fingernat-pymol-plugin

PyMOL plugin to visualize interactions detected by the fingeRNAt program

https://github.com/filipspl/fingernat-pymol-plugin

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.6%) to scientific vocabulary

Keywords

molecular-interactions molecular-modeling pymol-plugin visualization

Keywords from Contributors

hack
Last synced: 6 months ago · JSON representation ·

Repository

PyMOL plugin to visualize interactions detected by the fingeRNAt program

Basic Info
  • Host: GitHub
  • Owner: filipsPL
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.81 MB
Statistics
  • Stars: 4
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 7
Topics
molecular-interactions molecular-modeling pymol-plugin visualization
Created over 4 years ago · Last pushed about 3 years ago
Metadata Files
Readme License Citation Zenodo

README.md

fingernat-pymol-plugin

About

logo_fingernat

This PyMOL plugin visualizes interactions detected by the fingeRNAt progam. This means that you need to run it first and generate data to be visualized in this plugin. But don't worry, it's quite simple :)

This plugin works best with PyMOL >= 2.2.3 and Python 3.

Check Markdown links DOI cffconvert

To cite: Szulc, N. A., Mackiewicz, Z., Bujnicki, J. M., & Stefaniak, F. (2022). fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions. PLOS Computational Biology, 18(6), e1009783. https://doi.org/10.1371/journal.pcbi.1009783

This repo DOI: DOI

Installation

Prerequisities

The plugin works under the Python 3 and makes use of the pandas module. To install it:

```bash

using pip

python3 -m pip install pandas

or conda

conda install pandas

or in debian/ubuntu using apt:

apt install python3-pandas

or install the full conda environment of pymol and pandas, ready to install this plugin

conda create -y --name pymol-pandas -c conda-forge python">=3.5" pandas pymol-open-source ```

Plugin installation in PyMOL

  1. In PyMOL window go to top menu - Plugin -> Plugin manager -> Install new plugin
  2. In the URL field paste one of the following links:
    • the latest release: <!-- RELEASESTART -->https://github.com/filipsPL/fingernat-pymol-plugin/archive/refs/tags/0-4-2-8.zip<!-- RELEASEEND -->,
    • or the latest code archive: https://github.com/filipsPL/fingernat-pymol-plugin/archive/refs/heads/main.zip

click Fetch, confirm the installation and the path.

  1. The fingeRNAt plugin is available from the Plugin menu:

Compatibility and tests

This PyMOL plugin was tested in the following setups:

| PyMOL version | Linux | MacOS | Windows | | ------------- |:-----:|:-----:|:-------:| | 2.2.3 | ✅ | | | | 2.3.2 | ✅ | | | | 2.4.0 | ✅ | ✅ | | | 2.5.0 | ✅ | | | | 2.6.0a | ✅ | | |

Usage

  1. Load into PyMOL nucleic acid and ligand structures you had used to detect interactions with the fingeRNAt.

  2. Open the fingeRNAt plugin, click Browse and point to the DETAIL_... tsv file which was generated by fingeRNAt.

  3. Click Proceed!

  1. A bunch of new groups and objects are created:

  • Interactions: objects holding detected interactions. The exact number depends of the detected inteactions types.
  • Receptor preferences: objects showing preferences of the receptor for forming/accomodating the given type of interaction.
  • Ligand preferences: objects showing preferences of the ligand binding pocket for forming/accomodating the given type of interaction.
  • Neighbours: fragment of the receptor containing residues which form interactions with ligand

Each group and object can be hidden/shown separately.

  1. Each ligand's model (state) contains interactions detected for this particular model. The last model (state) contains the visual legend of the detected interactions:

Additionally, the color codes are printed in the console.

---------- Colors legend: ----------- Hydrogen bond (HB) is presented in marine Cation-anion (CA) is presented in red Halogen bond (HAL) is presented in purple Lipophilic (Lipophilic) is presented in silver Pi-stacking (Pi_Stacking) is presented in orange Pi-cation (Pi_Cation) is presented in green Pi-anion (Pi_Anion) is presented in hotpink Water-mediated (Water-mediated) is presented in blue Ion-mediated (Ion-mediated) is presented in salmon any_contact (any_contact) is presented in teal

The exact number of interactions depends on the input data.

Screenshots

| pymol | description | | -------------------------------- | ------------------------------------------------------------------------------ | | | Overview of the formed interactions | | | Receptor preferences | | | Ligand preferences in the ligand binding site | | | Preferred positions of Pi-involving interactions and cation anion-interactions | | | As above, but for the receptor | | | User defined interactions; some bonds are heading to implicit hydrogens |

Contributors

| :octocat: | github | contact | | --------------- | ---------------------------------------- | ------------------------------------------------------------------------ | | Filip Stefaniak | @filipsPL | | | Natalia Szulc | @n-szulc | |

Owner

  • Name: filips
  • Login: filipsPL
  • Kind: user
  • Location: Warsaw, Poland
  • Company: @thervira @genesilico

- computer aided drug design + medicinal chemistry - python programming, web devel - ML - QSAR, tox prediction - :swimmer: :bicyclist: :runner:

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: >-
  fingeRNAt—A novel tool for high-throughput analysis
  of nucleic acid-ligand interactions: pymol plugin
message: pymol plugin for fingeRNAt
type: software
authors:
  - given-names: "Natalia A. Szulc "
    email: nszulc@iimcb.gov.pl
    affiliation: >-
      International Institute of Molecular and Cell
      Biology in Warsaw, Warsaw, Poland
    orcid: "https://orcid.org/0000-0002-2991-3634"
  - given-names: Zuzanna Mackiewicz
    email: zmackiewicz@iimcb.gov.pl
    affiliation: >-
      International Institute of Molecular and Cell
      Biology in Warsaw, Warsaw, Poland
    orcid: "https://orcid.org/0000-0003-1654-9025"
  - orcid: "https://orcid.org/0000-0002-6633-165X"
    given-names: Janusz M. Bujnicki
    email: janusz@iimcb.gov.pl
    affiliation: >-
      International Institute of Molecular and Cell
      Biology in Warsaw, Warsaw, Poland
  - orcid: "https://orcid.org/0000-0001-5758-9416"
    given-names: Filip Stefaniak
    affiliation: >-
      International Institute of Molecular and Cell
      Biology in Warsaw, Warsaw, Poland
    email: fstefaniak@iimcb.gov.pl
identifiers:
  - type: doi
    value: 10.1371/journal.pcbi.1009783
  - type: url
    value: >-
      https://github.com/filipsPL/fingernat-pymol-plugin
    description: GitHub repository
  - type: doi
    value: 10.5281/zenodo.7341533
    description: Zenodo github repository
repository-code: "https://github.com/filipsPL/fingernat-pymol-plugin"
url: "https://github.com/n-szulc/fingeRNAt/"
abstract: >-
  Computational methods play a pivotal role in drug
  discovery and are widely applied in virtual
  screening, structure optimization, and compound
  activity profiling. Over the last decades, almost
  all the attention in medicinal chemistry has been
  directed to protein-ligand binding, and
  computational tools have been created with this
  target in mind. With novel discoveries of
  functional RNAs and their possible applications,
  RNAs have gained considerable attention as
  potential drug targets. However, the availability
  of bioinformatics tools for nucleic acids is
  limited. Here, we introduce fingeRNAt—a software
  tool for detecting non-covalent interactions formed
  in complexes of nucleic acids with ligands. The
  program detects nine types of interactions: (i)
  hydrogen and (ii) halogen bonds, (iii)
  cation-anion, (iv) pi-cation, (v) pi-anion, (vi)
  pi-stacking, (vii) inorganic ion-mediated, (viii)
  water-mediated, and (ix) lipophilic interactions.
  However, the scope of detected interactions can be
  easily expanded using a simple plugin system. In
  addition, detected interactions can be visualized
  using the associated PyMOL plugin, which
  facilitates the analysis of medium-throughput
  molecular complexes. Interactions are also encoded
  and stored as a bioinformatics-friendly Structural
  Interaction Fingerprint (SIFt)—a binary string
  where the respective bit in the fingerprint is set
  to 1 if a particular interaction is present and to
  0 otherwise. This output format, in turn, enables
  high-throughput analysis of interaction data using
  data analysis techniques. We present applications
  of fingeRNAt-generated interaction fingerprints for
  visual and computational analysis of RNA-ligand
  complexes, including analysis of interactions
  formed in experimentally determined RNA-small
  molecule ligand complexes deposited in the Protein
  Data Bank. We propose interaction fingerprint-based
  similarity as an alternative measure to RMSD to
  recapitulate complexes with similar interactions
  but different folding. We present an application of
  interaction fingerprints for the clustering of
  molecular complexes. This approach can be used to
  group ligands that form similar binding networks
  and thus have similar biological properties. The
  fingeRNAt software is freely available at
  https://github.com/n-szulc/fingeRNAt.
keywords:
  - rna
  - small molecules
  - non-covalent interactions
  - interaction fingerprint
  - python
  - drug design
license: Apache-2.0

GitHub Events

Total
Last Year

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 60
  • Total Committers: 3
  • Avg Commits per committer: 20.0
  • Development Distribution Score (DDS): 0.1
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Filip s****k@g****m 54
Natalia Szulc n****c@i****l 4
ImgBotApp I****p@g****m 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 9 months ago

All Time
  • Total issues: 0
  • Total pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: 9 minutes
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.67
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 2
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
  • imgbot[bot] (2)
  • filipsPL (1)
Top Labels
Issue Labels
Pull Request Labels

Dependencies

.github/workflows/action-links.yml actions
  • actions/checkout master composite
  • gaurav-nelson/github-action-markdown-link-check v1 composite
.github/workflows/cffconvert.yml actions
  • actions/checkout v2 composite
  • citation-file-format/cffconvert-github-action 2.0.0 composite