Title: Maxent-Stress Optimization of 3D Biomolecular Models,
Abstract: Knowing a biomolecule's structure is inherently linked to and a prerequisite
for any detailed understanding of its function. Significant effort has gone
into developing technologies for structural characterization. These
technologies do not directly provide 3D structures; instead they typically
yield noisy and erroneous distance information between specific entities such
as atoms or residues, which have to be translated into consistent 3D models.
Here we present an approach for this translation process based on
maxent-stress optimization. Our new approach extends the original graph drawing
method for the new application's specifics by introducing additional
constraints and confidence values as well as algorithmic components. Extensive
experiments demonstrate that our approach infers structural models (i. e.,
sensible 3D coordinates for the molecule's atoms) that correspond well to the
distance information, can handle noisy and error-prone data, and is
considerably faster than established tools. Our results promise to allow domain
scientists nearly-interactive structural modeling based on distance
constraints.