finding semirigid domains in biomolecules by clustering pair-distance variations

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ID: 213148
2014
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Abstract
Dynamic variations in the distances between pairs of atoms are used for clustering subdomains of biomolecules. We draw on a well-known target function for clustering and first show mathematically that the assignment of atoms to clusters has to be crisp, not fuzzy, as hitherto assumed. This reduces the computational load of clustering drastically, and we demonstrate results for several biomolecules relevant in immunoinformatics. Results are evaluated regarding the number of clusters, cluster size, cluster stability, and the evolution of clusters over time. Crisp clustering lends itself as an efficient tool to locate semirigid domains in the simulation of biomolecules. Such domains seem crucial for an optimum performance of subsequent statistical analyses, aiming at detecting minute motional patterns related to antigen recognition and signal transduction.
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kenn2014biomedfinding Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Michael Kenn;Reiner Ribarics;Nevena Ilieva;Wolfgang Schreiner
Journal spectrochimica acta - part a: molecular and biomolecular spectroscopy
Year 2014
DOI
10.1155/2014/731325
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