RSALOR

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: Matsvei Tsishyn, Pauline Hermans, Fabrizio Pucci, Marianne Rooman (2025). Residue conservation and solvent accessibility are (almost) all you need for predicting mutational effects in proteins. bioRxiv 2025.02.03.636212.

Installation and Usage

Installation with pip:

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:

# 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)

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:

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