Research areas:

Protein-DNA InteractionProtein-DNA Interaction and structure-based transcription-factor binding site prediction
Protein-DNA interactions play a crucial role in the regulation of gene expression. Knowledge of protein-DNA interactions at the structural-level can provide insights into the mechanisms of gene regulation and can guide the design of novel therapeutic molecules. Our goal is to develop computational methods and resources for modeling protein-DNA interactions and predicting transcription factor (TF) binding sites on a genomic scale. More specifically, we are interested in structural aspects of protein-DNA interactions and aim to address two related questions: 1) given a 3-dimensional complex structure of a transcription factor and a DNA sequence, can we accurately evaluate the binding affinity and specificity between the transcription factor and candidate sequences? 2) In those cases where the protein-DNA complex structure is not available, can we build a reliable protein-DNA interaction model via predictive protein-DNA docking methods?



Research Funding:

NSF        Charlotte Research Institute

1. UNC Charlotte Startup fund, 8/2007-6/2010

2. CMC-UNC Charlotte Collaborative Grants Program
    "An Integrative Approach to Study the Transcriptional Regulation of ALAS1 by Heme", Co-PI, 5/2009-5/2010  

3. National Science Foundation (NSF), Division of Biological Infrastructure (DBI)
    NSF CAREER Award: "CAREER: A Structure-Based Approach to Transcription Factor-binding Site Prediction via Protein-DNA Docking",  PI, 7/2009-9/2015

4. National Science Foundation (NSF), Division of Biological Infrastructure (DBI)
   "Collaborative Research: ABI Innovation: Towards high performance flexible transcription factor-DNA docking",  PI, 8/2014-7/2017

5. National Science Foundation (NSF), Division of Graduate Education (DGE)
   "EDU: Collaborative: enhancing education in genetic privacy with integration of research in computer science and bioinformatics”, Co-PI (PI-Mindy Shi), 9/2015-8/2017

6. National Institutes of Health (NIH)
   "Structural Features of Specificity in Protein-DNA Recognition",  PI, 9/2015-8/2018