Kavraki Lab

Physical and Biological Computing

Many large protein complexes undergo extensive conformational changes as part of their functionality. Tracing these changes is important for understanding the way these proteins function. It is not always possible to obtain a high resolution structure for very large complexes. While many conformational search methods explore the motions of atomic resolution protein structures, little has been done to handle the abundance of coarser resolution data available. Traditional conformational search methods are impractical for very large complexes due to the amount of computational time involved. Moreover, they cannot be applied to coarser resolution data where structural information may be partial or missing. To address this problem, we propose a novel computational methodology to efficiently trace the conformational changes in biological macromolecules represented as medium resolution structures. We develop and apply a search method from robotics to structural information. Our method is unique in its ability to conduct a computationally tractable search, using approximate data to obtain approximate but reliable results. The pathways obtained by this method can be useful in understanding protein motion and functionality. To provide a baseline test for our method, we tested it on Adenylate Kinase and the GroEL monomer. We show that we can produce low energy conformational pathways with accuracy well below the structure's resolution level. This method is a promising first step towards exploring the conformational motion of even larger complexes.
Path for a GroEL monomer This work is done in collaboration with Dr. Wah Chiu from Baylor College of Medicine.