Topoly: Python package to analyze topology of polymers

Dąbrowski-Tumański, Paweł; Rubach, Paweł; Niemyska, Wanda; Greń, Bartosz Ambroży; Sułkowska, Joanna I.

doi:10.1093/bib/bbaa196

Cited by 49 publications

(57 citation statements)

References 72 publications

(72 reference statements)

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“…Details of this method were given in our previous work 13 , 14 . To compute GLNs among cyclic chains and ring polymers, we used the Topoly Python package 58 . For a catenated cyclic chain and ring pair, the GLN was equal to 1.…”

Section: Methodsmentioning

confidence: 99%

Efficient compressed database of equilibrated configurations of ring-linear polymer blends for MD simulations

et al. 2022

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To effectively archive configuration data during molecular dynamics (MD) simulations of polymer systems, we present an efficient compression method with good numerical accuracy that preserves the topology of ring-linear polymer blends. To compress the fraction of floating-point data, we used the Jointed Hierarchical Precision Compression Number - Data Format (JHPCN-DF) method to apply zero padding for the tailing fraction bits, which did not affect the numerical accuracy, then compressed the data with Huffman coding. We also provided a dataset of well-equilibrated configurations of MD simulations for ring-linear polymer blends with various lengths of linear and ring polymers, including ring complexes composed of multiple rings such as polycatenane. We executed 109 MD steps to obtain 150 equilibrated configurations. The combination of JHPCN-DF and SZ compression achieved the best compression ratio for all cases. Therefore, the proposed method enables efficient archiving of MD trajectories. Moreover, the publicly available dataset of ring-linear polymer blends can be employed for studies of mathematical methods, including topology analysis and data compression, as well as MD simulations.

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Section: Methodsmentioning

confidence: 99%

Efficient compressed database of equilibrated configurations of ring-linear polymer blends for MD simulations

et al. 2022

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“…The protein gaps were filled with a straight interval. Topology determination The topology of θ-curves was determined using the tools from Topoly package [30], utilizing also the HOMFLY-PT polynomial for knot determination [56,57,58]. Knotoids were analyzed with Knoto-ID software [59].…”

Section: Methodsmentioning

confidence: 99%

“…In particular, we removed all structures with artificially long bonds or improbable gap filling. The topology of a θ-curve was analyzed with three orthogonal methods implemented in the Topoly package [30]: calculation of the Yamada polynomial [31], identification of the Kauffman's boundary link analysis [32], and by calculation of the constituent knots (the knots formed by pairs of arcs). The analysis of the constituent knots was done as a validation of the results, as these knots do not distinguish well even the simplest θ-curves.…”

Section: The Algorithmmentioning

confidence: 99%

$θ$-curves in proteins

Dabrowski-Tumanski,

Goundaroulis,

Stasiak

et al. 2019

Preprint

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Apart from the knots formed by the main-chain, the proteins can form numerous topological structures, when included the covalent and ion-mediated interactions. In this work, we define the protein non-trivial θ-curves and identify 7 different topologies in all structures known up to date. We study the correlation of the motif with the function and organism of origin, and pointing the similarity with main-chain knots, we show that some motifs may indeed be functional. We also analyze the folding and bridge-induced stability of an exemplary protein with θ-curve motif and provide a catalogue of possible θ-curves in proteins.

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“…A comparison of different knot polynomials is included in a description of the Python package Topoly, which is designed to find and categorize self-entangled proteins (Dabrowski-Tumanski et al, 2020). The authors have programmed several lesser-known polynomials in addition to the standard ones.…”

Section: Algorithmic Considerations 21 Knots and Linksmentioning

confidence: 99%

The need for a new generation of substructure searching software

Raithby¹,

Taylor²

2021

Acta Crystallogr Sect B

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Advances in synthetic chemistry mean that the molecules now synthesized include increasingly complex entities with mechanical bonds or extensive frameworks. For these complex molecular and supramolecular species, single-crystal X-ray crystallography has proved to be the optimal technique for determining full three-dimensional structures in the solid state. These structures are curated and placed in structural databases, the most comprehensive of which (for organic and metallo–organic structures) is the Cambridge Structural Database. A question of increasing importance is how users can search such databases effectively for these structures. Here some of the classes of complex molecules and supramolecules and the challenges associated with searching for them are highlighted. The idea of substructure searches that involve topological searches as well as searches for molecular fragments is developed, and significant enhancements are proposed to substructure search programs that are both achievable and highly beneficial for both the database user community and the broader chemistry community.

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Topoly: Python package to analyze topology of polymers

Cited by 49 publications

References 72 publications

Efficient compressed database of equilibrated configurations of ring-linear polymer blends for MD simulations

Efficient compressed database of equilibrated configurations of ring-linear polymer blends for MD simulations

$θ$-curves in proteins

The need for a new generation of substructure searching software

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