pepkit 0.0.2

Toolkit for peptide modelling

PepKit

Toolkit for Peptide Modeling and Analysis

PepKit is a comprehensive Python package for peptide-centric workflows, including sequence parsing, format conversion, descriptor calculation, clustering, structural modeling, and docking protocols.

Features

1. Sequence I/O and Standardization
   • Convert between FASTA and SMILES formats (fasta_to_smiles, smiles_to_fasta).
   • Standardize peptide sequences for downstream analysis.
2. Descriptors and Clustering
   • Compute physicochemical descriptors (e.g., molecular weight, hydrophobicity).
   • Cluster peptide libraries based on chemical similarity.
3. Binding Affinity Metrics
   • Calculate common metrics for peptide–target binding prediction.
   • Integrate with machine learning pipelines for affinity modeling.
4. Structural Modeling
   • Automated protocols for building peptide structures using AlphaFold and Rosetta.
   • Support for preparing input files and post-processing outputs.
5. Docking Workflows
   • High-throughput docking setup and analysis.
   • AlphaFold (AF) integration (under development) and Rosetta docking protocols.

Installation

Install via pip:

pip install pepkit

Or clone the repository

git clone https://github.com/Vivi-tran/PepKit.git
cd PepKit
pip install -e .

Quickstart

from pepkit import fasta_to_smiles, smiles_to_fasta

# FASTA to SMILES
seq = "ACDEFGHIK"
smiles = fasta_to_smiles(seq)
print(f"SMILES: {smiles}")

License

This project is licensed under MIT License - see the License file for details.