diSTruct v1.0: generating biomolecular structures from distance constraints

Oskar Taubert; Ines Reinartz; Henning Meyerhenke; Alexander Schug

doi:10.1093/bioinformatics/btz578

diSTruct v1.0: generating biomolecular structures from distance constraints

Bioinformatics. 2019 Dec 15;35(24):5337-5338. doi: 10.1093/bioinformatics/btz578.

Authors

Oskar Taubert¹, Ines Reinartz¹, Henning Meyerhenke², Alexander Schug³

Affiliations

¹ Steinbuch Centre for Computing, Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, Germany.
² Department of Computer Science, Humbold-Universität zu Berlin, Berlin, Germany.
³ John von Neumann Institute for Computing, Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich 52425, Germany.

PMID: 31329240
DOI: 10.1093/bioinformatics/btz578

Abstract

Summary: The distance geometry problem is often encountered in molecular biology and the life sciences at large, as a host of experimental methods produce ambiguous and noisy distance data. In this note, we present diSTruct; an adaptation of the generic MaxEnt-Stress graph drawing algorithm to the domain of biological macromolecules. diSTruct is fast, provides reliable structural models even from incomplete or noisy distance data and integrates access to graph analysis tools.

Availability and implementation: diSTruct is written in C++, Cython and Python 3. It is available from https://github.com/KIT-MBS/distruct.git or in the Python package index under the MIT license.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Biological Science Disciplines*
Molecular Biology
Software*