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Knowing a biomolecule's structure is inherently linked to and a prerequisitefor any detailed understanding of its function. Significant effort has goneinto developing technologies for structural characterization. Thesetechnologies do not directly provide 3D structures; instead they typicallyyield noisy and erroneous distance information between specific entities suchas atoms or residues, which have to be translated into consistent 3D models.  Here we present an approach for this translation process based onmaxent-stress optimization. Our new approach extends the original graph drawingmethod for the new application's specifics by introducing additionalconstraints and confidence values as well as algorithmic components. Extensiveexperiments demonstrate that our approach infers structural models (i. e.,sensible 3D coordinates for the molecule's atoms) that correspond well to thedistance information, can handle noisy and error-prone data, and isconsiderably faster than established tools. Our results promise to allow domainscientists nearly-interactive structural modeling based on distanceconstraints.

Maxent-Stress Optimization of 3D Biomolecular Models