Transcription Factor-DNA Interactions: Structural Classification and Prediction

描述(由申请人提供)： 人类疾病通常是由于生物体中特定基因转录过度或不足引起的。被称为转录因子(Tf)的蛋白质通过结合DNA上被称为Tf结合位点(TFBS)的特定位点来调节基因的转录。研究转铁蛋白如何识别转铁蛋白的策略之一是通过开发计算机算法来预测基因组序列中的转铁蛋白。大多数算法应用从TFBS的DNA序列获得的位置特定权重矩阵(PWM)。然而，在人类基因组中已经识别和预测的3000多个转录因子中，只有300个转录因子构建了pWMS。为了将预测方法应用于具有未知PWMS的TF，采用了两种方法。第一个建议为拥有相似DNA结合域的转录因子家族生成PWMS。然而，在现有的转录因子分类中，来自同一家族的转录因子通常不识别相同的DNA序列。因此，有一种新的能够推动TFBS预测的TFS分类是有吸引力的。第二种方法是在TF-DNA复合体的三维结构上构建PWMS。我们的初步结果表明，这种方法也可以应用于TF家族，通过TFBS序列和TF-DNA复合体的3D结构的比对，可以得到一个TF家族的脉宽调制。建议将生成的TF族PWMS的性能用于验证TF族的分类。该建议的目的是研究转录因子DNA结合域的序列和结构的相似性如何与转录因子结合域的相似性有关。这项研究将集中在至少有一种TF-DNA复合体或其紧密同系物的三维结构的TF。将通过以下具体目标实现这一目标：(1)根据转录因子和转录因子家族的序列和结构的相似性，对转录因子的DNA结合域进行自动分类；(2)开发一种基于结构的方法来预测转录因子家族的转录因子结合域；(3)通过以查询和网络工具的形式提供分类和预测方法的网络资源来传播结果。这项研究的结果将对注释人类和其他生物基因组中的转录因子和调节区具有价值。它们还将有助于破译基因调控网络，并设计用于治疗与基因调控不足相关的疾病的药物。拟议的研究结果将有助于对人类和其他生物基因组中的转录因子和调节区进行注释。这些信息对于设计治疗与基因调控不足相关的疾病的药物具有重要意义。

DESCRIPTION (provided by applicant): Human diseases often arise from excessive or deficient transcription of particular genes in an organism. Proteins known as transcription factors (TF) regulate transcription of a gene through binding specific sites on DNA known as TF binding sites (TFBS). One of the strategies used to study how TFs recognize TFBSs is through the development of computer algorithms for predicting TFBSs in genomic sequence. Most algorithms apply position-specific weight matrices (PWM) obtained from DNA sequences of TFBSs. However, for more than 3,000 TFs that have been identified and predicted in the human genome, PWMs were built for only 300 TFs. To apply the prediction methods to TFs with unknown PWMs, two approaches are applied. The first one proposes generating PWMs for families of TFs sharing similar DNA-binding domains. However, TFs from the same family, as designated in the existing classifications of TFs, often do not recognize the same DNA sequences. Hence, there is an appeal to a new classification of TFs able to drive the prediction of TFBSs. The second approach is to build PWMs on three- dimensional (3D) structures of TF-DNA complexes. As our preliminary results indicate, this approach can also be applied to families of TFs a PWM can be obtained for a TF family through alignment of TFBS sequences and 3D structures of TF-DNA complexes. The performance of such generated PWMs for TF families is suggested to be used for validation of the classification of TFs. The goal of the proposal is to study how similarity in sequences and structures of DNA-binding domains of TFs relates to the similarity of TFBSs. The research will focus on TFs for which at least one 3D structure of TF-DNA complex or its close homolog is available. The goal will be attained through the following specific aims: (1) Develop an automatic classification of DNA-binding domains of TFs based on similarity of sequences and structures of TFs and TFBSs; (2) Develop a structure-based approach to the prediction of TFBSs for families of TFs; and (3) Disseminate the results by means of a web resource providing access to the classification and prediction methods in the form of queries and web tools. The results of the study will be valuable for annotating TFs and regulatory regions in genomes of human and other organisms. They will also facilitate deciphering of gene regulatory networks and designing drugs for treatment of diseases associated with inadequate gene regulation. The results of the proposed study will facilitate annotating transcription factors and regulatory regions in genomes of human and other organisms. This information is significant for designing drugs for treatment of diseases associated with inadequate gene regulation.