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Precise regulation of Ras activity is critical for normal cell function, and mutation of Ras occurs frequently in cancers1. Ras GTPases switch between GDP-bound (inactive) and GTP-bound (active) states, which are dynamically regulated by guanine exchange factors (GEFs) and Ras GTPase-activating proteins (GAPs) that promote the active and inactive states, respectively. Ras-GTP levels change rapidly in response to growth factor activation of receptor tyrosine kinases (RTKs) to promote mitogen-activated protein kinase (MAPK) signaling. Ras is associated with multiple intracellular organelles, but its activity and function in different subcellular regions is not well defined2,3,4. Ras activation was thought to require membranes, but membrane-less granules formed by oncoprotein RTK fusions, such as EML4-Alk, can have associated Ras activity5; the mechanism of Ras activation inside EML4-Alk granules is unclear. Overall, despite decades of study, there are still many open questions about the spatiotemporal activity of Ras due to the lack of tools for detecting endogenous Ras activity. Although optogenetic and chemogenetic systems for directly activating Ras have been developed, such as Chemically Inducible Activator of Ras (CIAR)6, there are no sensors that can measure real-time, subcellular activity of endogenous levels of Ras-GTP2,4,7,8,9,10 (Fig. 1a), which are in the nanomolar range11. Most biosensors are based on native protein-binding domains12, but these are limited in number and often cannot be engineered without reducing affinity or specificity, thus limiting opportunities for tuning sensor dynamic range10 (Fig. 1a).
Fig. 1: A LOCKR-based sensor (Ras-LOCKR-S) measures endogenous Ras activity.
a, Schematic depicting the difficulty in matching sensor sensitivity to the biologically relevant concentration range. b, Ras-LOCKR-S optimization. c, Design pipeline. d, Avenues for tuning Ras-LOCKR-S switching energetics. e, Experimental tuning of Ras-LOCKR-S. Left, predicted structure of Ras-LOCKR-S with mutations highlighted. Right, heat maps of Ras-LOCKR-S with latch:cage or key:cage weakening mutations. FRET ratios (yellow/cyan) before (background) and after (maximum) 100 ng ml−1 EGF stimulation (n = 14 cells per condition) in 293T cells transiently expressing Ras-LOCKR-S. Dynamic range equals maximum FRET ratio (EGF) minus basal FRET ratio. The colored boxes in EGF-stimulated dynamic range heat map correspond to the constructs tested in f. f, Normalized to maximum FRET responses (calculated by setting the lowest and highest FRET ratios in each dataset to 0 and 1, respectively) in CIAR-PM-293 cells transiently expressing Ras-LOCKR-S mutants and treated with varying doses of A115 (n = 12–15 cells per A115 concentration). g, Normalized FRET ratio changes in 293T cells transiently expressing WT or NC Ras-LOCKR-S and stimulated with 100 ng ml−1 EGF (n = 10 cells per condition). h, Starting raw FRET ratios (left) and average normalized FRET ratio changes (right) in Ras-LOCKR-S-expressing 293T cells co-expressing WT HRas, HRas G12V, HRas S17N or no exogenous Ras (left: n = 10 cells per condition; right: n = 23 cells per condition). i, Comparison of Ras-LOCKR-S to GFP-RasBD in response to 100 ng ml−1 EGF in 293T cells (n = 19 cells). Solid lines indicate representative average timecourse, with error bars representing s.e.m. ****P = 3.5 × 10−5. Bar graphs represent mean ± s.e.m. ****P
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