PyLasso: a PyMOL plugin to identify lassos

Aleksandra M Gierut; Wanda Niemyska; Pawel Dabrowski-Tumanski; Piotr Sulkowski; Joanna I Sulkowska

doi:10.1093/bioinformatics/btx493

PyLasso: a PyMOL plugin to identify lassos

Bioinformatics. 2017 Dec 1;33(23):3819-3821. doi: 10.1093/bioinformatics/btx493.

Authors

Aleksandra M Gierut^{1

2}, Wanda Niemyska¹, Pawel Dabrowski-Tumanski^{1

3}, Piotr Sulkowski^{4

5}, Joanna I Sulkowska^{1

3}

Affiliations

¹ Centre of New Technologies, University of Warsaw, Banacha 2c, Warsaw, 02-097, Poland.
² Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Łojasiewicza 11, Cracow, 30-348, Poland.
³ Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw, 02-093, Poland.
⁴ Faculty of Physics, University of Warsaw, Pasteura 5, Warsaw, 02-093, Poland.
⁵ Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, 91125, USA.

PMID: 28961868
DOI: 10.1093/bioinformatics/btx493

Abstract

Summary: Entanglement in macromolecules is an important phenomenon and a subject of multidisciplinary research. As recently discovered, around 4% of proteins form new entangled motifs, called lassos. Here we present the PyLasso-a PyMOL plugin to identify and analyse properties of lassos in proteins and other (bio)polymers, as well as in other biological, physical and mathematical systems. The PyLasso is a useful tool for all researchers working on modeling of macromolecules, structure prediction, properties of polymers, entanglement in fluids and fields, etc.

Availability and implementation: The PyLasso and tutorial videos are available at http://pylasso.cent.uw.edu.pl.

Contact: jsulkowska@cent.uw.edu.pl.

MeSH terms

Computational Biology / methods*
Macromolecular Substances / chemistry*
Models, Molecular
Protein Conformation
Proteins / chemistry*
Software*

Substances

Macromolecular Substances
Proteins