DeepLPI: a novel deep learning-based model for protein–ligand interaction prediction for drug repurposing

DOI: 10.1038/s41598-022-23014-1

Authors: Bomin Wei (Princeton International School of Mathematics and Science) , Yue Zhang (University of Utah) , Xiang Gong (Princeton International School of Mathematics and Science)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Scientific Reports , VOL 12

State: Published (Approved)
Published: October 2022

Abstract: The substantial cost of new drug research and development has consistently posed a huge burden for both pharmaceutical companies and patients. In order to lower the expenditure and development failure rate, repurposing existing and approved drugs by identifying interactions between drug molecules and target proteins based on computational methods have gained growing attention. Here, we propose the DeepLPI, a novel deep learning-based model that mainly consists of ResNet-based 1-dimensional convolutional neural network (1D CNN) and bi-directional long short term memory network (biLSTM), to establish an end-to-end framework for protein–ligand interaction prediction. We first encode the raw drug molecular sequences and target protein sequences into dense vector representations, which go through two ResNet-based 1D CNN modules to derive features, respectively. The extracted feature vectors are concatenated and further fed into the biLSTM network, followed by the MLP module to finally predict protein–ligand interaction. We downloaded the well-known BindingDB and Davis dataset for training and testing our DeepLPI model. We also applied DeepLPI on a COVID-19 dataset for externally evaluating the prediction ability of DeepLPI. To benchmark our model, we compared our DeepLPI with the baseline methods of DeepCDA and DeepDTA, and observed that our DeepLPI outperformed these methods, suggesting the high accuracy of the DeepLPI towards protein–ligand interaction prediction. The high prediction performance of DeepLPI on the different datasets displayed its high capability of protein–ligand interaction in generalization, demonstrating that the DeepLPI has the potential to pinpoint new drug-target interactions and to find better destinations for proven drugs.

Diamond Keywords: COVID-19; Viruses

Subject Areas: Medicine, Information and Communication Technology

Diamond Offline Facilities: XChem
Instruments: NONE-No attached Diamond beamline

Added On: 02/11/2022 08:43

Documents:
s41598-022-23014-1.pdf

Discipline Tags:

Pathogens Infectious Diseases Artificial Intelligence Health & Wellbeing Information & Communication Technologies Drug Discovery Life Sciences & Biotech

Technical Tags:

Diffraction Macromolecular Crystallography (MX) Fragment Screening