carefully designed deep learning models and show pitfalls to avoid while predicting PPIs through machine learning methods. Our best model predicts accurately more than 78% of human PPI, in very strict conditions both for training and testing. The methodology we propose here allow us to have strong confidences about the ability of a model to scale up on larger datasets. This would allow sharper models when larger datasets would be available, rather than current models prone to information leaks. Our solid methodological foundations shall be applicable to more organisms and whole proteome networks predictions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Atmanene2017,

title = {Biophysical and structural characterization of mono/di-arylated lactosamine derivatives interaction with human galectin-3},

author = {Cédric Atmanene and Céline Ronin and Stéphane Téletchéa and François Moana Gautier and Florence Djedaïni-Pilard and Fabrice Ciesielski and Valérie Vivat and Cyrille Grandjean},

doi = {10.1016/j.bbrc.2017.05.150},

issn = {10902104},

year  = {2017},

date = {2017-01-01},

journal = {Biochemical and Biophysical Research Communications},

volume = {489},

number = {3},

pages = {281--286},

abstract = {Combination of biophysical and structural techniques allowed characterizing and uncovering the mechanisms underlying increased binding affinity of lactosamine derivatives for galectin 3. In particular, complementing information gathered from X-ray crystallography, native mass spectrometry and isothermal microcalorimetry showed favorable enthalpic contribution of cation-π interaction between lactosamine aryl substitutions and arginine residues from the carbohydrate recognition domain, which resulted in two log increase in compound binding affinity. This incrementing strategy allowed individual contribution of galectin inhibitor moieties to be dissected. Altogether, our results suggest that core and substituents of these saccharide-based inhibitors can be optimized separately, providing valuable tools to study the role of galectins in diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Dion2017a,

title = {Development of a Sensitive Microarray Platform for the Ranking of Galectin Inhibitors: Identification of a Selective Galectin-3 Inhibitor},

author = {Johann Dion and Tamara Advedissian and Nataliya Storozhylova and Samir Dahbi and Annie Lambert and Frédérique Deshayes and Mireille Viguier and Charles Tellier and Françoise Poirier and Stéphane Téletchéa and Christophe Dussouy and Hiroaki Tateno and Jun Hirabayashi and Cyrille Grandjean},

doi = {10.1002/cbic.201700544},

issn = {14397633},

year  = {2017},

date = {2017-01-01},

journal = {ChemBioChem},

volume = {18},

number = {24},

pages = {2428--2440},

abstract = {Glycan microarrays are useful tools for lectin glycan profiling. The use of a glycan microarray based on evanescent-field fluorescence detection was herein further extended to the screening of lectin inhibitors in competitive experiments. The efficacy of this approach was tested with 2/3′-mono- and 2,3′-diaromatic type II lactosamine derivatives and galectins as targets and was validated by comparison with fluorescence anisotropy proposed as an orthogonal protein interaction measurement technique. We showed that subtle differences in the architecture of the inhibitor could be sensed that pointed out the preference of galectin-3 for 2′-arylamido derivatives over ureas, thioureas, and amines and that of galectin-7 for derivatives bearing an α substituent at the anomeric position of glucosamine. We eventually identified a diaromatic oxazoline as a highly specific inhibitor of galectin-3 versus galectin-1 and galectin-7.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Segaliny2015,

title = {IL-34 and M-CSF form a novel heteromeric cytokine and regulate the M-CSF receptor activation and localization},

author = {Aude I Ségaliny and Régis Brion and Bénédicte Brulin and Mike Maillasson and Céline Charrier and Stéphane Téletchéa and Dominique Heymann},

doi = {10.1016/j.cyto.2015.05.029},

issn = {10960023},

year  = {2015},

date = {2015-01-01},

journal = {Cytokine},

volume = {76},

number = {2},

pages = {170--181},

abstract = {Interleukin-34 (IL-34) is a newly-discovered homodimeric cytokine that regulates, like Macrophage Colony-Stimulating Factor (M-CSF), the differentiation of the myeloid lineage through M-CSF receptor (M-CSFR) signaling pathways. To date, both cytokines have been considered as competitive cytokines with regard to the M-CSFR. The aim of the present work was to study the functional relationships of these cytokines on cells expressing the M-CSFR. We demonstrate that simultaneous addition of M-CSF and IL-34 led to a specific activation pattern on the M-CSFR, with higher phosphorylation of the tyrosine residues at low concentrations. Similarly, both cytokines showed an additive effect on cellular proliferation or viability. In addition, BIAcore experiments demonstrated that M-CSF binds to IL-34, and molecular docking studies predicted the formation of a heteromeric M-CSF/IL-34 cytokine. A proximity ligation assay confirmed this interaction between the cytokines. Finally, co-expression of the M-CSFR and its ligands differentially regulated M-CSFR trafficking into the cell. This study establishes a new foundation for the understanding of the functional relationship between IL-34 and M-CSF, and gives a new vision for the development of therapeutic approaches targeting the IL-34/M-CSF/M-CSFR axis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Craveur2015,

title = {Protein flexibility in the light of structural alphabets},

author = {Pierrick Craveur and Agnel P Joseph and Jeremy Esque and Tarun J Narwani and Floriane Noël and Nicolas Shinada and Matthieu Goguet and Sylvain Leonard and Pierre Poulain and Olivier Bertrand and Guilhem Faure and Joseph Rebehmed and Amine Ghozlane and Lakshmipuram S Swapna and Ramachandra M Bhaskara and Jonathan Barnoud and Stéphane Téletchéa and Vincent Jallu and Jiri Cerny and Bohdan Schneider and Catherine Etchebest and Narayanaswamy Srinivasan and Jean Christophe Gelly and Alexandre G de Brevern},

doi = {10.3389/fmolb.2015.00020},

issn = {2296889X},

year  = {2015},

date = {2015-01-01},

journal = {Frontiers in Molecular Biosciences},

volume = {2},

number = {MAY},

pages = {1--20},

abstract = {Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}