DNA-Binding Activity of Human Proteins

描述（由申请人提供）： 长期以来一直令人困惑的是，相对少量的转录因子（TF）如何精确控制人类中约21，000个ORF和可能10倍以上的非编码RNA的表达。转录领域的另一个主要差距是缺乏一套简单的规则来解释蛋白质-DNA相互作用的特异性。这些缺口是一个主要问题，因为在它们被填补之前，对转录电路及其基本原理的理解仍然是非常不完整的。长期目标是表征人类蛋白质-DNA相互作用（PDI）网络，并阐明使用蛋白质微阵列技术和生物信息学的合力转录调控的基本分子机制。本申请的目的是鉴定序列特异性非常规DNA结合蛋白（uDBPs）的全面列表，并更好地定义指定TF-DNA相互作用的规则。核心假设是，无偏的，高通量的PDIs分析将揭示转录调控网络和途径的规则和组织。该假设是根据申请人实验室中产生的初步数据制定的。这项研究的基本原理是，一旦产生了序列特异性uDBPs的全面列表，并且一旦完成了对TF的PDI和晶体结构的全面分析，我们将能够预测和测试uDBPs的新生理作用，并产生更好的规则来定义人类许多TF亚家族的DNA结合特异性。在强有力的初步数据的指导下，这一假设将通过追求两个具体目标进行测试：1）使用人类蛋白质组微阵列全面识别DNA结合蛋白; 2）识别和表征定义DNA结合偏好的TF识别结构域。在第一个目标下，500个预测和已知的DNA基序将被探测到由约17，000个单独纯化的蛋白质组成的人类蛋白质组微阵列，这是在申请人的实验室制造的新工具，以生成uDBP的全面列表。在一系列生物信息学分析和预测的基础上，将在申请人的实验室中对1-2个uDBP进行深入表征，以阐明其在转录调控中的生理作用。在第二个目标下，将分析各种物种的TF-DNA复合物的现有晶体结构，以鉴定指示PDI的TF的非接触氨基酸残基（AA）。将对选定的一组已鉴定残基进行进一步实验检测。该方法是创新的，因为它利用了基于活性的筛选人类蛋白质组中的uDBPs和无偏调查的贡献，由非接触AA来决定DNA结合特异性。这项拟议中的研究意义重大，因为它将是人类DNA结合活动的第一个系统性分析，将提供转录控制和调节参与者的全面清单，并且因为一套更好定义的规则最终将为科学界提供罗塞塔石碑解码人类转录调节电路。最终，这些知识有可能为TF相关疾病的更好治疗方法的开发提供信息。

DESCRIPTION (provided by applicant): It has long been puzzling how a relatively small number of transcription factors (TFs) can precisely control expression of ~21,000 ORFs and probably 10-fold more non-coding RNAs in humans. Another major gap in the transcription field is a lack of a simple set of rules that explain the specificity of protein-DNA interactions. These gaps represent a major problem because, until they are filled, understanding of the transcription circuitry and its underlining principles will remain highly incomplete. The long-term goals are to characterize the human protein-DNA interaction (PDI) network and elucidate the underlining molecular mechanisms of transcriptional regulation using the combined force of protein microarray technologies and bioinformatics. The objectives of this particular application are to identify a comprehensive list of sequence-specific unconventional DNA-binding proteins (uDBPs) and to better define rules that specify TF-DNA interactions. The central hypothesis is that unbiased, high-throughput profiling of PDIs will reveal rules and organization of transcriptional regulatory networks and pathways. This hypothesis has been formulated on the basis of preliminary data produced in the applicants< laboratories. The rationale for the proposed research is that, once a comprehensive list of sequence-specific uDBPs is generated and once a comprehensive analysis of PDIs and crystal structures of TFs is completed, we will be able to predict and test novel physiological roles of uDBPs and generate better rules that define DNA-binding specificity for many TF subfamilies in humans. Guided by strong preliminary data, this hypothesis will be tested by pursuing two specific aims: 1) Comprehensively identify DNA-binding proteins using human proteome microarrays; and 2) Identify and characterize TF recognition domains that define DNA-binding preference. Under the first aim, 500 predicted and known DNA motifs will be probed to a human proteome microarray composed of ~17,000 individually purified proteins, a new tool fabricated at the applicants' laboratory, to generate a comprehensive list of uDBPs. On the basis of a series of bioinformatics analysis and prediction, 1-2 uDBPs will be characterized in-depth to elucidate the physiological roles in transcription regulation in the applicants' laboratories. Under the second aim, the existing crystal structures of TF-DNA complexes of various species will be analyzed to identify non-contacting amino acid residues (AAs) of TFs that dictate PDIs. A selected set of the identified residues will be further tested experimentally. The approach is innovative, because it utilizes activity-based screens for uDBPs in the human proteome and an unbiased survey for contribution by non-contacting AAs to dictate DNA-binding specificity. This proposed research is significant, because it will be the first systematic profiling of DNA-binding activities in humans that will offer a comprehensive list of participants in transcriptional control and regulation, and because a set of better-defined rules will ultimately provide the scientific community with a Rosetta Stone for decoding human transcriptional regulatory circuitry. Ultimately, such knowledge has the potential to inform the development of better therapeutics for TF-related diseases.