Link to Pubmed Publications

Shuju Bai

Southern University and A&M College, Department of Computer Science

Project Title

Modeling Protein-Substrate Interactions in the Lipoxygenase Family Using Computational Approaches


Marcia E. Newcomer, Ph.D.
Louisiana State University, Department of Biological Sciences

Seung-Jong Park
Louisiana State University, Department of Computer Science

Funding Periods

Pilot Project (May 1, 2009 – April 30, 2010)

Project R1 (May 1, 2010 - April 30, 2015)


Human lipoxygenases (LOX) play pivotal roles in the biosynthesis of leukotrienes and other biologically active eicosanoids. Specific inhibitors that can modulate the physiological and pathological effects of these potent signaling compounds are of high interest. Currently, there are no animal LOX structures that provide a model for how the substrate binds in the LOX active site, a model critical for the development of specific inhibitors. The overall goal of the proposed investigations is to develop substrate-LOX models that can be used for the development of specific anti-LOX inhibitors. The specific aims of the application are: 1) Model protein-substrate interactions in 8R-lipoxygenase. There is no crystal structure of a lipoxygenase in complex with its substrate arachidonic acid (AA) to reveal the structural basis for product specificity in this family of enzymes. Our recent 1.85 Å resolution structure of 8R-LOX provides a strong foundation for model enzyme-substrate interactions. We will utilize computational approaches (molecular dynamics simulation) to derive a model for the 8R-lipoxygenase-arachidonic acid binary complex. 2) "Test" the generally applicability of this model to lipoxygenases of different product specificity. The features of the 8R-LOX:AA model binding site must be able to account for the regio- and stereo-specificity of the enzyme, yet exhibit the potential flexibility to explain the range of specificities found within the LOX enzyme superfamily. Thus, we will use a data mining/homology modeling approach and molecular dynamics simulation to determine whether the 8R-LOX:AA model derived above is consistent with sequence differences in lipoxygenases of different product specificity. The results of our research will help understand the mechanism of substrate recognition in lipoxygenases and facilitate drug design to target lipoxygenases.