Penalized multidimensional fitting for protein movement detection

JOURNAL OF APPLIED STATISTICS(2017)

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摘要
The three-dimensional structure of a given protein can take different conformations depending upon the reaction it undergoes and its substrate/cofactor/partners binding state. Various methods exist to study these conformational changes but only one, called DynDom, is clearly focused on movement detection. An alternative method is proposed, making use of multivariate data analysis, called penalized Multidimensional Fitting (penalized MDF)' based on penalized movements of points in order to approach the distances between points after movement to the distances given by the reference matrix. The objective is to detect the amino acids that undergo an important movement by fitting the distances of one conformation to the distances of the second one by modifying only the coordinates of the first one. This method is applied to three different proteins.
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关键词
Multidimensional analysis,data analysis,conformational changes,ligand binding,penalization,optimization
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