The aim of this repo is to be able to predict the probability of secondary structure conformation based on the sequence of amino acid only with a Artifical intelligence model: ProtTrans. Once these probabilities computed, give personalised dyhedral angle potentials for each amino acid based on sequence information. This will make it possible to make proteins more flexible/regionally oriented and thus ensure better folding.

Before using this code, ensure that you have the following prerequisites in place:

• Python 3.7 or later
• PyTorch
• Transformers library
• H5py
• Numpy
• Pandas

Please find all information in requirements

If you plan to run this code locally, you need access to a GPU with at least 5.2GB of memory.

1. Clone the repository to your local machine.

   git clone https://github.com/Romumrn/martini_AI
   cd martini_AI

2. Install the required Python libraries using pip.

pip install -r requirements.txt

3. Run the code for protein secondary structure prediction. You can provide a sequence as a command-line argument.

python run_martini_AI.py --sequence "SEQUENCE" --sequence_id "ID"
#or
python run_martini_AI.py --fasta protain.fasta

You can also try the test case provided on google collab

(Not tested yes)