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Babilonia-Diaz, N. S.

Publications and source records attributed to Babilonia-Diaz, N. S..

2 recordsLinked to original sources

Single-chain nanobody inhibition of Notch and avidity enhancement utilizing the β-pore forming toxin Aerolysin

Notch plays critical roles in developmental processes and disease pathogenesis, which has led to numerous efforts to modulate its function with small molecules and antibodies. Here we present a nanobody inhibitor of Notch signaling, derived from a synthetic phage-display library targeting the notch Negative Regulatory Region (NRR). The nanobody inhibits Notch signaling in a luciferase reporter assay and in Notch-dependent hematopoietic progenitor cell differentiation assay, despite a modest 19uM affinity for Notch. We addressed the low affinity by fusion to a membrane-associating domain derived from the {beta}-Pore forming toxin Aerolysin, resulting in a significantly improved IC50 for Notch inhibition. The nanobody-aerolysin fusion inhibits proliferation of T-ALL cell lines with similar efficacy to other Notch pathway inhibitors. Overall, this study reports the development of a Notch inhibitory antibody, and demonstrates a proof-of-concept for a generalizable strategy to increase the efficacy and potency of low-affinity antibody binders.

biochemistry↗

HUHgle: An Interactive Substrate Design Tool for Covalent Protein-ssDNA Labeling Using HUH-tags

HUH-tags have emerged as versatile fusion partners that mediate sequence specific protein-ssDNA bioconjugation through a simple and efficient reaction. Here we present HUHgle, a python-based interactive tool for the visualization, design, and optimization of substrates for HUH-tag mediated covalent labeling of proteins of interest with ssDNA substrates of interest. HUHgle streamlines design processes by integrating an intuitive plotting interface with a search function capable of predicting and displaying protein-ssDNA bioconjugate formation efficiency and specificity in proposed HUH-tag/ssDNA sequence combinations. Validation demonstrates that HUHgle accurately predicts product formation of HUH-tag mediated bioconjugation for single- and orthogonal-labeling reactions. In order to maximize the accessibility and utility of HUHgle, we have implemented it as a user-friendly Google Colab notebook which facilitates broad use of this tool, regardless of coding expertise. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/585203v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1a1bbforg.highwire.dtl.DTLVardef@13d218org.highwire.dtl.DTLVardef@146478corg.highwire.dtl.DTLVardef@1034a6b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗