Knoto-ID

Knoto-ID analyzes entanglement in open protein chains using the mathematical framework of knotoids to characterize backbone topology without closing chains into loops.


Key Features:

  • Knotoid Concept: Applies knotoids, an extension of classical knot theory for open curves, to evaluate entanglement without altering the protein backbone by loop closure.
  • Global and Local Topology Analysis: Performs global topology assessment of entire protein chains and local topology analysis via exhaustive examination of all subchains and identification of knotted cores.
  • Detection of Non-Trivial Folds: Detects topologically non-trivial protein folds that can be missed by conventional knot-detection methods.
  • Visualization Tools: Provides R scripts to generate projection maps, fingerprint matrices, and disk matrices for representation of topological data.
  • Implementation: Implemented in C++ and distributed under the GNU General Public License (GPL) version 2 or later.

Scientific Applications:

  • Protein topology characterization: Characterizes backbone entanglement to inform studies of protein folding, stability, and structure-function relationships.
  • Discovery of non-trivial folds: Identifies folds beyond classical knots, extending the scope of protein topology studies.
  • Local folding motif analysis: Maps local knotted regions and subchain entanglement to analyze local folding motifs and knotted cores.

Methodology:

Analyzes protein backbones as open curves using the knotoid mathematical framework without closing chains into loops and systematically examines subchains to identify knotted cores and characterize topology.

Topics

Details

License:
GPL-3.0
Maturity:
Mature
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R, C++
Added:
7/6/2019
Last Updated:
11/24/2024

Operations

Publications

Dorier J, Goundaroulis D, Benedetti F, Stasiak A. Knoto-ID: a tool to study the entanglement of open protein chains using the concept of knotoids. Bioinformatics. 2018;34(19):3402-3404. doi:10.1093/bioinformatics/bty365. PMID:29722808.

PMID: 29722808
Funding: - Leverhulme Trust: RP2013-K-017 - Swiss National Science Foundation: 31003A_166684

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