GISA: Using Gauss Integrals to identify rare conformations in protein structures

Grønbæk, Christian; Hamelryck, Thomas; Røgen, Peter

doi:10.1101/758029

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…Moreover, one can apply GLN approach to study entanglement between two structures none of which are closed loops. Lately new algorithm, GISA, was proposed to study local entanglement in protein chains and other biopolymers 39 . The algorithm computes Gauss integrals between many pairs of quite short fragments of chain and finds rare invariant values.…”

Section: Discussionmentioning

confidence: 99%

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

Niemyska

Millett

Sułkowska

2020

Sci Rep

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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.

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Section: Discussionmentioning

confidence: 99%

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

Niemyska

Millett

Sułkowska

2020

Sci Rep

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show abstract

“…Moreover, one can apply GLN approach to study entanglement between two structures none of which are closed loops. Lately new algorithm, GISA, was proposed to study local entanglement in protein chains and other biopolymers [40]. The algorithm computes Gauss integrals between many pairs of quite short fragments of chain and finds rare invariant values.…”

Section: Discussionmentioning

confidence: 99%

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

Niemyska¹,

Millett²,

Sułkowska³

2020

Preprint

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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 diagramfor 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 found that there are significantly more lassos with negative crossings than those with positive ones in proteins, the average value of maxGLN (maximal GLN between loop and pieces of tail) depends logarithmically on the length of a tail similarly as in the polymers. Next, we show the how high and low GLN values correlate with the internal flexibility 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.

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“…The appeal of this approach is that a computationally expensive pairwise comparison of protein structures can be avoided. Recently, GIT vectors were also used to identify unusual conformations in protein structures that could indicate the presence of errors or biologically interesting structural features [GHR20].…”

Section: Git Vectorsmentioning

confidence: 99%

Persistent topology of protein space

Hamilton¹,

Borgert²,

Hamelryck³

et al. 2021

Preprint

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Protein fold classification is a classic problem in structural biology and bioinformatics. We approach this problem using persistent homology. In particular, we use alpha shape filtrations to compare a topological representation of the data with a different representation that makes use of knot-theoretic ideas. We use the statistical method of Angle-based Joint and Individual Variation Explained (AJIVE) to understand similarities and differences between these representations.

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GISA: Using Gauss Integrals to identify rare conformations in protein structures

Cited by 3 publications

References 12 publications

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

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

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

Persistent topology of protein space

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