The DeepDRP is a predict tool for intrinsically disordered regions in protein and is built by Python framework.
Abstract Intrinsic disorder in proteins, a widely distributed phenomenon in nature, is related to many crucial biological processes and various diseases. Traditional determination methods tend to be high-cost and time-consuming, therefore it is desirable to seek an accurate identification method of intrinsically disordered proteins (IDPs). In this paper, we proposed a novel Deep learning model for Intrinsically Disordered Regions in Proteins named DeepDRP. DeepDRP employed an innovative TimeDistributed strategy and Bi-LSTM architecture to predict IDPs and is driven by integrated view features of PSSM, Energy-based encoding, AAindex, and transformer-enhanced embeddings including DR-BERT, OntoProtein, Prot-T5, and ESM-2. The comparison of different feature combinations indicates that the transformer-enhanced features contribute far more than traditional features to predict IDPs and ESM-2 accounts for a larger contribution in the pre-trained fusion vectors. The ablation test verified that the novel TimeDistributed strategy surely increased the model performance and is an efficient approach to the IDP prediction. Compared with state-of-the-art models on the DISORDER723, S1, and DisProt832 datasets, the Matthews correlation coefficient of DeepDRP significantly outperformed competing methods by 4.90% to 36.20%, 11.80% to 26.33%, and 4.82% to 13.55%. In brief, DeepDRP is a reliable model for IDP prediction and is freely available at https://github.com/ZX-COLA/DeepDRP.
Make sure the following python library is installed before using.
conda create -n DeepDRP python=3.10
conda activate DeepDRP
pip install tensorflow
pip3 install torch torchvision torchaudio
pip install scikit-learn
pip install transformers
pip install SentencePiece
#if you want to use a GUI version of DeepDRP
pip install pyqt6
We only provide the Linux version psi-blast in the software, if you are a MacOS or Windows user, please replace the whole psi-blast tool in the lib folder. Download and install BLAST+. Installers and source code are available from https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/.
You need to download the model weights into the lib folder. Weights available at https://xxx.
/DeepDRP/demo/DP00588.fasta
/DeepDRP/demo/4RBXA.fasta
if you already have the pssm results of the protein, please put the .pssm file into the tmp folder, the DeepDRP will first check if the pssm file exists. If not exist, the program will run the psiblast automatically.
Run in command line:
cd DeepDRP
conda activate DeepDRP
python predict.py -i <filelist> -o <output_path>
#Demo
cd DeepDRP
conda activate DeepDRP
python predict.py -i ./demo/filelist -o ./results
Run in GUI mode:
cd DeepDRP
conda activate DeepDRP
python GUI.py