TY - GEN A1 - Huisinga, Wilhelm A1 - Best, Christoph A1 - Cordes, Frank A1 - Roitzsch, Rainer A1 - Schütte, Christof T1 - From Simulation Data to Conformational Ensembles: Structure and Dynamics based Methods N2 - Statistical methods for analyzing large data sets of molecular configurations within the chemical concept of molecular conformations are described. The strategies are based on dependencies between configurations of a molecular ensemble; the article concentrates on dependencies induces by a) correlations between the molecular degrees of freedom, b) geometrical similarities of configurations, and c) dynamical relations between subsets of configurations. The statistical technique realizing aspect a) is based on an approach suggested by {\sc Amadei et al.} (Proteins, 17 (1993)). It allows to identify essential degrees of freedom of a molecular system and is extended in order to determine single configurations as representatives for the crucial features related to these essential degrees of freedom. Aspects b) and c) are based on statistical cluster methods. They lead to a decomposition of the available simulation data into {\em conformational ensembles} or {\em subsets} with the property that all configurations in one of these subsets share a common chemical property. In contrast to the restriction to single representative conformations, conformational ensembles include information about, e.g., structural flexibility or dynamical connectivity. The conceptual similarities and differences of the three approaches are discussed in detail and are illustrated by application to simulation data originating from a hybrid Monte Carlo sampling of a triribonucleotide. T3 - ZIB-Report - SC-98-36 KW - conformational ensemble KW - cluster method KW - structural and dynamical similarity KW - representative KW - conformation KW - essential degrees of freedom KW - transi Y1 - 1998 UR - https://opus4.kobv.de/opus4-zib/frontdoor/index/index/docId/379 UR - https://nbn-resolving.org/urn:nbn:de:0297-zib-3797 ER -