ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction

This repo presents the implementation of the ProLLM🧬

The paper has been accepted by COLM 2024.

Paper link: https://openreview.net/forum?id=2nTzomzjjb#discussion

Arxiv link: https://arxiv.org/abs/2405.06649

Website link: https://tiuxuxsh76075.github.io/prollm.github.io/

We present Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction, abbreviated as ProLLM. This innovative framework leverages the advanced capabilities of Large Language Models (LLMs) to interpret and analyze protein sequences and interactions through a natural language processing lens.

Key Features of ProLLM🔑

Protein Chain of Thought (ProCoT) Method: ProLLM introduces the Protein Chain of Thought (ProCoT) method, transforming the complex, structured data of protein interactions into intuitive, natural language prompts.
Enhanced Predictive Accuracy: This approach not only facilitates a deeper understanding of protein functions and interactions but also enhances the model's predictive accuracy by incorporating protein-specific embeddings and instruction fine-tuning on domain-specific datasets.

Requirements

pip install -r requirements.txt

Usage🧰

Dataset🧑‍💻

Download SHS27K, SHS148K, STRING and Human

Preprocess

Preprocess the dataset into Protein Chain of Thought (ProCoT) by the ./data_preprocess/[dataset_name]/preprocess.py
```
python [dataset]_preprocess.py
```

Embedding replacement

Do the embedding replacement in ./embedding_replacement

Instruction finturning

Instruction fintuning in ./Instruction_fintuning

train🧑‍💻

Do training through train_ProLLM.py , make sure the location of model and tokenizer in right place. Feel free to change 'num_epochs', 'batch_size' and 'learning_rate'.

python train_ProLLM.py --model_dir /path/to/model/dir --tokenizer_dir /path/to/tokenizer/dir --data_file dataset.csv --num_epochs 1 --batch_size 2 --learning_rate 3e-4 --output_dir /path/to/output/dir

Citation

If you find this paper helpful, please consider to cite:

@inproceedings{
jin2024prollm,
title={Pro{LLM}: Protein Chain-of-Thoughts Enhanced {LLM} for Protein-Protein Interaction Prediction},
author={Mingyu Jin and Haochen Xue and Zhenting Wang and Boming Kang and Ruosong Ye and Kaixiong Zhou and Mengnan Du and Yongfeng Zhang},
booktitle={First Conference on Language Modeling},
year={2024},
url={https://openreview.net/forum?id=2nTzomzjjb}
}

@article{jin2024prollm,
  title={ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction},
  author={Jin, Mingyu and Xue, Haochen and Wang, Zhenting and Kang, Boming and Ye, Ruosong and Zhou, Kaixiong and Du, Mengnan and Zhang, Yongfeng},
  journal={arXiv e-prints},
  pages={arXiv--2405},
  year={2024}
}

MingyuJ666 / ProLLM

readme