Translation Kinetics and their Effects on Protein Structure and Function, mRNA half-lives, and Cellular Phenotype

项目摘要 翻译动力学严重影响蛋白质的结构和功能，mRNA降解的速率， 细胞表型当同义密码子突变被整合到mRNA分子中时（其 改变核糖体翻译密码子位置的速率，但不改变它们编码的氨基酸的速率） 酶的比活性在很长一段时间内变化，当这些酶被激活时， 突变导致核糖体交通堵塞，细胞迁移和维持昼夜节律的能力， 受到影响。这些影响发生在不同物种之间，从细菌到果蝇，从真菌到人类。是什么 在这一领域缺少的是一个全面的，分子的理解如何翻译动力学影响这些 流程.利用计算（理论、模拟和大数据）和实验（质谱、低温）， EM和NMR）方法，这项建议侧重于四个基本问题：（一）是否可以存在一个新的 蛋白质错误折叠的形式，这被认为是联系同义突变和改变蛋白质功能， 实验证明？(ii)当这种蛋白质错误折叠发生时， 转录因子？(iii)是否有可能理解和预测伸长动力学如何引起不同的 核糖体运输的模式，以及这些模式如何影响抑制依赖的mRNA降解？（四） 什么样的分子机制将人类的同义突变与生长表型的变化联系起来？ 初步数据表明，这些问题的明确假设。对于问题（一）和（二），同义词 假设突变改变了新生蛋白质分子到细胞亚群的动力学分配， 错误折叠的，可溶的，自纠缠的状态，具有减少的功能，这可能会影响催化的情况下， 在转录因子的情况下，酶或DNA启动子结合。关于问题（三）， 可解释的机器学习提出了可以改变核糖体运输和mRNA的分子因素 降解-这将构成后续计算机模拟和体内测试的基础。对于问题（四）， PI使用的严格的统计方法已经确定了同义的癌症驱动因素， 有机会了解和连接同义突变的细胞表型。这些假设将是 使用计算工具进行测试，包括多尺度模拟技术，生物信息学和机器 学习并使用质谱、冷冻EM、NMR和酶趋化性进行实验测试。 这项研究将建立一个统一的机制，通过同义突变可以改变可溶性 蛋白质的结构和功能。它将提供一种新的分子基础， 同义突变可以在转录水平上影响基因表达。这将导致预测性的 模型连接翻译动力学，核糖体运输和依赖于翻译的非线性效应 mRNA降解。最后，它将建立影响人类健康的同义癌症驱动因素的存在。 细胞生长表型及其发生的分子机制。

Project Summary Translation kinetics critically influences protein structure and function, the rate of mRNA degradation, and cellular phenotype. When synonymous codon mutations are incorporated into an mRNA molecule (which changes the rate at which codon positions are translated by the ribosome but not the amino acids they encode) the specific activity of enzymes changes for long time periods, mRNA degradation rates are altered when these mutations lead to ribosome traffic jams, and the ability of cells to migrate and maintain a circadian rhythm can be affected. These effects occur across species, from bacteria to fruit flies, from fungi to humans. What is missing in this field is a comprehensive, molecular understanding of how translation kinetics influences these processes. Utilizing both computational (theory, simulation, and big data) and experimental (Mass Spec, Cryo- EM, and NMR) methods, this proposal focuses on four fundamental questions: (i) Can the existence of a novel form of protein misfolding, which is suggested to link synonymous mutations and altered protein function, be experimentally demonstrated? (ii) Can gene expression be altered when such protein misfolding occurs in transcription factors? (iii) Is it possible to understand and predict how elongation kinetics give rise to different patterns of ribosome traffic, and how these patterns influence translation-dependent mRNA degradation? (iv) What molecular mechanisms connect synonymous mutations in humans to changes in growth phenotype? Preliminary data suggest clear hypotheses to these questions. For questions (i) and (ii), synonymous mutations are hypothesized to alter the kinetic partitioning of nascent protein molecules into subpopulations of misfolded, soluble, self-entangled states that have reduced functionality, which can affect catalysis in the case of enzymes or DNA promotor binding in the case of transcription factors. For question (iii), application of interpretable machine learning has suggested molecular factors that can alter both ribosome traffic and mRNA degradation – which will form the basis for follow up in silico and in vivo testing. And for question (iv), rigorous statistical methods the PI has used have identified synonymous cancer drivers which provide a unique opportunity to understand and connect synonymous mutations to cellular phenotype. These hypotheses will be tested using computational tools including multi-scale simulation techniques, bioinformatics, and machine learning. And experimentally tested using mass spectrometry, Cryo-EM, NMR, and enzymatic chemotaxis. This research will establish a unifying mechanism by which synonymous mutations can alter soluble protein structure and function over long time periods. It will provide a novel molecular basis by which synonymous mutations can affect gene expression at the transcriptional level. It will result in a predictive model connecting non-linear effects between translation kinetics, ribosome traffic, and translation-dependent mRNA degradation. And finally, it will establish the existence of synonymous cancer drivers affecting human cell growth phenotype and the molecular mechanisms by which this occurs.