Characterizing the Effects of Protein and RNA Variability in Molecular Function and Interactions

项目摘要 本提案资助的父项目的科学目标(ESI的35米拉) 包括开发生物分子的全球概率和计算模型， 描述和量化蛋白质可变性及其相互作用的图景。我们的目标是 阐明功能突变的图景，它隐藏在更大的非 功能空间。我们正在利用这一功能图景来设计杂交转录 调节器、生物传感器、疾病相关蛋白突变的影响以及预测 二组分系统中的专一性网络。另一个重要目标是设计模型以 描述序列对蛋白质-蛋白质和蛋白质-核酸相互作用的依赖性。 这些模型将允许我们对推断的景观进行编码和预测识别，并 将我们的结果与实验技术相结合。泛函光谱的设计 由进化过程塑造的生物分子可变性将被用来估计影响 疾病突变、抗生素耐药性、生物分子传感器设计以及 相互作用网络上的序列组成。作为父母资助的研究目标 受益于算法开发，它还旨在将此类开发提供给 科学界。本科生的暑期研究体验将集中在 用于表征蛋白质-核酸识别的软件流水线的开发 可在网上公开使用，方便分析、预测和发现核酸序列 与关键蛋白质相互作用，包括一些与疾病相关的蛋白质。

Project Summary The scientific goals of the funded parent project of this proposal (R35 MIRA for ESI) include the development of global probabilistic and computational models of biomolecules that characterize and quantify the landscape of protein variability and their interactions. We aim to elucidate the landscape of functional mutations, which is hidden within the much larger non- functional space. We are using this functional landscape to engineer hybrid transcriptional regulators, bio-sensors, the effects of mutations in disease-related proteins as well as to predict specificity networks in two-component systems. Another important goal es to devise models to characterize the sequence dependance on protein-protein and protein-nucleic acid interactions. These models will allow us to encode and predict recognition from inferred landscapes and to integrate our results with experimental technologies. Devising the spectrum of functional biomolecular variability sculpted by evolutionary processes will be used to estimate the effects of mutations in disease, antibiotic resistance, biomolecular sensor design and the impact of sequence composition on interaction networks. As the research goals of the parent grant benefits from algorithmic development, it also aims to make such developments available to the scientific community. An undergraduate summer research experience will focus on the development of a software pipeline to characterize protein-nucleic acid recognition and make it publicly available online to facilitate analysis, prediction and discovery of nucleic acid sequences that interact with key proteins, including some related to disease.