Protein Cleavage Site Prediction

This project aims to predict the position of cleavage sites in protein sequences. The sequences of amino acids, starting from the N-terminal side, are used to represent proteins. Each amino acid is denoted by a letter code, with most uppercase letters used in this encoding.

Project Overview

The project begins with a simple statistical model to establish a reference. We then aim to improve accuracy using specific kernel functions for Support Vector Machines (SVMs).

Data

The data used in this project consists of sequences of amino acids. An example of a protein sequence is shown below, where the cleavage site is marked as the bond between the two underlined AR amino acids:

Installation

To use the different models we fitted and selected : load the desired model using : joblib -> loaded_model = joblib.load('best_svm_model_accuracy_PROBA.pkl')

each of these models have been trained on different lengths of cleavage site neighborhoods
Here are the following lengths :
    - BLOSUM Model -> p = 13, q = 2 , n = 15
    - Probabilistic Model -> p = 9, q = 2, n = 11
    - Model using the scalar product with poly -> p = 13, q = 2, n = 15
    - Model using the scalar product with poly -> p = 13, q = 2, n = 15

Predict Cleavage Sites with SVM Models

predict_cleavage.py This Python script predicts protein cleavage sites using pre-trained SVM models with various kernels (RBF, BLOSUM, scalar, probabilistic). Input can be a sequence string or a file path to a dataset with multiple sequences.

Models and Paths:
    rbf: data/models/best_svm_rbf.pkl
    blosum: data/models/best_svm_model_accuracy_BLOSUM.pkl
    scalar: data/models/best_svm_model_accuracy_scalar.pkl
    probabilistic: data/models/best_svm_model_accuracy_PROBA.pkl

Parameters:
    p=13, q=2 for all models

Usage:
    Run: python predict_cleavage.py <kernel> <sequence or file path>
    Example: python predict_cleavage.py rbf "MAGTMAASSAAGLAGLGLAAG"

Output:
    Displays the sequence with predicted cleavage sites in bold.
    Writes accuracy, average number of predictions, and average distance to real cleavage sites to data/results/results_predict_cleavage.txt.

other files

We used other files and notebooks to tune our parameters.