Biology subjects

Inomata, K.

Publications and source records attributed to Inomata, K..

2 recordsLinked to original sources

bioRxiv2024

Different molecular recognition by three domains of the full-length GRB2 to SOS1 proline-rich motifs and EGFR phosphorylated sites

The adaptor protein human GRB2 plays crucial roles in mediating signal transduction from cell membrane receptors to RAS and its downstream proteins by recruiting SOS1. Recent studies have revealed that GRB2 also serves as a scaffold for liquid-liquid phase separation (LLPS) with SOS1 and transmembrane receptors, which is thought to regulate the magnitude of cell signalling pathways. In this study, we employed solution NMR spectroscopy to investigate the interactions of the full-length GRB2 with proline-rich motifs (PRMs) derived from ten potential GRB2-binding sites in SOS1, as well as a peptide from a phosphorylation site of EGFR. Our findings indicate that the binding affinity of the two SH3 domains of GRB2 for PRMs differs by a factor of ten to twenty, with the N-terminal SH3 domain (NSH3) exhibiting a markedly higher affinity. The interactions of PRMs with the SH3 domains affected not only the regions surrounding the PRM binding sites on the SH3 domains but also the linker area connecting the three domains and parts of the SH2 domain. Analysis of the interaction between the phosphorylated EGFR binding site and the SH2 domain revealed chemical shift perturbations in regions distal from the known binding site of SH2. Moreover, we observed that the inter-domain interactions of the two SH3 domains with the SH2 domain of GRB2 are asymmetric. These findings suggest that the local binding of PRMs and phosphorylated EGFR to GRB2 impacts the overall structure of the GRB2 molecule, including domain orientation and dimerisation, which may contribute to LLPS formation.

biophysics↗

bioRxiv2021

Prediction of broad chemical toxicities using induced pluripotent stem cells and gene networks by transfer learning from embryonic stem cell data

The assessment of toxic chemicals using animals has limited applicability to humans. Moreover, from the perspective of animal protection, effective alternatives are also desired. Previously, we developed a method that combines developmental toxicity testing based on undifferentiated human embryonic stem (ES) cells (KhES-3) and gene networks. We showed that [≥] 95% accurate predictions could be achieved for neurotoxins, genotoxic carcinogens, and non-genotoxic carcinogens. Here, we expanded this method to predict broad toxicities and predicted the toxicity of 24 chemicals in six categories (neurotoxins, cardiotoxins, hepatotoxins, nephrotoxins [glomerular nephrotoxins/tubular nephrotoxins], and non-genotoxic carcinogens) and achieved high prediction accuracy (AUC = 0.90-1.00) in all categories. Moreover, to develop a testing system with fewer ethical issues, we screened for an induced pluripotent stem (iPS) cell line on the basis of cytotoxic sensitivity and used this line to predict toxicity in the six categories based on the gene networks of iPS cells using transfer learning from the ES cell gene networks. We successfully predicted toxicities in four toxin categories (neurotoxins, hepatotoxins, glomerular nephrotoxins, and non-genotoxic carcinogens) at high accuracy (AUC = 0.82-0.99). These results demonstrate that the prediction of chemical toxicity is possible even with iPS cells by transfer learning once a gene expression database has been developed from an ES cell line. This method holds promise for tailor-made safety evaluations using individual iPS cells.

pharmacology and toxicology↗