Collaborative Research: ABI Innovation: Towards high performance flexible transcription factor-DNA docking

蛋白质和DNA之间的分子相互作用在DNA修饰和基因调控等许多基本生物学过程中起着至关重要的作用。转录因子是一组特殊的蛋白质，它们与基因组中特定的DNA序列相互作用，调节基因的表达。了解转录因子-DNA在结构水平上的相互作用有助于阐明蛋白质-DNA识别的基本机制。该项目旨在为蛋白质-DNA柔性对接开发新的计算算法。本项目的重点是对转录因子-DNA复合体结构进行建模。计算对接通过填补由于实验方法的限制而在复杂结构图景中的空白，已经成为理解复杂模型的实验方法的一种经济高效的替代方案。更好地了解蛋白质-DNA相互作用有助于刺激药物设计的创新。该项目开发的技术可以很容易地应用于其他类型的计算对接研究。这个项目将为学生提供一个跨学科和协作的研究环境。该项目带来的智力挑战和教育机会将有助于相关研究生和博士后成为相关领域的独立研究人员。计算对接是结构生物信息学中的一个巨大挑战。蛋白质-DNA对接的一个主要瓶颈是对巨大搜索空间的采样。与假设刚性蛋白质和DNA结构的刚性对接相比，柔性蛋白质-DNA对接的采样要困难得多。在柔性对接中，除了探索蛋白质和DNA分子的相对位置外，还需要考虑蛋白质和DNA分子的灵活性，因为蛋白质和DNA分子相互作用时会发生构象变化。高效的采样算法和加速的计算将是实现更高精度的蛋白质-DNA对接的关键。将开发有效采样转录因子-DNA构象的新算法来模拟分子识别机制。这一研究项目的成果将发表在国际同行评议的期刊上，并在科学会议上介绍，以确保向科学界广泛传播。Http://guolab.uncc.edu

Molecular interactions between proteins and DNA play crucial roles in many fundamental biological processes such as DNA modification and gene regulation. Transcription factors are a special group of proteins that interact with specific DNA sequences in the genome to regulate gene expression. Knowledge of transcription factor-DNA interactions at the structural level can help elucidate the fundamental mechanisms of protein-DNA recognition. This project aims to develop novel computational algorithms for flexible protein-DNA docking. The focus of this project is to model transcription factor-DNA complex structures. Computational docking, by filling the gap in the complex structure landscape due to the limitation of experimental methods, has become a cost-efficient alternative to experimental approaches to understanding complex models. A better understanding of protein-DNA interaction can help stimulate innovations in drug designs. The techniques developed in this project can be readily applied to other types of computational docking studies. This project will provide students an interdisciplinary and collaborative research environment. The intellectual challenges and educational opportunities from this project will help prepare the graduate students and postdoc involved to become independent researchers in related fields.Computational docking represents a grand challenge in structural bioinformatics. One major bottleneck of protein-DNA docking is the sampling of the enormous search space. Compared to rigid-docking that assumes rigid protein and DNA structures, sampling of flexible protein-DNA docking is much more difficult. In flexible docking, in addition to exploring the relative positions of the protein and DNA molecules, the flexibility of protein and DNA needs to be also considered since protein and DNA molecules undergo conformational changes upon interaction. Efficient sampling algorithms and sped-up computation will be critical for achieving higher accuracy in protein-DNA docking. Novel algorithms for efficient sampling of transcription factor-DNA conformations will be developed to simulate the molecular recognition mechanism. The results of this research project will be published in international peer-reviewed journals and presented at scientific meetings to ensure broad dissemination to the scientific community. http://guolab.uncc.edu