AIMC Topic: Drug Repositioning
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Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Mar 20, 2024
Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-modifying treatments for PD remains a major unmet medical need. Notably, drug repositioning is becomin...
Drug Repositioning via Graph Neural Networks: Identifying Novel JAK2 Inhibitors from FDA-Approved Drugs through Molecular Docking and Biological Validation.
Molecules (Basel, Switzerland)
Mar 19, 2024
The increasing utilization of artificial intelligence algorithms in drug development has proven to be highly efficient and effective. One area where deep learning-based approaches have made significant contributions is in drug repositioning, enabling...
Drug discovery and development: the role of artificial intelligence in drug repurposing.
Future medicinal chemistry
Mar 1, 2024
Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.
Frontiers in immunology
Feb 13, 2024
INTRODUCTION: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable...
Prediction of Drug-Disease Associations Based on Multi-Kernel Deep Learning Method in Heterogeneous Graph Embedding.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 5, 2024
Computational drug repositioning can identify potential associations between drugs and diseases. This technology has been shown to be effective in accelerating drug development and reducing experimental costs. Although there has been plenty of resear...
A deep learning framework for predicting molecular property based on multi-type features fusion.
Computers in biology and medicine
Dec 28, 2023
Extracting expressive molecular features is essential for molecular property prediction. Sequence-based representation is a common representation of molecules, which ignores the structure information of molecules. While molecular graph representation...
Anti-Dengue: A Machine Learning-Assisted Prediction of Small Molecule Antivirals against Dengue Virus and Implications in Drug Repurposing.
Viruses
Dec 27, 2023
Dengue outbreaks persist in global tropical regions, lacking approved antivirals, necessitating critical therapeutic development against the virus. In this context, we developed the "Anti-Dengue" algorithm that predicts dengue virus inhibitors using ...
Drug Repositioning Based on Deep Sparse Autoencoder and Drug-Disease Similarity.
Interdisciplinary sciences, computational life sciences
Dec 16, 2023
Drug repositioning is critical to drug development. Previous drug repositioning methods mainly constructed drug-disease heterogeneous networks to extract drug-disease features. However, these methods faced difficulty when we are using structurally si...
SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution.
Journal of chemical information and modeling
Dec 16, 2023
Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influe...
Identification of new potential candidates to inhibit EGF via machine learning algorithm.
European journal of pharmacology
Nov 23, 2023
One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The advantage of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerat...
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