RESUMO
Nitrogen is the primary nutrient for plants. Low nitrogen generally affects plant growth and fruit quality. Melon, as an economic crop, is highly dependent on nitrogen. However, the response mechanism of its self-rooted and grafted seedlings to low-nitrogen stress has not been reported previously. Therefore, in this study, we analyzed the transcriptional differences between self-rooted and grafted seedlings under low-nitrogen stress using fluorescence characterization and RNA-Seq analysis. It was shown that low-nitrogen stress significantly inhibited the fluorescence characteristics of melon self-rooted seedlings. Analysis of differentially expressed genes showed that the synthesis of genes related to hormone signaling, such as auxin and brassinolide, was delayed under low-nitrogen stress. Oxidative stress response, involved in carbon and nitrogen metabolism, and secondary metabolite-related differentially expressed genes (DEGs) were significantly down-regulated. It can be seen that low-nitrogen stress causes changes in many hormonal signals in plants, and grafting can alleviate the damage caused by low-nitrogen stress on plants, ameliorate the adverse effects of nitrogen stress on plants, and help them better cope with environmental stresses.
Assuntos
Cucurbitaceae , Perfilação da Expressão Gênica , Regulação da Expressão Gênica de Plantas , Nitrogênio , Estresse Fisiológico , Transcriptoma , Nitrogênio/metabolismo , Estresse Fisiológico/genética , Cucurbitaceae/genética , Cucurbitaceae/crescimento & desenvolvimento , Cucurbitaceae/metabolismo , Perfilação da Expressão Gênica/métodos , Plântula/genética , Plântula/crescimento & desenvolvimento , Plântula/metabolismo , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Reguladores de Crescimento de Plantas/metabolismoRESUMO
Casitas B-lymphoma proto-oncogene-b (Cbl-b) is a RING finger E3 ligase that has an important role in effector T cell function, acting as a negative regulator of T cell, natural killer (NK) cell, and B cell activation. A discovery effort toward Cbl-b inhibitors was pursued in which a generative AI design engine, REINVENT, was combined with a medicinal chemistry structure-based design to discover novel inhibitors of Cbl-b. Key to the success of this effort was the evolution of the "Design" phase of the Design-Make-Test-Analyze cycle to involve iterative rounds of an in silico structure-based drug design, strongly guided by physics-based affinity prediction and machine learning DMPK predictive models, prior to selection for synthesis. This led to the accelerated discovery of a potent series of carbamate Cbl-b inhibitors.