Network analysis of circular permutations in multidomain proteins reveals functional linkages for uncharacterized proteins.
Various studies have implicated different multidomain proteins in cancer. However, there has been little or no detailed study on the role of circular multidomain proteins in the general problem of cancer or on specific cancer types. This work represents an initial attempt at investigating the potential for predicting linkages between known cancer-associated proteins with uncharacterized or hypothetical multidomain proteins, based primarily on circular permutation (CP) relationships. First, we propose an efficient algorithm for rapid identification of both exact and approximate CPs in multidomain proteins. Using the circular relations identified, we construct networks between multidomain proteins, based on which we perform functional annotation of multidomain proteins. We then extend the method to construct subnetworks for selected cancer subtypes, and performed prediction of potential link-ages between uncharacterized multidomain proteins and the selected cancer types. We include practical results showing the performance of the proposed methods.
Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA.
Donald
D
Adjeroh
Faculty of Software, Fujian Normal University, Fuzhou, Fujian, China.
Yue
Y
Jiang
Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, PA, USA.
Bing-Hua
BH
Jiang
Faculty of Software, Fujian Normal University, Fuzhou, Fujian, China.
Jie
J
Lin
cancer; circular patterns; functional annotation; multidomain proteins