Metadata-Version: 2.1
Name: smrtnet_latest
Version: 0.21
Summary: A python lib for predicting small molecule-RNA interactions (SRIs)
Home-page: https://github.com/Yuhan-Fei/SMRTnet
Author: yuhan_Fei & jiasheng_Zhang
Author-email: yuhan_fei@outlook.com
License: MIT
Requires-Python: ==3.8.10
License-File: LICENSE
Requires-Dist: babel
Requires-Dist: charset-normalizer==3.3.2
Requires-Dist: dgllife
Requires-Dist: matplotlib
Requires-Dist: networkx
Requires-Dist: huggingface-hub
Requires-Dist: notebook
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: prefetch_generator
Requires-Dist: prettytable
Requires-Dist: pytorch-lightning
Requires-Dist: rdkit==2022.3.5
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: tensorboard
Requires-Dist: tensorboardX
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Requires-Dist: transformers==4.28.1
Requires-Dist: xsmiles

Small molecules can bind RNAs to regulate their fate and functions, providing promising opportunities for treating human diseases. However, current tools for predicting small molecule-RNA interactions (SRIs) require prior knowledge of RNA tertiary structures, limiting their utility in drug discovery. Here, we present SMRTnet, a deep learning method to predict SRIs based on RNA secondary structure. By integrating large language models, convolutional neural networks, graph attention networks, and multimodal data fusion, SMRTnet achieves high performance across multiple experimental benchmarks, substantially outperforming existing state-of-the-art tools.
