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RSS FeedsIJMS, Vol. 20, Pages 4102: Prediction of Potential Drug-Disease Associations through Deep Integration of Diversity and Projections of Various Drug Features (International Journal of Molecular Sciences)

 
 

22 august 2019 19:01:59

 
IJMS, Vol. 20, Pages 4102: Prediction of Potential Drug-Disease Associations through Deep Integration of Diversity and Projections of Various Drug Features (International Journal of Molecular Sciences)
 




Identifying new indications for existing drugs may reduce costs and expedites drug development. Drug-related disease predictions typically combined heterogeneous drug-related and disease-related data to derive the associations between drugs and diseases, while recently developed approaches integrate multiple kinds of drug features, but fail to take the diversity implied by these features into account. We developed a method based on non-negative matrix factorization, DivePred, for predicting potential drug–disease associations. DivePred integrated disease similarity, drug–disease associations, and various drug features derived from drug chemical substructures, drug target protein domains, drug target annotations, and drug-related diseases. Diverse drug features reflect the characteristics of drugs from different perspectives, and utilizing the diversity of multiple kinds of features is critical for association prediction. The various drug features had higher dimensions and sparse characteristics, whereas DivePred projected high-dimensional drug features into the low-dimensional feature space to generate dense feature representations of drugs. Furthermore, DivePred’s optimization term enhanced diversity and reduced redundancy of multiple kinds of drug features. The neighbor information was exploited to infer the likelihood of drug–disease associations. Experiments indicated that DivePred was superior to several state-of-the-art methods for prediction drug-disease association. During the validation process, DivePred identified more drug-disease associations in the top part of prediction result than other methods, benefitting further biological validation. Case studies of acetaminophen, ciprofloxacin, doxorubicin, hydrocortisone, and ampicillin demonstrated that DivePred has the ability to discover potential candidate disease indications for drugs.


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24 viewsCategory: Biochemistry, Biophysics, Molecular Biology
 
IJMS, Vol. 20, Pages 4103: Systematic Analysis of Differentially Expressed Maize ZmbZIP Genes between Drought and Rewatering Transcriptome Reveals bZIP Family Members Involved in Abiotic Stress Responses (International Journal of Molecular Sciences)
IJMS, Vol. 20, Pages 4101: An Update on Pharmacological Potential of Boswellic Acids against Chronic Diseases (International Journal of Molecular Sciences)
 
 
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