Voronoia 4-ever

Author:

Staritzbichler Rene1ORCID,Ristic Nikola1ORCID,Goede Andrean2ORCID,Preissner Robert23ORCID,Hildebrand Peter W145ORCID

Affiliation:

1. University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany

2. Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Physiology, Structural Bioinformatics Group, Berlin 10117, Germany

3. Charité –Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Information Technology, Science IT, Charitéplatz 1, 10117 Berlin, Germany

4. Charité –Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Charitéplatz 1, 10117 Berlin, Germany

5. Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany

Abstract

Abstract We present an updated version of the Voronoia service that enables fully automated analysis of the atomic packing density of macromolecules. Voronoia combines previous efforts to analyse 3D protein and RNA structures into a single service, combined with state-of-the-art online visualization. Voronoia uses the Voronoi cell method to calculate the free space between neighbouring atoms to estimate van der Waals interactions. Compared to other methods that derive van der Waals interactions by calculating solvent-free surfaces, it explicitly considers volume or packing defects. Large internal voids refer either to water molecules or ions unresolved by X-ray crystallography or cryo-EM, cryptic ligand binding pockets, or parts of a structural model that require further refinement. Voronoia is, therefore mainly used for functional analyses of 3D structures and quality assessments of structural models. Voronoia 4-ever updates the database of precomputed packing densities of PDB entries, allows uploading multiple structures, adds new filter options and facilitates direct access to the results through intuitive display with the NGL viewer. Voronoia is available at: htttp://proteinformatics.org/voronoia.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

Subject

Genetics

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