RPcontact: RNA-Protein Contact Prediction

Improved prediction of RNA-protein contacts using RNA and protein language models

Overview

RPcontact is a novel computational tool for accurately predicting RNA-protein contacts, addressing a fundamental challenge in understanding molecular biology processes such as transcription, splicing, and translation. Traditional methods are limited by the scarcity of RNA-protein complex structures and the constraints of experimental techniques. While recent deep learning approaches like AlphaFold 3 and RoseTTAFoldNA have made progress, they still rely heavily on homologous templates.

RPcontact overcomes these limitations by leveraging large language models specifically designed for RNA (ERNIE-RNA) and proteins (ESM-2). Trained exclusively on ribosomal RNA-protein complexes, RPcontact delivers robust and generalized performance, accurately predicting contacts in both dimeric and multimeric non-rRNA-protein complexes. Benchmark results show that RPcontact significantly outperforms binary contacts inferred from models like AlphaFold 3 and RoseTTAFoldNA, making it a valuable tool for structure and function prediction in RNA-protein research.

Quick Start

Requirements

Dependency	Recommended Version
Python	≥ 3.8
PyTorch	1.13.1
fair-esm	1.0.2

Install dependencies (example):

pip install numpy pandas matplotlib biopython scikit-learn
pip install torch==1.13.1
pip install fair-esm==1.0.2

Script Overview

Script	Function	Example Command
predict.py	Single RNA-protein pair contact prediction	`python predict.py`
predict_batch.py	Batch RNA-protein pairs contact prediction	`python predict_batch.py`
evaluate.py	Evaluation and visualization	`python evaluate.py`
app.py	Launch web-based demo interface (need install gradio)	`python app.py`

Data Preparation

RNA/protein sequences: FASTA format
Embedding features: pickle format
For batch prediction: provide a CSV file for pairing info

Typical Usage

Single pair prediction:

python predict.py --fasta your_sequence.fasta --out output_dir/

Batch prediction:

python predict_batch.py --rna_fasta rna.fasta --pro_fasta protein.fasta --csv pairs.csv --out output_dir/

Evaluation:

python evaluate.py --fasta your_sequence.fasta --out eval_dir/ --flabel true_labels.pickle

Common Parameters

Parameter	Description
--fasta	Input FASTA file (for single prediction)
--rna_fasta	RNA FASTA file (for batch prediction)
--pro_fasta	Protein FASTA file (for batch prediction)
--csv	RNA-protein pairing info CSV (for batch prediction)
--ffeat	Precomputed embedding feature file (pickle format)
--fmodel	Pretrained model file path
--out	Output directory
--flabel	True label file (for evaluation)
--device	Specify device (e.g., cpu or cuda:0)
--draw	Whether to visualize results

Output Interpretation

The prediction output is a contact probability matrix for each RNA-protein pair. Higher scores indicate a higher probability of interaction.
The evaluation script provides accuracy and other metrics, as well as visualization.

Contact & Citation

Questions or suggestions? Contact:

Jiuhong Jiang
Email: jiangjh2023@shanghaitech.edu.cn

If you find this project helpful, please cite our manuscript. - Jiang, J., Zhang, X., Zhan, J., Miao, Z., & Zhou, Y. (2025). RPcontact: Improved prediction of RNA-protein contacts using RNA and protein language models. bioRxiv, 2025-06.

Make RNA-protein contact prediction easier and more accurate!