Willy Wriggers, Pablo Chacón, Julio Kovacs, Florence Tama and Stefan Birmanns. Topology Representing Neural Networks Reconcile Biomolecular Shape, Structure, and Dynamics. Neurocomputing, 2004, Vol. 56, pp. 365-379.

Topology-representing networks (TRNs) generate reduced models of biomolecules and thereby facilitate the 5tting of molecular fragments into large macromolecular complexes. The components of such complexes undergo a wide range of motions, and shapes observed at low resolution often deviate from the known atomic structures. What is required for the modeling of such motions is a combination of global shape constraints based on the low-resolution data with a local modeling of atomic interactions. We present a novel Motion Capture Network that freezes inessential degrees of freedom to maintain the stereochemistryof an atomic model. TRN-based deformable models retain much of the mechanical properties of biological macromolecules. The elastic models yield a decomposition of the predicted motion into vibrational normal modes and are amenable to interactive manipulation with haptic rendering software.

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