GLN: a method to reveal unique properties of lasso type topology in proteins

Sci Rep. 2020 Sep 16;10(1):15186. doi: 10.1038/s41598-020-71874-2.

Abstract

Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a matrix diagram-for a pair of a loop and a tail-to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We show how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a matrix diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Databases, Protein
  • Datasets as Topic
  • Humans
  • Models, Molecular*
  • Models, Theoretical*
  • Molecular Dynamics Simulation
  • Protein Conformation
  • Protein Folding*
  • Proteins / chemistry*

Substances

  • Proteins