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

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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