Skip to main content

Detect multimeric motifs.

Project description

Project description

LinkTetrado is algorithm designed for the identification and classification of multimeric nucleotide assemblies in nucleic acid structures. LinkTetrado automatically identifies nucleotides interacting with tetrads in a planar arrangement, allowing for the detection of pentads, hexads, heptads, octads, and beyond. It analyzes nucleic acid 3D structures, accepting both PDB and mmCIF file formats. It leverages the ElTetrado engine to extract detailed structural information about base pairs and tetrads in an input structure. Next, it searches the space in the vicinity of tetrads for possible nucleotides that could interact with the tetrads.

Polyadic motifs

Polyadic motifs - such as triads (3 bases), tetrads (4), pentads (5), hexads (6), heptads (7), and octads (8) - are formed when three or more nucleotides interact through hydrogen bonding, typically through their Hoogsteen or sugar edges, resulting in stable, ring-like networks where each base generally forms bonds with two adjacent bases. These polyadic motifs play a crucial role in enhancing the stability and structural complexity of nucleic acids and are involved in essential processes, including gene regulation and molecular recognition. The figure below illustrates schematic representations of example polyadic motifs in a cut, top down 3D visualization and a simple 2D graph.

Polyad Example Example polyadic motifs of different orders and their schematic representations: (A) pentad (5 nucleotides), (B) hexad (6 nucleotides), (C) heptad (7 nucleotides), and (D) octad (8 nucleotides). In the 3D models (top row), nucleotides forming the polyads are shown in color, coded by nucleotide type: green for guanine, blue for uracil or thymine, and red for adenine. Green thus highlights the guanine tetrad core.

Installation

Please run:

pip install linktetrado

Dependencies

The project is written in Python 3.8+ and requires NumPy, and ElTetrado (Zok et al., 2022; Popenda et al., 2020; Zok et al., 2020).

LinkTetrado parses the output of ElTetrado. It can also process PDB or PDBx/mmCIF files which will be first analyzed internally with ElTetrado.

Usage

usage: linktetrado [-h] [-i INPUT] [--print-eltetrado]
                   [--tilt-max TT_MAX] [--tilt-avg TT_AVG]
                   [--height-max HT_MAX] [--height-avg HT_AVG]
                   [--dist-in-max DT_INMAX] [--dist-out-max DT_OUTMAX]
                   [--lax-order] [-m MODEL]
                   [--stacking-mismatch STACKING_MISMATCH] [--strict]
                   [--no-reorder]

options:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        path to input PDB, PDBx/mmCIF file.
  --print-eltetrado     (optional) should ElTetrado analysis output also
                        be provided alongside multimer analysis.
  --tilt-max TT_MAX     (optional) maximum tilt in degrees between
                        potential polyad candidate nucleotide and all
                        tetrad nucleotides [default=55]
  --tilt-avg TT_AVG     (optional) average tilt in degrees between
                        potential polyad candidate nucleotide and all
                        tetrad nucleotides [default=45]
  --height-max HT_MAX   (optional) maximum height difference in Angstrem
                        between between potential polyad candidate
                        nucleotide and all tetrad nucleotides
                        [default=3.7]
  --height-avg HT_AVG   (optional) average height difference in Angstrem
                        between between potential polyad candidate
                        nucleotide and all tetrad nucleotides
                        [default=3.15]
  --dist-in-max DT_INMAX
                        (optional) maximum distance in Angstrem between
                        inner atoms between potential polyad candidate
                        nucleotide and all tetrad nucleotides
                        [default=13.75]
  --dist-out-max DT_OUTMAX
                        (optional) maximum distance in Angstrem between
                        outer atoms between potential polyad candidate
                        nucleotide and all tetrad nucleotides
                        [default=12.5]
  --lax-order           (optional) adjusts the algorithm’s filtering
                        mode, enabling the detection of polyads with
                        varying orders within a single stack
  -m MODEL, --model MODEL
                        (optional, ElTetrado) model number to process
  --stacking-mismatch STACKING_MISMATCH
                        a perfect tetrad stacking covers 4 nucleotides;
                        this option can be used with value 1 or 2 to
                        allow this number of nucleotides to be non-
                        stacked with otherwise well aligned tetrad
                        [default=2]
  --strict              nucleotides in tetrad are found when linked only
                        by cWH pairing
  --no-reorder          chains of bi- and tetramolecular quadruplexes
                        should be reordered to be able to have them
                        classified; when this is set, chains will be
                        processed in original order, which for
                        bi-/tetramolecular means that they will likely be
                        misclassified; use with care!

Examples

The repository contains 4 example structures that contain pentad, hexad, heptad and octad motifs as well as the expected default output from the program that is expected for each of them. The examples include structures 1JJP (pentad), 1EEG (hexad), 1oz8 (heptad), 1n7a (octad).

Bibliography

  1. Zok T, Popenda M, Szachniuk M (2020) ElTetrado: a tool for identification and classification of tetrads and quadruplexes, BMC Bioinformatics 21:40 (doi:10.1186/s12859-020-3385-1).

  2. Popenda M, Miskiewicz J, Sarzynska J, Zok T, Szachniuk M (2020) Topology-based classification of tetrads and quadruplex structures, Bioinformatics 36(4):1129-1134 (doi:10.1093/bioinformatics/btz738).

  3. Zok T, Kraszewska N, Miskiewicz J, Pielacinska P, Zurkowski M, Szachniuk M (2022) ONQUADRO: a database of experimentally determined quadruplex structures, Nucleic Acids Research 50(D1):D253-D258 (doi:10.1093/nar/gkab1118).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

linktetrado-1.0.0.tar.gz (13.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

linktetrado-1.0.0-py3-none-any.whl (11.5 kB view details)

Uploaded Python 3

File details

Details for the file linktetrado-1.0.0.tar.gz.

File metadata

  • Download URL: linktetrado-1.0.0.tar.gz
  • Upload date:
  • Size: 13.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for linktetrado-1.0.0.tar.gz
Algorithm Hash digest
SHA256 414cd8bb97b95a90188cdeb17fb376b50557e2be8ffcbd8a92a3f5f745823ae3
MD5 127713fa63db23b0a9c723ac1928aa14
BLAKE2b-256 347b5d566f764f9543381ee9da1feab69ceeda60788e1182bf3fc1c6526b13e3

See more details on using hashes here.

File details

Details for the file linktetrado-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: linktetrado-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 11.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for linktetrado-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 881ae8b2f75af42a6075a47255217ab28716b5fb33edcf3d1f9cfb5c7c14cada
MD5 a96d7b35ec94f43f87f949d0a9117729
BLAKE2b-256 70a11b3d9b92fc3cd22b921347c1cb3cbedfa0929db1fc40ce8435d18a93b22d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page