Excellence in Research: Deep Learning based approaches for protein post-translational modification site prediction

真核细胞的复杂性不能仅仅用基因和蛋白质来解释，而是通过它们复杂的调控来解释，这种调控涉及基于许多机制的相互作用。这种调节的一个重要方面是在mRNA翻译成蛋白质后进行的，由此细胞蛋白质经历修饰（翻译后修饰，PTM）。在研究的所有生命形式中，这些修饰都会影响蛋白质的结构及其功能，包括它们参与调控机制。确定这些PTM位点发生的位置对于正确阐明结构-功能关系至关重要。虽然湿实验室方法可以测试单个蛋白质的修饰和功能，但计算方法是表征PTM位点的有前途的高通量替代方法;因此，开发准确可靠的PTM位点预测方法已成为重要的研究领域。该项目非常符合该机构的使命和目标，正如NCA T的卓越2020所示：“对教育做出坚定的承诺，同时努力实现更密集的研究密集型环境”。这项卓越研究奖（EiR）将使项目研究人员能够开发和建立一个独立的，高质量的研究计划，这将影响NCA T的少数民族学生的研究经验和教育，该项目旨在为三个重要的翻译后蛋白质修饰事件（即磷酸化，甲基化位点和SUMO化）的位点开发准确的基于深度学习（DL）的预测因子。本项目旨在首先开发一种准确的DL方法用于磷酸化位点预测（最广泛研究的PTM之一），以解决采用这种方法的许多关键问题，包括所需的训练数据量，所需的架构复杂性等因素;一旦因子已经被定义并在磷酸化数据上训练，该方法将用于预测靶向赖氨酸残基的两种其他类型的PTM：甲基化和SUMO化。该项目将深入研究与生物信息学应用特定DL架构使用相关的三个重要问题，包括：i）所需的训练示例数量，ii）架构的复杂性与性能，iii）手工制作功能与简单功能的性能。此外，该项目旨在探索与使用简单特征与整合生物观察的更复杂特征有关的问题，以及创建计算实验所需的负数据集的最佳实践。该项目将提供一种新的和广泛适用的基于DL的方法来预测PTM，产生更准确和完整的注释，然后其他研究人员可以用来促进相关的生物学研究。 将创造新的教育和推广机会，以加强学生的教育和技能发展，特别是在DL方法和应用方面;学生招聘将侧重于为全国最大的HBCU北卡罗来纳州AT州立大学的妇女和少数民族学生创造机会。此外，该项目还将为学生建立一个国际研究体验计划，以访问日本的研究实验室。该项目还将为NCA T和邻近HBCU的学生提供专业职业准备的“SciPhD训练营”提供支持。开发的资源将在www.example.com上向社区提供http://bcb.ncat.edu.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

The complexity of eukaryotic cells cannot be explained by genes and proteins alone but, rather, by their complex regulation that involves interactions based on a number of mechanisms. One important aspect of this regulation is performed after translation of mRNA to protein, whereby cellular proteins undergo modification (post-translational modifications, PTMs). In all forms of life studied, these modifications affect both the structure of proteins and their functions, including their participation in regulatory mechanisms. Identifying where these PTM sites occur is essential to correctly elucidating structure-function relationships. While wet-lab methods can test individual protein modification and function, computational methods are a promising high-throughput alternative by which to characterize PTM sites; thus, development of accurate and reliable PTM site prediction methods has become an important area of research. The project fits well with the mission and goals of the institution, as indicated in NCA&T's Preeminence 2020: "to make a strong commitment to education while working towards a much more-intensive research-intensive environment". This Excellence in Research (EiR) award will enable the project researchers to develop and establish an independent, high-quality research program that will impact the research experience and education of minority students at NCA&T.This project aims to develop accurate Deep Learning (DL)-based predictors for the sites of three important post-translational protein modification events viz. phosphorylation, methylation sites and SUMOylation. This project aims to develop first an accurate DL approach for phosphorylation site prediction (one of the most widely studied PTMs) to tackle a host of key issues for adopting this method, including such factors as the required amount of training data, required complexity of the architecture among others; once the factors have been defined and trained on the phosphorylation data, the approach will be used to predict two other types of PTMs targeting lysine residues: methylation and SUMOylation. The project will provide insight into three important questions relevant to the use of DL architectures specific to applications in bioinformatics including: i) required number of training examples, ii) complexity of architecture vs. the performance, and iii) performance of hand-crafted features vs. simple features. In addition, the project aims to explore issues related to the use of simple features vs. more complex features that integrate biological observations, and best practices for the creation of negative datasets needed in computational experiments. The project will provide a novel and broadly applicable DL-based approach to predicting PTMs, producing more accurate and complete annotation that other researchers can then use to facilitate related biological studies. New education and outreach opportunities will be created for enhancing educational offerings and skills development in students, particularly in DL methods and applications; student recruitment will focus on creating opportunities for women and minority students at North Carolina A&T State University, the nation's largest HBCU. In addition, the project will establish an international research experience program for students, to visit research labs in Japan. This project will also provide support to conduct the "SciPhD Bootcamp" for professional career preparation for students from NCA&T and neighboring HBCUs. The developed resources will be accessible to the community at http://bcb.ncat.edu.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.