Metadata-Version: 2.1
Name: rsalor
Version: 1.0.9
Summary: Combines structural data (Relative Solvent Accessibility, RSA) and evolutionary data (Log Odd Ratio, LOR from MSA) to evaluate missense mutations in proteins.
Home-page: https://github.com/3BioCompBio/RSALOR
Author: Matsvei Tsishyn
Author-email: matsvei.tsishyn@protonmail.com
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C++
Classifier: Programming Language :: C
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENCE
Requires-Dist: numpy
Requires-Dist: biopython>=1.75


# RSALOR

[![PyPi Version](https://img.shields.io/pypi/v/rsalor.svg)](https://pypi.org/project/rsalor/) [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

`rsalor` is a Python package that computes the `RSA*LOR` score for each missence mutation in a protein. It combines multiple computational steps into a fast and user-friendly tool.

**Please cite**:
Hermans, P., Tsishyn, M., Schwersensky, M., Rooman, M., & Pucci, F. (2024). Exploring evolution to uncover insights into protein mutational stability. Molecular Biology and Evolution, msae267.  
[Link to publication](https://academic.oup.com/mbe/advance-article/doi/10.1093/molbev/msae267/7934942).

## Installation and Usage

Installation with `pip`:
```bash
pip install rsalor
```

Make sure the first sequence in your MSA file is the target sequence to mutate.  
From directory `./test_data/` execute the following Python code:
```python
# Import
from rsalor import MSA

# Log basic usage instructions and arguments of the package
MSA.help()

# Initialize MSA
msa_path = "./6acv_A_29-94.fasta"
pdb_path = "./6acv_A_29-94.pdb"
chain = "A"
msa = MSA(msa_path, pdb_path, chain, num_threads=8, verbose=True)

# You can ignore structure and RSA by omitting the pdb_path argument
#msa = MSA(msa_path, num_threads=8, verbose=True)

# Get LOR and other scores for all mutations
scores = msa.get_scores() # [{'mutation_fasta': 'S1A', 'mutation_pdb': 'SA1A', 'RSA': 61.54, 'LOR': 5.05, ...}, ...]

# Or directly save scores to a CSV file
msa.save_scores("./6acv_A_29-94_scores.csv", sep=";")
```

## Requirements

- Python 3.9 or later
- Python packages `numpy` ans `biopython` (version 1.75 or later)
- A C++ compiler that supports C++11 (such as GCC)

An example of a working `conda` environment is provided in `./conda-env.yml`.

## Short description

The `rsalor` package combines structural data (Relative Solvent Accessibility, RSA) and evolutionary data (Log Odd Ratio, LOR from MSA) to evaluate missense mutations in proteins.

It parses a Multiple Sequence Alignment (MSA), removes redundant sequences, and assigns a weight to each sequence based on sequence identity clustering. The package then computes the weighted Log Odd Ratio (LOR) and Log Ratio (LR) for each single missense mutation. Additionally, it calculates the Relative Solvent Accessibility (RSA) for each residue and combines the LOR/LR and RSA scores, as described in the reference paper. The package resolves discrepancies between the MSA's target sequence and the protein structure (e.g., missing residues in structure) by aligning the PDB structure with the MSA target sequence.

## Compile from source

For performance reasons, `rsalor` uses a C++ backend to weight sequences in the MSA. The C++ code needs to be compiled to use it directly from source. To compile the code, follow these steps:
```bash
git clone https://github.com/3BioCompBio/RSALOR # Clone the repository
cd RSALOR/rsalor/weights/            # Navigate to the C++ code directory
mkdir build                          # Create a build directory
cd build                             # Enter the build directory
cmake ..                             # Generate make files
make                                 # Compile the C++ code
mv ./lib_computeWeightsBackend* ../  # Move the compiled file to the correct directory
```
