Search Results
Experimental validation of computerised models of clustering of platelet glycoprotein receptors that signal via tandem SH2 domain proteins
2022, Maqsood, Zahra, Clark, Joanne C., Martin, Eleyna M., Cheung, Yam Fung Hilaire, Morán, Luis A., Watson, Sean E. T., Pike, Jeremy A., Di, Ying, Poulter, Natalie S., Slater, Alexandre, Lange, Bodo M. H., Nieswandt, Bernhard, Eble, Johannes A., Tomlinson, Mike G., Owen, Dylan M., Stegner, David, Bridge, Lloyd J., Wierling, Christoph, Watson, Steve P.
The clustering of platelet glycoprotein receptors with cytosolic YxxL and YxxM motifs, including GPVI, CLEC-2 and PEAR1, triggers activation via phosphorylation of the conserved tyrosine residues and recruitment of the tandem SH2 (Src homology 2) domain effector proteins, Syk and PI 3-kinase. We have modelled the clustering of these receptors with monovalent, divalent and tetravalent soluble ligands and with transmembrane ligands based on the law of mass action using ordinary differential equations and agent-based modelling. The models were experimentally evaluated in platelets and transfected cell lines using monovalent and multivalent ligands, including novel nanobody-based divalent and tetravalent ligands, by fluorescence correlation spectroscopy. Ligand valency, receptor number, receptor dimerisation, receptor phosphorylation and a cytosolic tandem SH2 domain protein act in synergy to drive receptor clustering. Threshold concentrations of a CLEC-2-blocking antibody and Syk inhibitor act in synergy to block platelet aggregation. This offers a strategy for countering the effect of avidity of multivalent ligands and in limiting off-target effects.
BLOOM: BLoom filter based oblivious outsourced matchings
2017, Ziegeldorf, Jan Henrik, Pennekamp, Jan, Hellmanns, David, Schwinger, Felix, Kunze, Ike, Henze, Martin, Hiller, Jens, Matzutt, Roman, Wehrle, Klaus
Whole genome sequencing has become fast, accurate, and cheap, paving the way towards the large-scale collection and processing of human genome data. Unfortunately, this dawning genome era does not only promise tremendous advances in biomedical research but also causes unprecedented privacy risks for the many. Handling storage and processing of large genome datasets through cloud services greatly aggravates these concerns. Current research efforts thus investigate the use of strong cryptographic methods and protocols to implement privacy-preserving genomic computations.
Compomics-utilities: An open-source Java library for computational proteomics
2011, Barsnes, Harald, Vaudel, Marc, Helsens, Kenny, Sickmann, Albert, Walther, Dirk, Berven, Frode S.
The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool.