title: Finding semirigid domains in biomolecules by clustering pair-distance variations.
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.
authors: Section of Biosimulation and Bioinformatics, Center for Medical Statistics, Informatics, and Intelligent Systems (CeMSIIS), Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
authors: Michael
authors: 0000-0002-8998-8005
authors: M
authors: Kenn
authors: Section of Biosimulation and Bioinformatics, Center for Medical Statistics, Informatics, and Intelligent Systems (CeMSIIS), Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
authors: Reiner
authors: 0000-0002-5743-5166
authors: R
authors: Ribarics
authors: Institute for Nuclear Research and Nuclear Energy (INRNE), Bulgarian Academy of Sciences, 72, Tzarigradsko Chaussee, 1784 Sofia, Bulgaria.
authors: Nevena
authors: 0000-0002-2372-2319
authors: N
authors: Ilieva
authors: Section of Biosimulation and Bioinformatics, Center for Medical Statistics, Informatics, and Intelligent Systems (CeMSIIS), Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
authors: Wolfgang
authors: W
authors: Schreiner
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology; D017143:Fuzzy Logic; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000235:genetics / Q000276:immunology*; D008962:Models, Theoretical; D056004:Molecular Dynamics Simulation; D020411:Oligonucleotide Array Sequence Analysis; D010363:Pattern Recognition, Automated; D015398:Signal Transduction