Predicting allosteric communication pathways using motion correlation network
Background: Allosteric regulation can be described as the binding of an effector at one site switches the functionality of another site, often at distance. Although a wide variety of models have been proposed, the underlying mechanism of the allosteric communication remains unclear. In this work, we hypothesize that the allosteric communication between the allosteric site and catalytic site should be carried out along pathways of residues that have strongly correlated motions, so that information such as conformation change can be quickly transduced from one site to another.Results: (ⅰ) The intramolecular communication pathways of 10 out of 15 myosin proteins derived from our Motion Correlation Network (MCN) model agree with the pathways derived from multiple sequence alignment (MSA) in a very high statistically significant level (<1.0E -08). (ⅱ) The pathways of the remaining 5 myosin proteins, which all fall in the post-rigor state, are completely different from the pathways obtained from MSA and the disagreement suggests the possibility of the existence of a different route in the post-rigor state. (ⅲ) The intramolecular communication pathways of thrombin derived from our method agree with the pathways derived from electron density maps in a high statistically significant level (< 1.0E-05).Conclusions: We provide a simple and computationally inexpensive approach to identify the putative allosteric communication pathways. The excellent agreement between our results and previous works supports our hypothesis that the most efficient allosteric communication is through pathways of residues that have strongly correlated motions. Such an agreement also implies that sequence conservation, which has been used to identify allosteric communication pathways, may have a dynamics origin.
Tu-Liang Lin Guang Song
Computer Science Department, Iowa State University, 226 Atanasoff Hall, Ames, IA 50011, USA Computer Science Department, Iowa State University, 226 Atanasoff Hall, Ames, IA 50011, USA L.H.Bake
国际会议
The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)
北京
英文
588-598
2009-01-01（万方平台首次上网日期，不代表论文的发表时间）