SAAMBE-3D is a tool written in python 3, it is tested to work with python3.7. SAAMBE-3D implements a structure based mathod for predicting the binding free energy change for protein-protein due to a point-mutation. It requires the 3D structure in PDB of the protein-protein complex as input and information about the mutation to make the prediction.
- i) predict the binding free energy change caused by single mutation, and
- ii) predict whether a particular mutation is disruptive or non-disruptive.
SAAMBE-3D requires following packages and mentioned versions to be installed in the python (Python 3.11.5) to work
- numpy (1.26.0)
- prody (2.4.0)
- xgboost (1.7.6)
It has been tested to work on a machine running Ubunutu 22.04.3. The python is mainted using conda 23.7.2. We created a python environment for SAAMBE-3D using:
conda create -n py311_saambe3d python=3.11Then if any conda environment is already active deactivate it using:
conda deactivateActivate the conda python environemnt created above using:
conda activate py311_saambe3dAll the above versions of packages are installed using following commands.
conda install -c conda-forge numpy=1.26.0
conda install -c conda-forge prody=2.4.0
conda install -c conda-forge xgboost=1.7.6downgrade the pyparsing to 3.1.1 if higher version installed, as it leads to error in selection parsing using prody. One can use below command for it.
conda install -c conda-forge pyparsing==3.1.1
Alternatively one can create the python enviroment py311_saambe3d from the
environment.yaml file using command:
conda env create --file=environment.yml
The method provides two different models for predictions:
- regression.model (for predicting: binding free energy change)
- classification.model (for prediction: if the mutation is disruptive or non-disruptive)
To have a look at and familiarize yourself with all the options supported use:
python saambe-3d.py --helpThe SAAMBE-3D can be run for a single point mutation by executing following command from inside of the SAAMBE-3D directory:
python saambe-3d.py -i PDBfile -c Chain -r Resid -w wild -m mutation -d modelTo make predictionsof a list of point-mutations execute:
saambe-3d.py -i PDBfile -f mutation_list -d modelFor example if user want to predict binding free energy for protein-protein complex with PDB ID 1A22 due to mutation from Cysteine (C) to Alanine (A) at res ID 182 in chain A, they should run the script by typing
python saambe-3d.py -i 1A22.pdb -c A -r 182 -w C -m A -d 1After running it check the file output.out or the file name if you provided any with sammbe-3d.py -o option for the output.
If user want to get multiple predictions for many single mutations at the same complex, user can provide a file
say mutations_list.txt, which should be formatted as follows for the above example.
The columns in the mutation list file are: ChainID resID wildtype_residue mutant_residue
A 182 C A and the command will be:
python saambe-3d.py -i 1A22.pdb -f mutations_list.txt -d 1After running it check the file output.out or the file name if you provided any with sammbe-3d.py -o option for the output.
Similarly. for predicting disruptive/non-disruptive mutation, user can type the same command, just need to change the model from 1 to 0
python saambe-3d.py -i 1A22.pdb -c A -r 182 -w C -m A -d 0After running it check the file output.out or the file name if you provided any with sammbe-3d.py -o option for the output.
OR
python saambe-3d.py -i 1A22.pdb -f mutations_list.txt -d 0After running it check the file output.out or the file name if you provided any with sammbe-3d.py -o option for the output.
The 'mutations_list.txt' will be exactly same.
Pahari, S., Li, G., Murthy, A. K., Liang, S., Fragoza, R., Yu, H., & Alexov, E. (2020). SAAMBE-3D: predicting effect of mutations on protein–protein interactions. International journal of molecular sciences, 21(7), 2563.
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