https://github.com/radifar/pyplif-hippos

HIPPOS Is PyPLIF On Steroids. A Molecular Interaction Fingerprinting Tool for Docking Results of Autodock Vina and PLANTS
https://github.com/radifar/pyplif-hippos

autodock-vina drug-discovery interaction-fingerprinting molecular-docking virtual-screening

Last synced: 7 months ago
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HIPPOS Is PyPLIF On Steroids. A Molecular Interaction Fingerprinting Tool for Docking Results of Autodock Vina and PLANTS

• Host: GitHub
• URL: https://github.com/radifar/pyplif-hippos
• Owner: radifar
• License: other
• Created: 2020-06-04T13:40:38.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2023-08-15T13:07:18.000Z (almost 3 years ago)
• Last Synced: 2025-10-21T19:51:48.180Z (7 months ago)
• Topics: autodock-vina, drug-discovery, interaction-fingerprinting, molecular-docking, virtual-screening
• Language: Python
• Homepage: https://pyplif-hippos.readthedocs.io
• Size: 40.9 MB
• Stars: 31
• Watchers: 4
• Forks: 8
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

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README

          
# PyPLIF HIPPOS: A Molecular Interaction Fingerprinting Tool for Docking Results of AutoDock Vina and PLANTS

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Icons made by Freepik from Flaticon is licensed by CC 3.0 BY


Welcome to PyPLIF-HIPPOS's project page. PyPLIF-HIPPOS is an upgraded version of [PyPLIF](https://github.com/radifar/pyplif/) (**Python-based Protein-Ligand Interaction Fingerprinting**), a tool for molecular docking post-analysis. It will translate the 3D coordinates of both ligand(s) (generated from docking simulation) and protein into a series of *interaction bitstring* (also known as *Interaction Fingerprint*) (see image below). **HIPPOS** (/ˌhipoʊz/) is a recursive acronym of **HIPPOS Is PyPLIF On Steroids**. From this point forward, PyPLIF-HIPPOS is simplified to HIPPOS.

Compared to PyPLIF, HIPPOS is not only faster and able to generate more customized interaction bitstring, but also supports both [PLANTS](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/pharmazie-und-biochemie/pharmazie/pharmazeutische-chemie/pd-dr-t-exner/research/plants/) & [Vina](http://vina.scripps.edu/)! More over, unlike its predecessor it is (far) more well-documented.



  



Reprinted with permission from https://doi.org/10.1021/acs.jcim.0c00305. Copyright 2020 American Chemical Society.




  



Illustration by Radifar et al (2013) from Bioinformation.net is licensed by CC 4.0 BY

## Quick Installation

The easiest way to install HIPPOS is using [Anaconda or Miniconda](https://docs.anaconda.com/anaconda/install/).

If you have Anaconda or Miniconda ready in your machine, you can start with

creating new environment (recommended):

`conda create -n hippos python=3.6`

Then activate the environment and install HIPPOS:

`conda activate hippos`  

`conda install -c conda-forge pyplif-hippos`

next you can try run HIPPOS and HIPPOS-GENREF with the following command:

`hippos`  

`hippos-genref` 

## How to Use HIPPOS

So I already installed HIPPOS, now what? Well you could start with how to generate

the [reference bitstring](https://pyplif-hippos.readthedocs.io/en/latest/getting-started-genref.html)

and Getting Started tutorial for [AutoDock Vina](https://pyplif-hippos.readthedocs.io/en/latest/getting-started-vina.html)

or [PLANTS](https://pyplif-hippos.readthedocs.io/en/latest/getting-started-plants.html).

## Ideas for Improvement? Found Bug(s)?

If you have any idea for improvement or found bug to report feel free to write them [here](https://github.com/radifar/PyPLIF-HIPPOS/issues).

## Citing HIPPOS

If you are using HIPPOS please cite this paper:

Istyastono, E., Radifar, M., Yuniarti, N., Prasasty, V. and Mungkasi, S., 2020. 

PyPLIF HIPPOS: A Molecular Interaction Fingerprinting Tool for Docking Results 

of AutoDock Vina and PLANTS. Journal of Chemical Information and Modeling, 60(8), pp.3697-3702.

https://doi.org/10.1021/acs.jcim.0c00305

## Acknowledgment

This project has received funding from the [National Agency for Research and Innovation](https://international.ristekdikti.go.id/) (Indonesia)

under grant agreement No. 807.7/LL5/PG/2020. This project has been restructured based on the

[MOLSSI Computational Molecular Science Python Cookiecutter](https://github.com/molssi/cookiecutter-cms)

version 1.3, and benefited greatly from [MOLSSI Python Package Development Best Practices](https://molssi.org/2020/04/20/may-webinar-series-python-package-development/)

workshop.

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© Copyright 2021, Muhammad Radifar & Enade Perdana Istyastono