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Precision medicine review: rare driver mutations and their biophysical classification

机译:精准医学评论:罕见的驾驶员突变及其生物物理分类

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摘要

How can biophysical principles help precision medicine identify rare driver mutations? A major tenet of pragmatic approaches to precision oncology and pharmacology is that driver mutations are very frequent. However, frequency is a statistical attribute, not a mechanistic one. Rare mutations can also act through the same mechanism, and as we discuss below, “latent driver” mutations may also follow the same route, with “helper” mutations. Here, we review how biophysics provides mechanistic guidelines that extend precision medicine. We outline principles and strategies, especially focusing on mutations that drive cancer. Biophysics has contributed profoundly to deciphering biological processes. However, driven by data science, precision medicine has skirted some of its major tenets. Data science embodies genomics, tissue- and cell-specific expression levels, making it capable of defining genome- and systems-wide molecular disease signatures. It classifies cancer driver genes/mutations and affected pathways, and its associated protein structural data guide drug discovery. Biophysics complements data science. It considers structures and their heterogeneous ensembles, explains how mutational variants can signal through distinct pathways, and how allo-network drugs can be harnessed. Biophysics clarifies how one mutation—frequent or rare—can affect multiple phenotypic traits by populating conformations that favor interactions with other network modules. It also suggests how to identify such mutations and their signaling consequences. Biophysics offers principles and strategies that can help precision medicine push the boundaries to transform our insight into biological processes and the practice of personalized medicine. By contrast, “phenotypic drug discovery,” which capitalizes on physiological cellular conditions and first-in-class drug discovery, may not capture the proper molecular variant. This is because variants of the same protein can express more than one phenotype, and a phenotype can be encoded by several variants.
机译:生物物理原理如何帮助精密医学识别罕见的驾驶员突变?精确肿瘤学和药理学的实用方法的主要原则是,驱动程序突变非常频繁。但是,频率是统计属性,而不是机械属性。罕见的突变也可以通过相同的机制起作用,正如我们在下面讨论的那样,“潜在的驱动程序”突变也可能遵循相同的途径,带有“辅助”突变。在这里,我们回顾了生物物理学如何提供扩展精密医学的机制指南。我们概述了原理和策略,特别是关注导致癌症的突变。生物物理学为解密生物过程做出了巨大贡献。但是,在数据科学的推动下,精密医学已经摆脱了其一些主要宗旨。数据科学体现了基因组学,组织和细胞特异性表达水平,使其能够定义基因组和系统范围内的分子疾病特征。它对癌症驱动基因/突变和受影响的途径进行了分类,其相关的蛋白质结构数据指导了药物的发现。生物物理学是对数据科学的补充。它考虑了结构及其异质集成,解释了突变变体如何通过不同的途径发出信号,以及如何利用同种网络药物。生物物理学通过填充有利于与其他网络模块相互作用的构象,阐明了一个突变(频繁或罕见)如何影响多个表型性状。它还建议了如何识别此类突变及其信号转导的后果。生物物理学提供的原理和策略可帮助精密医学突破界限,将我们的见识转化为生物学过程和个性化医学的实践。相比之下,利用生理细胞条件和一流药物发现的“表型药物发现”可能无法捕获适当的分子变异。这是因为同一蛋白质的变体可以表达一种以上的表型,并且一种表型可以由几种变体编码。

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