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A conformational switch-controlled RNA sensor based on orthogonal dCas12a for RNA imaging in live cells.

Biosens Bioelectron

January 2025

Lab of Biosystem and Microanalysis, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, Shanghai, 200237, China; School of Chemistry and Chemical Engineering, Shihezi University, Xinjiang, 832000, China. Electronic address:

RNA imaging technology is essential for understanding the complex RNA regulatory mechanisms and serves as a powerful tool for disease diagnosis. However, conventional RNA imaging methods often require multiple fluorescent tags for the specific labeling of individual targets, complicating both the imaging process and subsequent analysis. Herein, we develop an RNA sensor that integrates a blocked CRISPR RNA (crRNA)-based conformational switch with a controllable CRISPR activation (CRISPRa) system and apply for RNA imaging.

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ConspectusA key challenge in modern chemistry research is to mimic life-like functions using simple molecular networks and the integration of such networks into the first functional artificial cell. Central to this endeavor is the development of signaling elements that can regulate the cell function in time and space by producing entities of code with specific information to induce downstream activity. Such artificial signaling motifs can emerge in nonequilibrium systems, exhibiting complex dynamic behavior like bistability, multistability, oscillations, and chaos.

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Colloidal crystals of micrometer-sized colloids create prismatic structural colors through the grating diffraction of visible light. Here, we develop design rules to engineer such structural color by specifically accounting for the effect of crystal defects. The local quality and grain size of the colloidal structure are varied by performing self-assembly in the presence of a direct current (DC) electric field.

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Designing binders to target undruggable proteins presents a formidable challenge in drug discovery. In this work, we provide an algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein. To do this, we propose a process to generate naturalistic peptide candidates through Gaussian perturbation of the peptidic latent space of the ESM-2 protein language model and subsequently screen these novel sequences for target-selective interaction activity via a contrastive language-image pretraining (CLIP)-based contrastive learning architecture.

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Controlling the reactivity of bonds along polymer chains enables both functionalization and deconstruction with relevance to chemical recycling and circularity. Because the substrate is a macromolecule, however, understanding the effects of chain conformation on the reactivity of polymer bonds emerges as important yet underexplored. Here, we show how oxy-functionalization of chemically recyclable condensation polymers affects acidolysis to monomers through control over distortion and interaction energies in the rate-limiting transition states.

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