Skip to main content
# ProLIF
Protein-Ligand Interaction Fingerprints

:warning: This project is under development, do not use it in the current state :warning:

## :small_blue_diamond: Description

ProLIF is a tool designed to generate Interaction FingerPrints (IFP) and compute similarity scores for protein-ligand interactions, given a reference ligand and a list of binding-site residues.

## :small_blue_diamond: Installation

ProLIF is written in Python 3, and uses the following non-standard libraries:
* [rdkit](http://www.rdkit.org/docs/Install.html)

To install rdkit with Anaconda, use the following command:
```
conda install -c rdkit rdkit
```

## :small_blue_diamond: Usage

```
INPUT arguments:
-r fileName, --reference fileName
Path to your reference ligand.
-l fileName [fileName ...], --ligand fileName [fileName ...]
Path to your ligand(s).
-p fileName, --protein fileName
Path to your protein.
--residues RESIDUES [RESIDUES ...]
Residues chosen for the interactions. Default: automatically detect residues within --cutoff of the reference ligand
--cutoff float Cutoff for automatic residue detection. Default: 5.0 angströms
--json fileName Path to a custom parameters file. Default: prolif.json

OUTPUT arguments:
-o filename, --output filename
Path to the output CSV file
-v, --verbose Increase terminal output verbosity

Other arguments:
--interactions bit [bit ...]
List of interactions used to build the fingerprint.
-) hydrogen bond: HBdonor, HBacceptor
-) halogen bond: XBdonor
-) ionic: cation, anion
-) pi-stacking: FaceToFace, FaceToEdge
-) hydrophobic
-) pi-cation
-) metal
Default: HBdonor HBacceptor cation anion FaceToFace FaceToEdge pi-cation hydrophobic
--score {tanimoto,dice,tversky}
Similarity score between molecule A and B :
Let 'a' and 'b' be the number of bits activated in molecules A and B, and 'c' the number of activated bits in common.
-) tanimoto : c/(a+b-c). Used by default
-) dice : 2c/(a+b)
-) tversky : c/(alpha*(a-c)+beta*(b-c)+c)
--alpha int Alpha parameter for Tversky. Default: 0.7
--beta int Beta parameter for Tversky. Default: 0.3

Mandatory arguments: --reference --ligand --protein
MOL2 files only.
```

## :small_blue_diamond: License

Unless otherwise noted, all files in this directory and all subdirectories are distributed under the Apache License, Version 2.0:
```
Copyright 2017 Cédric BOUYSSET

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
```

Metadata

Release files for prolif 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for prolif 0.1.1
File Size Uploaded Provenance Actions
prolif-0.1.1.tar.gz 11.5 kB Without provenance Details for prolif-0.1.1.tar.gz

Release files / prolif-0.1.1.tar.gz

Download URL prolif-0.1.1.tar.gz
Size 11.5 kB
Tags Source
SHA-256 checksum
How to use checksums
f0db6810a6968449ee0ae0f139aed808e438e9832b0c86f2024731ab954e83a9
BLAKE2b-256 checksum
How to use checksums
f5a45210c5edee98a7647ceb04caadbba59b3805b10f4e23b873835eeb173791
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Security for prolif 0.1.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.1 This release

1 release file No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page