Aleksandra I Jarmolinska1,2, Anna Gambin2, Joanna I Sulkowska1,3. 1. Centre of New Technologies, Warsaw 02-097, Poland. 2. Department of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw 02-097, Poland. 3. Faculty of Chemistry, University of Warsaw, Warsaw 02-093, Poland.
Abstract
SUMMARY: The biggest hurdle in studying topology in biopolymers is the steep learning curve for actually seeing the knots in structure visualization. Knot_pull is a command line utility designed to simplify this process-it presents the user with a smoothing trajectory for provided structures (any number and length of protein, RNA or chromatin chains in PDB, CIF or XYZ format), and calculates the knot type (including presence of any links, and slipknots when a subchain is specified). AVAILABILITY AND IMPLEMENTATION: Knot_pull works under Python >=2.7 and is system independent. Source code and documentation are available at http://github.com/dzarmola/knot_pull under GNU GPL license and include also a wrapper script for PyMOL for easier visualization. Examples of smoothing trajectories can be found at: https://www.youtube.com/watch?v=IzSGDfc1vAY. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: The biggest hurdle in studying topology in biopolymers is the steep learning curve for actually seeing the knots in structure visualization. Knot_pull is a command line utility designed to simplify this process-it presents the user with a smoothing trajectory for provided structures (any number and length of protein, RNA or chromatin chains in PDB, CIF or XYZ format), and calculates the knot type (including presence of any links, and slipknots when a subchain is specified). AVAILABILITY AND IMPLEMENTATION: Knot_pull works under Python >=2.7 and is system independent. Source code and documentation are available at http://github.com/dzarmola/knot_pull under GNU GPL license and include also a wrapper script for PyMOL for easier visualization. Examples of smoothing trajectories can be found at: https://www.youtube.com/watch?v=IzSGDfc1vAY. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Mariusz Popenda; Tomasz Zok; Joanna Sarzynska; Agnieszka Korpeta; Ryszard W Adamiak; Maciej Antczak; Marta Szachniuk Journal: Nucleic Acids Res Date: 2021-09-27 Impact factor: 16.971