TY - CHAP A1 - Galliat, Tobias A1 - Deuflhard, Peter A1 - Roitzsch, Rainer A1 - Cordes, Frank ED - Schlick, T. ED - Gan, H. T1 - Automatic Identification of Metastable Conformations via Self-Organized Neural Networks T2 - Computational Methods for Macromolecules Y1 - 2002 UR - http://www.zib.de/PaperWeb/abstracts/ZR-00-51 IS - 24 PB - Springer ER - TY - CHAP A1 - Galliat, Tobias A1 - Deuflhard, Peter A1 - Roitzsch, Rainer A1 - Cordes, Frank T1 - Automatic identification of metastable conformations via self-organized neural networks T2 - Proceedings of the 3rd International Workshop on Algorithms for Macromolecular Modelling Y1 - 2002 ER - TY - CHAP A1 - Fischer, Alexander A1 - Schütte, Christof A1 - Deuflhard, Peter A1 - Cordes, Frank ED - Schlick, T. ED - Gan, H. T1 - Hierarchical Uncoupling-Coupling of Metastable Conformations T2 - Computational Methods for Macromolecules Y1 - 2002 UR - http://www.zib.de/PaperWeb/abstracts/ZR-01-03 IS - 24 SP - 235 EP - 259 PB - Springer ER - TY - CHAP A1 - Fischer, Alexander A1 - Schütte, Christof A1 - Deuflhard, Peter A1 - Cordes, Frank ED - Schlick, T. ED - Gan, H. T1 - Hierarchical Uncoupling-Coupling of Metastable Conformations T2 - Computational Methods for Macromolecules Y1 - 2002 UR - http://publications.imp.fu-berlin.de/128/ VL - 24 SP - 235 EP - 259 PB - Springer ER - TY - GEN A1 - Cordes, Frank A1 - Weber, Marcus A1 - Schmidt-Ehrenberg, Johannes T1 - Metastable Conformations via successive Perron-Cluster Cluster Analysis of dihedrals N2 - Decomposition of the high dimensional conformational space of bio-molecules into metastable subsets is used for data reduction of long molecular trajectories in order to facilitate chemical analysis and to improve convergence of simulations within these subsets. The metastability is identified by the Perron-cluster cluster analysis of a Markov process that generates the thermodynamic distribution. A necessary prerequisite of this analysis is the discretization of the conformational space. A combinatorial approach via discretization of each degree of freedom will end in the so called ''curse of dimension''. In the following paper we analyze Hybrid Monte Carlo simulations of small, drug-like biomolecules and focus on the dihedral degrees of freedom as indicators of conformational changes. To avoid the ''curse of dimension'', the projection of the underlying Markov operator on each dihedral is analyzed according to its metastability. In each decomposition step of a recursive procedure, those significant dihedrals, which indicate high metastability, are used for further decomposition. The procedure is introduced as part of a hierarchical protocol of simulations at different temperatures. The convergence of simulations within metastable subsets is used as an ''a posteriori'' criterion for a successful identification of metastability. All results are presented with the visualization program AmiraMol. T3 - ZIB-Report - 02-40 KW - metastability KW - Perron-Cluster Cluster Analysis KW - curse of dimension KW - Hybrid Monte Carlo KW - significant dihedrals Y1 - 2002 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-7074 ER -